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Phinzi, Kwanele, Imre Holb, and Szilárd Szabó. "Mapping Permanent Gullies in an Agricultural Area Using Satellite Images: Efficacy of Machine Learning Algorithms." Agronomy 11, no. 2 (February 13, 2021): 333. http://dx.doi.org/10.3390/agronomy11020333.
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Gullies are responsible for detaching massive volumes of productive soil, dissecting natural landscape and causing damages to infrastructure. Despite existing research, the gravity of the gully erosion problem underscores the urgent need for accurate mapping of gullies, a first but essential step toward sustainable management of soil resources. This study aims to obtain the spatial distribution of gullies through comparing various classifiers: k-dimensional tree K-Nearest Neighbor (k-d tree KNN), Minimum Distance (MD), Maximum Likelihood (ML), and Random Forest (RF). Results indicated that all the classifiers, with the exception of ML, achieved an overall accuracy (OA) of at least 0.85. RF had the highest OA (0.94), although it was outperformed in gully identification by MD (0% commission), but the omission error was 20% (MD). Accordingly, RF was considered as the best algorithm, having 13% error in both adding (commission) and omitting pixels as gullies. Thus, RF ensured a reliable outcome to map the spatial distribution of gullies. RF-derived gully density map reflected the agricultural areas most exposed to gully erosion. Our approach of using satellite imagery has certain limitations, and can be used only in arid or semiarid regions where gullies are not covered by dense vegetation as the vegetation biases the extracted gullies. The approach also provides a solution to the lack of laser scanned data, especially in the context of the study area, providing better accuracy and wider application possibilities.
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Polychronaki, A., I. Z. Gitas, and A. Minchella. "Monitoring post-fire vegetation recovery in the Mediterranean using SPOT and ERS imagery." International Journal of Wildland Fire 23, no. 5 (2014): 631. http://dx.doi.org/10.1071/wf12058.
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This study examined the effect of two different forest fires 19 and 23 years ago on the Mediterranean island of Thasos. An object-based classification scheme was developed to map the major land-cover types using multi-temporal Système Pour l’Observation de la Terre (SPOT) and European Remote-Sensing (ERS) (C-band VV) images covering the time period from 1993 to 2007. The developed scheme mapped the post-fire land-cover types accurately: 0.84 Kappa coefficient and 90.5% overall accuracy. The use of the ERS backscatter coefficient contributed to decreasing the commission errors related to the mapping of forested areas and to overcoming misclassifications that occurred between forested areas and shrublands located in shadowed areas. Results indicated that the forest regeneration rate is rather slow, especially in areas where the degree of burn severity was high while the largest part of the burned area is, to date, covered by low vegetation and shrubs. Nevertheless, a gradual shift from low vegetation to shrubland was observed. A preliminary investigation on the use of the ERS backscatter coefficient and the Normalised Difference Vegetation Index to monitor forest regeneration revealed that the backscatter coefficient could provide information related to changes in dense regenerating pine forests for the first 18 years after the fire event, whereas the Normalised Difference Vegetation Index was found to be sensitive to the regenerating forest understorey vegetation. However, further investigation is needed to confirm these findings.
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Roy, S., G. Beig, and S. Ghude. "Exposure-plant response of ambient ozone over the tropical Indian region." Atmospheric Chemistry and Physics Discussions 9, no. 1 (February 9, 2009): 4141–57. http://dx.doi.org/10.5194/acpd-9-4141-2009.
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Abstract. A high resolution regional chemistry-transport model has been used to study the distribution of exposure-plant response index (AOT40, Accumulated exposure Over a Threshold of 40 ppb, expressed as ppb h) over the Indian geographical region for the year 2003 as case study. The directives on ozone pollution in ambient air provided by United Nations Economic Commission for Europe (UNECE) and World Health Organization (WHO) for vegetation protection (AOT40) have been used to assess the air quality. A substantial temporal and spatial variation in AOT40 values has been observed across the Indian region. Large areas of India show ozone values above the AOT40 threshold limit (3000 ppb h for 3 months). Simulated AOT40 values are found to be substantially higher throughout the year over the most fertile Indo-Gangetic plains than the other regions of India, which can have an adverse effect on plants and vegetation in this region. The observed monthly AOT40 values reported from an Indian station, agree reasonably well with model simulated results. We find that the simulated AOT40 target values for protection of vegetation is exceeded even in individual months, especially during November and April. Necessary and effective emission reduction strategies are therefore required to be developed in order to curb the surface level ozone pollution to protect the vegetation from further damage in India whose economy is highly dependent on agricultural sector and may influence the global balance.
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Deb Roy, S., G. Beig, and Sachin D. Ghude. "Exposure-plant response of ambient ozone over the tropical Indian region." Atmospheric Chemistry and Physics 9, no. 14 (July 29, 2009): 5253–60. http://dx.doi.org/10.5194/acp-9-5253-2009.
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Abstract. A high resolution regional chemistry-transport model has been used to study the distribution of exposure-plant response index (AOT40, Accumulated exposure Over a Threshold of 40 ppb, expressed as ppb h) over the Indian geographical region for the year 2003 as case study. The directives on ozone pollution in ambient air provided by United Nations Economic Commission for Europe (UNECE) and World Health Organization (WHO) for vegetation protection (AOT40) have been used to assess the air quality. A substantial temporal and spatial variation in AOT40 values has been observed across the Indian region. Large areas of India show ozone values above the AOT40 threshold limit (3000 ppb h for 3 months). Simulated AOT40 values are found to be substantially higher throughout the year over the most fertile Indo-Gangetic plains than the other regions of India, which can have an adverse effect on plants and vegetation in this region. The observed monthly AOT40 values reported from an Indian station, agree reasonably well with model simulated results. There is an underestimation of AOT40 in the model results during the periods of highest ozone concentration from December to March. We find that the simulated AOT40 target values for protection of vegetation is exceeded even in individual months, especially during November to April. Necessary and effective emission reduction strategies are therefore required to be developed in order to curb the surface level ozone pollution to protect the vegetation from further damage in India whose economy is highly dependent on agricultural sector and may influence the global balance.
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ZAIATZ, Ana Paula Sousa Rodrigues, Cornélio Alberto ZOLIN, Laurimar Goncalves VENDRUSCULO, Tarcio Rocha LOPES, and Janaina PAULINO. "Agricultural land use and cover change in the Cerrado/Amazon ecotone: A case study of the upper Teles Pires River basin." Acta Amazonica 48, no. 2 (April 2018): 168–77. http://dx.doi.org/10.1590/1809-4392201701930.
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ABSTRACT The upper Teles Pires River basin is a key hydrological resource for the state of Mato Grosso, but has suffered rapid land use and cover change. The basin includes areas of Cerrado biome, as well as transitional areas between the Amazon and Cerrado vegetation types, with intensive large-scale agriculture widely-spread throughout the region. The objective of this study was to explore the spatial and temporal dynamics of land use and cover change from 1986 to 2014 in the upper Teles Pires basin using remote sensing and GIS techniques. TM (Thematic Mapper) and TIRS (Thermal Infrared Sensor) sensor images aboard the Landsat 5 and Landsat 8, respectively, were employed for supervised classification using the “Classification Workflow” in ENVI 5.0. To evaluate classification accuracy, an error matrix was generated, and the Kappa, overall accuracy, errors of omission and commission, user accuracy and producer accuracy indexes calculated. The classes showing greatest variation across the study period were “Agriculture” and “Rainforest”. Results indicated that deforested areas are often replaced by pasture and then by agriculture, while direct conversion of forest to agriculture occured less frequently. The indices with satisfactory accuracy levels included the Kappa and Global indices, which showed accuracy levels above 80% for all study years. In addition, the producer and user accuracy indices ranged from 59-100% and 68-100%, while the errors of omission and commission ranged from 0-32% and 0-40.6%, respectively.
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Barandovski, Lambe, Trajce Stafilov, Robert Sajn, Marina Frontasyeva, and Katerina Baceva. "Air pollution study in Macedonia using a moss biomonitoring technique, ICP-AES and AAS." Macedonian Journal of Chemistry and Chemical Engineering 32, no. 1 (June 15, 2013): 89. http://dx.doi.org/10.20450/mjcce.2013.137.
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In the framework of the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops under the auspices of the United Nations Economic Commission for Europe (UNECE-ICP Vegetation) Convention on Long-Range Transboundary Air Pollution (LRTAP), in 2002 and 2005, a moss biomonitoring technique was applied to air pollution studies in the Republic of Macedonia. The third moss survey took place in August and September 2010 when 72 samples of the terrestrial mosses Homalothecium lutescens and Hypnum cupressiforme were collected over the territory of the Republic of Macedonia, using the same sampling network grid as for the previous surveys. Using inductively coupled plasma-atomic emission spectrometry (ICP-AES) and atomic absorption spectrometry (AAS), a total of 18 elements (Al, Ba, Ca, Cd, Cr, Cu, Fe, Hg, K, Li, Mg, Mn, Ni, P, Pb, Sr, V and Zn) were determined. To reveal hidden multivariate data structures and to identify and characterize different pollution sources, Principal Component Analysis was used. Distributional maps were prepared to point out the regions most affected by pollution and related to known sources of contamination. As in the previous surveys, the regions near the towns of Skopje, Veles, Tetovo, Radoviš and Kavadarci were found to be most affected by pollution, even though the median elemental content in the mosses in 2010 for Cd, Cr, Cu, Ni, Pb and Zn was slightly lower than in the previous surveys. For the first time, P content in the moss samples was analyzed, and a higher content of this element as well as K in the mosses was observed in the agricultural regions of the country.
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Dobes, Leo, Nathan Weber, Jeff Bennett, and Sue Ogilvy. "Stream-bed and flood-plain rehabilitation at Mulloon Creek, Australia: a financial and economic perspective." Rangeland Journal 35, no. 3 (2013): 339. http://dx.doi.org/10.1071/rj12098.
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Prior to European settlement, many Australian rivers were characterised by interconnected ‘chains of ponds’, with riparian vegetation preventing scour and subsequent channel erosion. Damage and destruction of vegetation by grazing animals has resulted in stream-channel incision and associated lowering of watertables on adjacent flood-plains. Proponents of natural sequence farming seek to restore hydro-geomorphic functionality by raising stream levels through construction of leaky weirs and revegetation. Lack of documentation of ‘before and after’ production data precludes evaluation of either the financial viability or the broader economic merits of raising stream levels. A case study, based on financial and economic costs, and possible benefits, at one site, highlighted the need for more targeted research that can be combined with an economic evaluation of stream rehabilitation. Only a more focussed, multidisciplinary research effort can reveal whether it is likely to be financially viable for individual properties or to be socially beneficial. The study also identified that government agencies should commission, and publish, the results of assessments of alternative schemes that have been used to control erosion or to rehabilitate streams, for comparative purposes. Similarly, a comprehensive cost–benefit analysis should be undertaken to ensure an objective basis for regulatory control over the management of water resources on Australian properties.
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Lowell, Kim, Ron Shamir, Andreia Siqueira, John White, Alice O'Connor, Gary Butcher, Mark Garvey, and Michael Niven. "Assessing the capabilities of geospatial data to map built structures and evaluate their bushfire threat." International Journal of Wildland Fire 18, no. 8 (2009): 1010. http://dx.doi.org/10.1071/wf08077.
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Bushfire threat was evaluated for built structures for three areas in Victoria (Australia) that had been impacted by the devastating 16 February 1983 Ash Wednesday fires. Structures were mapped for 1982 and 2006 using human interpretation of high-resolution (0.35-m pixels) digital orthophotographs. Damage to structures from the 1983 Ash Wednesday fires was also evaluated using human interpretation of the digital orthophotographs. Approximately 25% of the structures present were not mapped due to either interpreter error or overhanging vegetation. The majority of unmapped structures were sheds and garages. The error of omission for houses was between 7 and 10% with the error of commission for houses being less than 0.5%. Bushfire threat was modelled using information about topographic slope and aspect, forest vegetation, and prevailing wind direction during days of high fire danger. The method detected a substantial change in bushfire threat from 1982 to 2006 for one of the three study sites whereas no change in overall bushfire threat was observed for the other two. Considering the location of structures built since 1982, these results appeared reasonable. However, the 1982 bushfire threat was not related to actual structure damage sustained during the 1983 Ash Wednesday fires. Estimating bushfire threat using this methodology cost AU$6 per structure or AU$4.60 per property.
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Symeonakis, E., and T. Higginbottom. "Bush encroachment monitoring using multi-temporal Landsat data and random forests." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2 (November 11, 2014): 29–35. http://dx.doi.org/10.5194/isprsarchives-xl-2-29-2014.
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It is widely accepted that land degradation and desertification (LDD) are serious global threats to humans and the environment. Around a third of savannahs in Africa are affected by LDD processes that may lead to substantial declines in ecosystem functioning and services. Indirectly, LDD can be monitored using relevant indicators. The encroachment of woody plants into grasslands, and the subsequent conversion of savannahs and open woodlands into shrublands, has attracted a lot of attention over the last decades and has been identified as a potential indicator of LDD. Mapping bush encroachment over large areas can only effectively be done using Earth Observation (EO) data and techniques. However, the accurate assessment of large-scale savannah degradation through bush encroachment with satellite imagery remains a formidable task due to the fact that on the satellite data vegetation variability in response to highly variable rainfall patterns might obscure the underlying degradation processes. <br><br> Here, we present a methodological framework for the monitoring of bush encroachment-related land degradation in a savannah environment in the Northwest Province of South Africa. We utilise multi-temporal Landsat TM and ETM+ (SLC-on) data from 1989 until 2009, mostly from the dry-season, and ancillary data in a GIS environment. We then use the machine learning classification approach of random forests to identify the extent of encroachment over the 20-year period. The results show that in the area of study, bush encroachment is as alarming as permanent vegetation loss. The classification of the year 2009 is validated yielding low commission and omission errors and high k-statistic values for the grasses and woody vegetation classes. Our approach is a step towards a rigorous and effective savannah degradation assessment.
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Morton, Douglas C., Ruth S. DeFries, Yosio E. Shimabukuro, Liana O. Anderson, Fernando Del Bon Espírito-Santo, Matthew Hansen, and Mark Carroll. "Rapid Assessment of Annual Deforestation in the Brazilian Amazon Using MODIS Data." Earth Interactions 9, no. 8 (June 1, 2005): 1–22. http://dx.doi.org/10.1175/ei139.1.
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Abstract The Brazilian government annually assesses the extent of deforestation in the Legal Amazon for a variety of scientific and policy applications. Currently, the assessment requires the processing and storing of large volumes of Landsat satellite data. The potential for efficient, accurate, and less data-intensive assessment of annual deforestation using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution is evaluated. Landsat-derived deforestation estimates are compared to MODIS-derived estimates for six Landsat scenes with five change-detection algorithms and a variety of input data—Surface Reflectance (MOD09), Vegetation Indices (MOD13), fraction images derived from a linear mixing model, Vegetation Cover Conversion (MOD44A), and percent tree cover from the Vegetation Continuous Fields (MOD44B) product. Several algorithms generated consistently low commission errors (positive predictive value near 90%) and identified more than 80% of deforestation polygons larger than 3 ha. All methods accurately identified polygons larger than 20 ha. However, no method consistently detected a high percent of Landsat-derived deforestation area across all six scenes. Field validation in central Mato Grosso confirmed that all MODIS-derived deforestation clusters larger than three 250-m pixels were true deforestation. Application of this field-validated method to the state of Mato Grosso for 2001–04 highlighted a change in deforestation dynamics; the number of large clusters (>10 MODIS pixels) that were detected doubled, from 750 between August 2001 and August 2002 to over 1500 between August 2003 and August 2004. These analyses demonstrate that MODIS data are appropriate for rapid identification of the location of deforestation areas and trends in deforestation dynamics with greatly reduced storage and processing requirements compared to Landsat-derived assessments. However, the MODIS-based analyses evaluated in this study are not a replacement for high-resolution analyses that estimate the total area of deforestation and identify small clearings.
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Wan, Liang, Yijian Li, Haiyan Cen, Jiangpeng Zhu, Wenxin Yin, Weikang Wu, Hongyan Zhu, Dawei Sun, Weijun Zhou, and Yong He. "Combining UAV-Based Vegetation Indices and Image Classification to Estimate Flower Number in Oilseed Rape." Remote Sensing 10, no. 9 (September 17, 2018): 1484. http://dx.doi.org/10.3390/rs10091484.
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Remote estimation of flower number in oilseed rape under different nitrogen (N) treatments is imperative in precision agriculture and field remote sensing, which can help to predict the yield of oilseed rape. In this study, an unmanned aerial vehicle (UAV) equipped with Red Green Blue (RGB) and multispectral cameras was used to acquire a series of field images at the flowering stage, and the flower number was manually counted as a reference. Images of the rape field were first classified using K-means method based on Commission Internationale de l’Éclairage (CIE) L*a*b* space, and the result showed that classified flower coverage area (FCA) possessed a high correlation with the flower number (r2 = 0.89). The relationships between ten commonly used vegetation indices (VIs) extracted from UAV-based RGB and multispectral images and the flower number were investigated, and the VIs of Normalized Green Red Difference Index (NGRDI), Red Green Ratio Index (RGRI) and Modified Green Red Vegetation Index (MGRVI) exhibited the highest correlation to the flower number with the absolute correlation coefficient (r) of 0.91. Random forest (RF) model was developed to predict the flower number, and a good performance was achieved with all UAV variables (r2 = 0.93 and RMSEP = 16.18), while the optimal subset regression (OSR) model was further proposed to simplify the RF model, and a better result with r2 = 0.95 and RMSEP = 14.13 was obtained with the variable combination of RGRI, normalized difference spectral index (NDSI (944, 758)) and FCA. Our findings suggest that combining VIs and image classification from UAV-based RGB and multispectral images possesses the potential of estimating flower number in oilseed rape.
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Dini, Irene, Giulia Graziani, Francalisa Luisa Fedele, Andrea Sicari, Francesco Vinale, Luigi Castaldo, and Alberto Ritieni. "An Environmentally Friendly Practice Used in Olive Cultivation Capable of Increasing Commercial Interest in Waste Products from Oil Processing." Antioxidants 9, no. 6 (June 1, 2020): 466. http://dx.doi.org/10.3390/antiox9060466.
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In the Rural Development Plan (2014–2020), the European Commission encouraged the conversion and supported the maintenance of organic farming. Organic olive oil (bioEVOO) production involves the use of environmentally sustainable fertilizers and the recycling of olive pomace (Pom) and olive vegetation waters (VW) to reduce the environmental impact of these wastes. An ecofriendly way to recycle olive wastes is to reuse them to extract bioactive compounds. In this study, the total phenolic compounds content, their profile and dosage, the antioxidant action in oil, pomace, and vegetation water was evaluated when the Trichoderma harzianum M10 was used as a biostimulant in agriculture. Two spectrophotometric tests (2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azinobis (3-ethylbenzothiazoline-6-sulfonic) acid (ABTS)) evaluated the antioxidant potential of samples, a spectrophotometric method estimated total phenolic content, and an Ultra-High-Performance Liquid Chromatography (UHPLC)–Orbitrap method evaluated the phenolics profile. Our results showed that the biostimulation improved the antioxidant potential and the total concentration of phenolics in the bioEVOO and bio-pomace (bioPom) samples and mainly enhanced, among all classes of phenolic compounds, the production of the flavonoids and the secoiridoids. Moreover, they demonstrated the Trichoderma action in the mevalonate pathway to produce phenols for the first time. The decisive action of the Thricoderma on the production of phenolic compounds increases the economic value of the waste materials as a source of bioactive compounds useful for the pharmaceutical, cosmetic, and food industries.
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Adamska, Maryna. "Riparian buffer zones on selected rivers in Lower Silesia – an important conservation practice and the management strategy in urban planning." Contemporary Trends in Geoscience 2, no. 1 (September 1, 2013): 6–17. http://dx.doi.org/10.2478/ctg-2014-0001.
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Abstract Buffer zones are narrow strips of land lying along the surface water, covered with appropriately selected vegetation. They separate aquatic ecosystems from the direct impact of agricultural land and reduce the movement of nutrients in the environment. In 2008 the European Commission established requirements for the implementation of buffer strips along water courses. Poland committed to the enforcement of these requirements until 1 January 2012. This was one of the reasons of this study. The subject of the analysis included the following rivers in Lower Silesia: Smortawa, Krynka, Czarna Woda and the selected transects of Ślęza and Nysa Łużycka. Detailed studies were designed to estimate the buffer zones occurring on these watercourses and assess these zones’ structure. This will be used to develop clear criteria for the selection of the width of these zones based on land use land management. It can be used in the implementation of executive acts at different levels of space management. Field research consisted of inventory the extent of riparian buffer strips on selected water courses and photographic documentation. Species composition of the vegetation forming a buffer zone was identified by using Braun-Blanquet method. There was lack of continuity of the riparian buffer zones on investigated rivers. Buffer zones should have carefully formulated definition and width because they are element of the significant ecological value, they perform important environmental protective functions and they are also the subject of Community law.
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Fu, Yuyun, Rui Li, Xuewen Wang, Yves Bergeron, Osvaldo Valeria, Raphaël D. Chavardès, Yipu Wang, and Jiheng Hu. "Fire Detection and Fire Radiative Power in Forests and Low-Biomass Lands in Northeast Asia: MODIS versus VIIRS Fire Products." Remote Sensing 12, no. 18 (September 4, 2020): 2870. http://dx.doi.org/10.3390/rs12182870.
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Fire omission and commission errors, and the accuracy of fire radiative power (FRP) from satellite moderate-resolution impede the studies on fire regimes and FRP-based fire emissions estimation. In this study, we compared the accuracy between the extensively used 1-km fire product of MYD14 from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the 375-m fire product of VNP14IMG from the Visible Infrared Imaging Radiometer Suite (VIIRS) in Northeastern Asia using data from 2012–2017. We extracted almost simultaneous observation of fire detection and FRP from MODIS-VIIRS overlapping orbits from the two fire products, and identified and removed duplicate fire detections and corresponding FRP in each fire product. We then compared the performance of the two products between forests and low-biomass lands (croplands, grasslands, and herbaceous vegetation). Among fire pixels detected by VIIRS, 65% and 83% were missed by MODIS in forests and low-biomass lands, respectively; whereas associated omission rates by VIIRS for MODIS fire pixels were 35% and 53%, respectively. Commission errors of the two fire products, based on the annual mean measurements of burned area by Landsat, decreased with increasing FRP per fire pixel, and were higher in low-biomass lands than those in forests. Monthly total FRP from MODIS was considerably lower than that from VIIRS due to more fire omission by MODIS, particularly in low-biomass lands. However, for fires concurrently detected by both sensors, total FRP was lower with VIIRS than with MODIS. This study contributes to a better understanding of fire detection and FRP retrieval performance between MODIS and its successor VIIRS, providing valuable information for using those data in the study of fire regimes and FRP-based fire emission estimation.
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Plugatar, Yu V., N. B. Ermakov, P. V. Krestov, N. V. Matveyeva, V. B. Martynenko, V. B. Golub, V. Yu Neshataeva, et al. "The concept of vegetation classification of Russia as an image of contemporary tasks of phytocoenology." Vegetation of Russia, no. 38 (July 2020): 3–12. http://dx.doi.org/10.31111/vegrus/2020.38.3.
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The scientific discussion concerning the development of the promising approaches for phyto-diversity conservation and the rational use of plant resources in Russian Federation was held at the Presidium of the Russian Academy of Sciences in December 2019. After the reports of leading scientists from biological institutes, a resolution No. 195 dated December 10, 2019 «Global changes in terrestrial ecosystems of Russia in the 21st century: challenges and opportunities» was adopted. The resolution includes a set of priority scientific aims including the development and application of modern technologies for inventory of the plant communities and the development of vegetation classification in Russia. As a result of the opinion exchange between phytocoenologists from different regions, the Concept of Russian Vegetation Classification was proposed. It is based on the following principles. 1. The use of the ecological-floristic approach and the hierarchy of the main syntaxonomic categories applied for the Classification of Vegetation of Europe. 2. Development of the Russian archive of geobotanical relevés and syntaxa in accordance with international standards and with the remote access functions. 3. Application of strict rules for syntaxon names formulated in the International Code of Phytosociological Nomenclature. The Concept assumes the development of a special program «Russian Vegetation Classification» with the justification of the necessity for targeted funding of the program in Research Institutions and Universities involved for solving this scientific problem on the principle of network collaboration. The final results of this program will be represented in the multi-volume publication «Vegetation of Russia». A shortened version of the Concept (English version was kindly revised by Dr. Andrew Gillison, Center for Biodiversity Management, Cairns, Queensand, Australia) is below. Vegetation classification of Russia Research Program Concept Systematic classification and inventory of plant communities (phytocoenoses) is fundamental to the study and forecasting of contemporary complex processes in the biosphere, controlled among other factors, by global climate change. Vegetation classification serves as a common language that enables professionals in various fields of science to communicate and interact with each other in the process of studying and formulating practical ecosystem-related management decisions. Because plant community types can carry a great deal of information about the environment, nearly all approaches to simulation of changes in global biota are based inevitably on vegetation categories. Phytocoenosis is a keystone element when assessing the biodiversity genetic potential, formulating decisions in biological resource management and in sustaining development across Russian territories. Among the world’s vegetation classification systems, phytosociology is a system in which the concept of plant association (basic syntaxon) is the basic element in the classification of phytocoenoses. The phytosociological approach as applied in this concept proposal, has its origins in the Brussels Botanical Congress in 1910. However, despite the broad acceptance of phytocoenotic diversity as a fundamental methodological tool for understanding biosphere processes and managing biological resources nowadays, we still lack a unified approach as to its systematization at both global and country levels with the consequence that, there is no a single classification system. The results obtained by vegetation scientists working under European Vegetation Survey led by L. Mucina became the effective reference for international cooperation in vegetation classification. In the last 17 years they have produced a system of vegetation classification of Europe, including the European part of Russia (Mucina et al., 2016. «Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities»). Despite the fact that «Vegetation of Europe» is based on ecological and floristic principles, it nevertheless represents an example of the synthesis of one of the most effective approaches to systematizing vegetation diversity by different vegetation science schools. The synthetic approach implemented in this study assumes full accounting of the ecological indicative significance of the floristic composition and structure of plant community and habitat attributes. The approach has already demonstrated its high efficiency for understanding and forecast modeling both natural and anthropogenic processes in the biosphere, as well as in assessment of the environmental and resource significance of vegetation (ref). The demand for this approach is supported by its implementation in a number of pan-European and national projects: NATURE 2000, CORINE, CarHAB, funded at the state and pan-European levels. Currently, one of the main systems for the study and protection of habitats within the framework of environmental programs of the European Union (Davies, Moss, 1999; Rodwell et al., 2002; Moss, 2008; Linking..., 2015; Evans et al., 2018) is EUNIS (European Nature Information System), the framework of which is a multilevel classification of habitats in Europe has been established. EUNIS was used as the basis for the preparation and establishment of the Red List of European Habitats (Rodwell et al., 2013). It is approved by the Commission of the European Union (EU) (Habitats Directive 92/43 / EEC, Commission of the European Communities) for use in environmental activities of EU countries. In its Resolution of 10.12.2019, the Presidium of the Russian Academy of Sciences (RAS) expressed the need in a modern vegetation classification for the assessment of the ecosystem transformations under current climate changes and increasing anthropogenic impacts, as well as in development of effective measures for the conservation and rational use of plant resources of Russia. The resolution recommended the development of the Concept of Vegetation Classification of Russia to the Science Council for biodiversity and biological resources (at RAS Department of biological sciences — Section of Botany). As a consequence, a group of Russian vegetation researchers has developed the Concept for Vegetation Classification of Russia and proposed principles and a plan for its implementation. Aim Elaboration of a system of vegetation classification of Russia reflecting the natural patterns of plant communities formation at different spatial and geographical levels and serving as the fundamental basis for predicting biosphere processes, science-based management of bioresources, conservation of biodiversity and, ultimately, rational nature management for planning sustainable development of its territories. Research goals 1. Development of fundamental principles for the classification of vegetation by synthesis of the achievements of Russian and world’s vegetation science. 2. Inventory of plant community diversity in Russia and their systematization at different hierarchical levels. Elaboration and publication of a Prodromus of vegetation of Russia (syntaxon checklist) with an assessment of the correctness of syntaxa, their Nomenclatural validization and bibliography. Preparation and publication of a book series «Vegetation of Russia» with the entire classification system and comprehensive description of all syntaxonomic units. 3. The study of bioclimatic patterns of the phytocoenotic diversity in Russia for predictive modeling of biosphere processes. Assessment of qualitative changes in plant cover under global climate change and increasing anthropogenic impact in its various forms. 4. Assessment of the conservation value of plant communities and ecosystems. Habitat classification within Russia on the basis of the vegetation classification with a reference to world experience. 5. Demonstration of the opportunities of the vegetation classification for the assessment of actual plant resources, their future prognoses under climate and resource use change, optimization of nature management, environmental engineering and planning of projects for sustainable development. Basic principles underlying the vegetation classification of Russia I. Here we address the synthesis of accumulated theoretical ideas about the patterns of vegetation diversity and the significant features of phytocoenoses. The main goal is to identify the most significant attributes of the plant cover at different hierarchical levels of classification: floristic, structural-phytocoenotic, ecotopic and geographical.We propose the following hierarchy of the main syntaxonomical categories used in the classification of European vegetation (Mucina et al., 2016) by the ecological-floristic approach (Braun-Blanquet): Type of vegetation, Class, Order, Alliance, Association. Applying the ecological-floristic approach to the vegetation classification of Russia will maximize the use of the indicative potential of the plant community species composition to help solve the complex tasks of modern ecology, notably plant resource management, biodiversity conservation, and the forecast of vegetation response to environmental change of environment changes. II. We plan to establish an all-Russian archive of geobotanical relevés in accordance with international standards and reference information system on the syntaxonomical diversity coupled with implemented remote access capabilities. At present, the archives in botanical, biological, environmental and geographical institutes of the Russian Academy of Sciences, as well as those of universities, have accumulated a large mass of geobotanical relevés for most regions of Russia (according to preliminary estimates — more than 300,000). These documents, which are fundamental to solving the most important national tasks for the conservation and monitoring of the natural human environment, need to be declared a National treasure. In this respect, the development of the all-Russian Internet portal for the vegetation classification is an urgent priority. III. The vegetation classification procedure will be based on a generalization of field data (geobotanical relevés) performed in accordance with international standards, using up-to-date mathematical and statistical methods and information technology. IV. The vegetation classification of Russia will be based on strict rules for naming of syntaxa, according to their validity as formulated in the International Code of Phytosociological Nomenclature, which is constantly being improved (Weber et al., 2020). These underlying principles will help develop the ecological indicative potential of a wide range of vegetation features that can be used to focus on solving a range of global and regional ecology problems, plant resources management, biodiversity protection, and forecasting of the consequences of environmental changes. Prospects for the implementation of the concept «Vegetation classification of Russia» At present, the academic research centers and universities of Moscow, St. Petersburg, Novosibirsk, Vladivostok, Irkutsk, Murmansk, Crimea, Bashkiria, Komi and other regions have sufficient scientific potential to achieve the goals in the framework of the special Program of the Russian Academy of Sciences — that is, to develop a vegetation classification of Russia. To achieve this goal will require: - organization of a network of leading teams within the framework of the Scientific Program of the Russian Academy of Sciences «Vegetation classification of Russia», adjustment of the content of state assignment with the allocation of additional funding. - approval of the thematic Program Committee by the RAS for the development of organizational approaches and elaboration of specific plans for the realization of the Scientific Program, - implementation of the zonal-geographical principle in organization of activity on developing the regional classifications and integrating them into a single classification system of the vegetation of Russia. - ensuring the integration of the system of vegetation classification of Russia with similar systems in the countries of the former USSR, Europe, USA, China, Japan, etc. Potential organizations-participants in the scientific Program — 18 institutes of the Russian Academy of Sciences and 8 Universities. Estimated timelines of the implementation of the concept «Vegetation classification of Russia» — 2021–2030. General schedule for the entire period of research 2021. Approval of classification principles, unified methodical and methodological approaches by project participants. Discussion and elaboration of the rules of organization of the all-Russian archive of geobotanical relevés and syntaxa. 2022–2026. Formation of all-Russian archive of geobotanical relevés and syntaxa. Development of plant community classification and identification of the potential indicative features of units of different ranks based on quantitative methods and comparative syntaxonomic analysis with existing classification systems in Europe, North and East Asia. Justification of new concepts for key syntaxa. The study of environmental and geographical patterns of the vegetation diversity in Russia using up-to-date methods of ordination modeling and botany-geography analysis. 2022. Publication of a Prodromus of vegetation classification of Russia. Schedule for the publication of volumes of the «Vegetation classification of Russia» 2023. «Boreal forests and pre-tundra woodlands» 2024. «Forests of the temperate zone» 2025. «Tundra and polar deserts» and «Alpine vegetation» 2026. «Steppe vegetation» and «Meadow vegetation» 2027. «Aquatic and bog vegetation» 2028. «Halophytic vegetation» 2029. «Synanthropic vegetation» 2027–2030. Development of criteria for assessing the environmental significance of the plant community syntaxonomic categories for various natural zones based on world criteria. Preparation of the volume «Classification of habitats of Russia and assessment of their environmental significance».
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Tien, Doan Phan Thao, Le Hong Khiem, Trinh Thi Thu Trinh, Marina Vladimir Frontasyeva, Nguyen Thi Minh Sang, and Son An Nguyen. "Comparing atmospheric trace element accumulation of three moss species." Science and Technology Development Journal 23, no. 4 (November 8, 2020): 752–57. http://dx.doi.org/10.32508/stdj.v23i4.2417.
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Introduction: The intention of Vietnam to participate in the European-Asian Moss Survey in the framework of The United Nations Economic Commission for Europe - International Cooperative Programme on effects of air pollution on natural vegetation and crops (UNECE ICP Vegetation) necessitates choosing appropriate moss species that grow in the tropical and subtropical climate of Vietnam. The three selected moss species, divided into phytogeographical elements, were as follows: Leucobryum (aduncum, albidum), Hypnum commutatum and Barbula indica.
Methods: The present study focuses on Central Vietnam where 18 samples of the three above moss species were collected in the vicinity of Dalat and Hue cities. Elements in the moss samples were detected by neutron activation analysis (NAA) at the IBR-2 reactor of the Division of Neutron Activation Analysis, Frank Laboratory of Neutron Physics, Joint Institute for Nuclear Research in Dubna, Russia.
Results: The analytical results for twenty-three trace elements, which were used to study elemental accumulation abilities of the three moss species in the air, were Na, Mg, Al, Cl, K, Ca, Ti, V, Mn, Fe, Co, Zn, As, Br, Rb, Sr, Sb, I, Cs, Ba, La, Th, and U. The accumulation abilities were found to decrease in the following order: Leucobryum > Hypnum > Barbula. However, Leucobryum, because of its short stem, was not judged to be a suitable candidate for biomonitoring.
Conclusion: The element accumulation abilities of Hypnum moss were better than those for Barbula, but both were comparable and could be used as indicators for air deposition monitoring; however, Hypnum was not widely present in Vietnam. Thus, Barbula indica moss could be used for performance of atmospheric deposition monitoring in Vietnam.
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Ascenso, Ana, Carla Gama, Carlos Silveira, Carolina Viceto, Alfredo Rocha, Myriam Lopes, and Ana Isabel Miranda. "Ozone Effects on Douro Vineyards under Climate Change." Atmosphere 12, no. 10 (September 22, 2021): 1238. http://dx.doi.org/10.3390/atmos12101238.
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Tropospheric ozone (O3) levels in southern Europe have an increasing tendency, in close relation with the higher incidence of hot summers and heatwaves. Given that O3 is one of the most damaging pollutants for vegetation, known to affect productivity and quality of crops, it is necessary to develop more rigorous and consistent methods of risk assessment that consider climate change conditions. Studying the O3 deposition over the Douro Demarcated Region (DDR), which is one of the most productive wine areas in Portugal, and assessing its potential effects under a climate change scenario, was the purpose of this study. To that end, the chemical transport model CHIMERE, with a spatial resolution of 1 km2, fed by meteorological data from the WRF model, was applied for a recent past climate (2003 to 2005) and future mid-term (2049 and 2064) and long-term (2096 and 2097) scenarios. Simulations for future climate were performed considering: (i) only the climate change effect, and (ii) the effect of climate change together with future air pollutant emissions. The assessment of the potential damage in terms of wine productivity and quality (sugar content) was performed through analysis of O3 deposition and the application of concentration–response functions, based on AOT40 values. Modeling results show that a reduction in emission of O3 precursors can successfully decrease AOT40 levels in the DDR, but it is not enough to accomplish the European Commission target value for the protection of vegetation. If the emissions remain constant, the exposure–response functions indicate that, in the long-term, AOT40 levels could worsen wine productivity and quality.
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Brieger, Frederic, Ulrike Herzschuh, Luidmila A. Pestryakova, Bodo Bookhagen, Evgenii S. Zakharov, and Stefan Kruse. "Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds." Remote Sensing 11, no. 12 (June 18, 2019): 1447. http://dx.doi.org/10.3390/rs11121447.
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Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
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Vickers, Lance, James Houser, James Rooni, and James Guldin. "Some Lessons Learned on Early Survival and Growth of Containerized, Locally-Sourced Ponderosa Pine Seedlings in the Davis Mountains of Western Texas, US." Forests 10, no. 3 (March 16, 2019): 267. http://dx.doi.org/10.3390/f10030267.
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The ponderosa pine forests in the Davis Mountains of western Texas recently experienced a major mortality event caused, in part, by an extended regional drought that predisposed trees and stands to mortality from both western pine beetle and wildfires. The loss of many overstory pines and the scarcity of natural ponderosa pine regeneration pose a considerable challenge to restoration. A commissioned study investigated artificial regeneration using containerized ponderosa pine seedlings with multiple planting seasons and vegetation management alternatives. Early survival was statistically greater for dormant season plantings than monsoon season plantings. Vegetation management treatments influenced early growth, survival, and herbivory rates. Physical weed control, which consisted of fibrous weed mats around the base of planted seedlings, showed early advantages over some vegetation management treatments in growth, survival and herbivory deterrence, but all vegetation management treatments had similar survival and herbivory results after 2.5 years. Early survival was poor in all treatments, mainly due to herbivory, which was identified as the principal short-term obstacle to artificial regeneration of ponderosa pine in the Davis Mountains. The larger question regarding feasibility of recovery in this isolated population, particularly if local climatic conditions become increasingly unfavorable, remains.
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Cross, Matthew, Ted Scambos, Fabio Pacifici, Orlando Vargas-Ramirez, Rafael Moreno-Sanchez, and Wesley Marshall. "Classification of Tropical Forest Tree Species Using Meter-Scale Image Data." Remote Sensing 11, no. 12 (June 14, 2019): 1411. http://dx.doi.org/10.3390/rs11121411.
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Accurate classification of tropical tree species is critical for understanding forest habitat, biodiversity, forest composition, biomass, and the role of trees in climate variability through carbon uptake. The aim of this study is to establish an accurate classification procedure for tropical tree species, specifically testing the feasibility of WorldView-3 (WV-3) multispectral imagery for this task. The specific study site is a defined arboretum within a well-known tropical forest research location in Costa Rica (La Selva Biological Station). An object-based classification is the basis for the analysis to classify six selected tree species. A combination of pre-processed WV-3 bands were inputs to the classification, and an edge segmentation process defined multi-pixel-scale tree canopies. WorldView-3 bands in the Green, Red, Red Edge, and Near-Infrared 2, particularly when incorporated in two specialized vegetation indices, provide high discrimination among the selected species. Classification results yield an accuracy of 85.37%, with minimal errors of commission (7.89%) and omission (14.63%). Shadowing in the satellite imagery had a significant effect on segmentation accuracy (identifying single-species canopy tops) and on classification. The methodology presented provides a path to better characterization of tropical forest species distribution and overall composition for improving biomass studies in a tropical environment.
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Eliseeva, Lyudmila Valerievna, Olga Petrovna Nesterova, and Maria Vasilievna Prokopyeva. "The study of methods of sowing of beans varieties in the conditions of the Chuvash Republic." Agrarian Scientific Journal, no. 8 (August 25, 2019): 12–16. http://dx.doi.org/10.28983/asj.y2019i8pp12-16.
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The results of studying the methods of sowing varieties of beans in the conditions of the Chuvash Republic are given. Studies were conducted in 2017–2018. in the University "Student" Chuvash State Agricultural Academy. Objects of research - varieties of beans Ballada, Chocolate, Dream hostess. The studies used the methods of the State Commission for varietal testing and statistical processing of the results according to the method of Dospekhov. Field germination in all varieties turned out to be higher when sown with 15 cm row spacing, and the safety of plants for harvesting when sowing with 30 cm row spacing. The vegetation period averaged 102-112 days. In all varieties, the ordinary method allowed to start cleaning 3-4 days earlier. In all varieties, the ordinary method allowed to start cleaning 3-4 days earlier. In the wet year of 2017, bean plants with all sowing methods were higher, but less productive beans were formed on the plants. Sowing methods have had an ambiguous impact on the elements of the crop structure. Thus, in the Ballada and Mistress’s dream varieties, the size of the seeds increases with wide-row sowing, and in the Chocoladnitsa and Mistress’s Dream varieties the number of beans per plant. In 2017, the mistress’s dream variety turned out to be the most productive, while the wide-row sowing reliably exceeded the average by 0.45 t / ha. In 2018, the sowing variant of the ordinary (15 cm) method proved more effective in all varieties. The maximum yield was recorded for the Variety Chocolate variety in 2018 when sowing with 15 cm row spacing - 6.87 t / ha. The results indicate that in the conditions of the Chuvash Republic beans are able to mature and form consistently high yields.
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De Swaef, Tom, Wouter H. Maes, Jonas Aper, Joost Baert, Mathias Cougnon, Dirk Reheul, Kathy Steppe, Isabel Roldán-Ruiz, and Peter Lootens. "Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses." Remote Sensing 13, no. 1 (January 5, 2021): 147. http://dx.doi.org/10.3390/rs13010147.
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The persistence and productivity of forage grasses, important sources for feed production, are threatened by climate change-induced drought. Breeding programs are in search of new drought tolerant forage grass varieties, but those programs still rely on time-consuming and less consistent visual scoring by breeders. In this study, we evaluate whether Unmanned Aerial Vehicle (UAV) based remote sensing can complement or replace this visual breeder score. A field experiment was set up to test the drought tolerance of genotypes from three common forage types of two different species: Festuca arundinacea, diploid Lolium perenne and tetraploid Lolium perenne. Drought stress was imposed by using mobile rainout shelters. UAV flights with RGB and thermal sensors were conducted at five time points during the experiment. Visual-based indices from different colour spaces were selected that were closely correlated to the breeder score. Furthermore, several indices, in particular H and NDLab, from the HSV (Hue Saturation Value) and CIELab (Commission Internationale de l’éclairage) colour space, respectively, displayed a broad-sense heritability that was as high or higher than the visual breeder score, making these indices highly suited for high-throughput field phenotyping applications that can complement or even replace the breeder score. The thermal-based Crop Water Stress Index CWSI provided complementary information to visual-based indices, enabling the analysis of differences in ecophysiological mechanisms for coping with reduced water availability between species and ploidy levels. All species/types displayed variation in drought stress tolerance, which confirms that there is sufficient variation for selection within these groups of grasses. Our results confirmed the better drought tolerance potential of Festuca arundinacea, but also showed which Lolium perenne genotypes are more tolerant.
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Phinzi, Kwanele, Dávid Abriha, and Szilárd Szabó. "Classification Efficacy Using K-Fold Cross-Validation and Bootstrapping Resampling Techniques on the Example of Mapping Complex Gully Systems." Remote Sensing 13, no. 15 (July 28, 2021): 2980. http://dx.doi.org/10.3390/rs13152980.
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The availability of aerial and satellite imageries has greatly reduced the costs and time associated with gully mapping, especially in remote locations. Regardless, accurate identification of gullies from satellite images remains an open issue despite the amount of literature addressing this problem. The main objective of this work was to investigate the performance of support vector machines (SVM) and random forest (RF) algorithms in extracting gullies based on two resampling methods: bootstrapping and k-fold cross-validation (CV). In order to achieve this objective, we used PlanetScope data, acquired during the wet and dry seasons. Using the Normalized Difference Vegetation Index (NDVI) and multispectral bands, we also explored the potential of the PlanetScope image in discriminating gullies from the surrounding land cover. Results revealed that gullies had significantly different (p < 0.001) spectral profiles from any other land cover class regarding all bands of the PlanetScope image, both in the wet and dry seasons. However, NDVI was not efficient in gully discrimination. Based on the overall accuracies, RF’s performance was better with CV, particularly in the dry season, where its performance was up to 4% better than the SVM’s. Nevertheless, class level metrics (omission error: 11.8%; commission error: 19%) showed that SVM combined with CV was more successful in gully extraction in the wet season. On the contrary, RF combined with bootstrapping had relatively low omission (16.4%) and commission errors (10.4%), making it the most efficient algorithm in the dry season. The estimated gully area was 88 ± 14.4 ha in the dry season and 57.2 ± 18.8 ha in the wet season. Based on the standard error (8.2 ha), the wet season was more appropriate in gully identification than the dry season, which had a slightly higher standard error (8.6 ha). For the first time, this study sheds light on the influence of these resampling techniques on the accuracy of satellite-based gully mapping. More importantly, this study provides the basis for further investigations into the accuracy of such resampling techniques, especially when using different satellite images other than the PlanetScope data.
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Ashiev, A. R., and K. N. Khabibullin. "The study of correlation between productivity and morphobiological traits of the collection peas samples." Grain Economy of Russia, no. 3 (July 9, 2020): 3–7. http://dx.doi.org/10.31367/2079-8725-2020-69-3-3-7.
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The current paper has presented the study results of correlation between productivity and morphobiological traits of the collection peas samples. The study was carried out at the FSBSI “AgriculturalResearchCenter“Donskoy”, located in the southern part of theRostovregion. The purpose of the study was to analyze the correlation between the quantitative traits of collection peas samples and their productivity. The study of the pea collection was conducted in the collection nursery of pea in 2017–2019, in accordance with the IPI methodology for the study of legumes (1975), the methodology of the State Commission for Variety Testing of Agricultural Crops (2019) and the methodology of a fi trial (2012). The objects of the study were 100 samples of pea of domestic and foreign breeding taken from the world collection of VIGR named after N. I. Vavilov. The variety “Aksaysky Usaty5”was used as a standard variety. The forecrop was winter wheat. The sowing of the collection samples was carried out in the third decade of March with the SSFK-7 seeder, with a seeding rate of million germinating seeds per1 ha, with a row width of15 cm. The plots contained seven rows. The plot area was5 m2 with a single repetition. The registration plot was0.25 m2. There has been identifi that in 2017-2019 the average productivity ranged from 1.12 t/ha (“Omega”,Moldova) to 2.82 t/ha (“Kazanets”, Rossiya) with average 2.13 t/ha in the collection. The most productive samples were plants with a plant height of 45–55 cm, an average number of beans 2.7–3.3 pcs/plant, 1000 seed weight of 210–270 g, a vegetation period of 69–73 days, and seed weight per plant of 3.3–4.3 g, an average number of seeds 13–19 pcs/plant. The study results of correlation between productivity and morphobiological traits of the collection peas samples are going to be used as an initial material in further breeding work.
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Filipponi, Federico. "Exploitation of Sentinel-2 Time Series to Map Burned Areas at the National Level: A Case Study on the 2017 Italy Wildfires." Remote Sensing 11, no. 6 (March 14, 2019): 622. http://dx.doi.org/10.3390/rs11060622.
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Satellite data play a major role in supporting knowledge about fire severity by delivering rapid information to map fire-damaged areas in a precise and prompt way. The high availability of free medium-high spatial resolution optical satellite data, offered by the Copernicus Programme, has enabled the development of more detailed post-fire mapping. This research study deals with the exploitation of Sentinel-2 time series to map burned areas, taking advantages from the high revisit frequency and improved spatial and spectral resolution of the MSI optical sensor. A novel procedure is here presented to produce medium-high spatial resolution burned area mapping using dense Sentinel-2 time series with no a priori knowledge about wildfire occurrence or burned areas spatial distribution. The proposed methodology is founded on a threshold-based classification based on empirical observations that discovers wildfire fingerprints on vegetation cover by means of an abrupt change detection procedure. Effectiveness of the procedure in mapping medium-high spatial resolution burned areas at the national level was demonstrated for a case study on the 2017 Italy wildfires. Thematic maps generated under the Copernicus Emergency Management Service were used as reference products to assess the accuracy of the results. Multitemporal series of three different spectral indices, describing wildfire disturbance, were used to identify burned areas and compared to identify their performances in terms of spectral separability. Result showed a total burned area for the Italian country in the year 2017 of around 1400 km2, with the proposed methodology generating a commission error of around 25% and an omission error of around 40%. Results demonstrate how the proposed procedure allows for the medium-high resolution mapping of burned areas, offering a benchmark for the development of new operational downstreaming services at the national level based on Copernicus data for the systematic monitoring of wildfires.
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Liu, Jinglong, Yunjia Wang, Shiyong Yan, Feng Zhao, Yi Li, Libo Dang, Xixi Liu, Yaqin Shao, and Bin Peng. "Underground Coal Fire Detection and Monitoring Based on Landsat-8 and Sentinel-1 Data Sets in Miquan Fire Area, XinJiang." Remote Sensing 13, no. 6 (March 17, 2021): 1141. http://dx.doi.org/10.3390/rs13061141.
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Underground coal fires have become a worldwide disaster, which brings serious environmental pollution and massive energy waste. Xinjiang is one of the regions that is seriously affected by the underground coal fires. After years of extinguishing, the underground coal fire areas in Xinjiang have not been significantly reduced yet. To extinguish underground coal fires, it is critical to identify and monitor them. Recently, remote sensing technologies have been showing great potential in coal fires’ identification and monitoring. The thermal infrared technology is usually used to detect thermal anomalies in coal fire areas, and the Differential Synthetic Aperture Radar Interferometry (DInSAR) technology for the detection of coal fires related to ground subsidence. However, non-coal fire thermal anomalies caused by ground objects with low specific heat capacity, and surface subsidence caused by mining and crustal activities have seriously affected the detection accuracy of coal fire areas. To improve coal fires’ detection accuracy by using remote sensing technologies, this study firstly obtains temperature, normalized difference vegetation index (NDVI), and subsidence information based on Landsat8 and Sentinel-1 data, respectively. Then, a multi-source information strength and weakness constraint method (SWCM) is proposed for coal fire identification and analysis. The results show that the proposed SWCM has the highest coal fire identification accuracy among the employed methods. Moreover, it can significantly reduce the commission and omission error caused by non-coal fire-related thermal anomalies and subsidence. Specifically, the commission error is reduced by 70.4% on average, and the omission error is reduced by 30.6%. Based on the results, the spatio-temporal change characteristics of the coal fire areas have been obtained. In addition, it is found that there is a significant negative correlation between the time-series temperature and the subsidence rate of the coal fire areas (R2 reaches 0.82), which indicates the feasibility of using both temperature and subsidence to identify and monitor underground coal fires.
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Zanni, Sara, and Alessandro De Rosa. "Remote Sensing Analyses on Sentinel-2 Images: Looking for Roman Roads in Srem Region (Serbia)." Geosciences 9, no. 1 (January 5, 2019): 25. http://dx.doi.org/10.3390/geosciences9010025.
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The present research is part of the project “From Aquileia to Singidunum: reconstructing the paths of the Roman travelers—RecRoad”, developed at the Université Bordeaux Montaigne, thanks to a Marie Skłodowska-Curie fellowship. One of the goals of the project was to detect and reconstruct the Roman viability between the Roman cities of Aquileia (Aquileia, Italy) and Singidunum (Belgrade, Serbia), using different sources and methods, one of which is satellite remote sensing. The research project analyzed and combined several data, including images produced by the Sentinel-2 mission, funded by the European Commission Earth Observation Programme Copernicus, in which satellites were launched between 2015 and 2017. These images are freely available for scientific and commercial purposes, and constitute a constantly updated gallery of the whole planet, with a revisit time of five days at the Equator. The technical specifications of the satellites’ sensors are particularly suitable for archaeological mapping purposes, and their capacities in this field still need to be fully explored. The project provided a useful testbed for the use of Sentinel-2 images in the archaeological field. The study compares traditional Vegetation Indices with experimental trials on Sentinel images applied to the Srem District in Serbia. The paper also compares the results obtained from the analysis of the Sentinel-2 images with WorldView-2 multispectral images. The obtained results were verified through an archaeological surface survey.
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Sultan, Vivian, and Brian Hilton. "How May Location Analytics Be Used to Enhance the Reliability of the Smart Grid?" Inventions 4, no. 3 (August 2, 2019): 39. http://dx.doi.org/10.3390/inventions4030039.
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The United States (U.S.) electric infrastructure urgently needs renovation, as highlighted by recent major outages in California, New York, Texas, and Florida. The media has discussed the aging power infrastructure, and the Public Utilities Commission called for a comprehensive review of the causes of recent power outages. Without optimization algorithms to account for the many operating parameters and outage scenarios, planning engineers may inadvertently choose non-optimal locations for new components such as automated distribution switches, thereby impacting circuit reliability. This study aims to address this problem by answering the research question: “How may location analytics should be used to enhance the reliability of the smart grid?” To address this problem, Insights for ArcGIS was used to build worksheets using a geographic information systems (GIS)-based approach to resolve the challenges faced by utilities to reduce power outage frequency. Three case studies demonstrate various risk scenarios wherein a utility can prepare for the unexpected. An artefact in Insights for ArcGIS was created using a design science research methodology. This research proposes a solution to facilitate storm/disaster planning and vegetation management, identify optimal grid locations needing inspection or work, and detect regions where new distribution switches may provide benefits, considering the many operating parameters and outage scenarios. The artefact demonstrates that GIS can play an integral role in resolving this problem.
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Rai, Mana Raj, Amnat Chidthaisong, Chaiwat Ekkawatpanit, and Pariwate Varnakovida. "Assessing Climate Change Trends and Their Relationships with Alpine Vegetation and Surface Water Dynamics in the Everest Region, Nepal." Atmosphere 12, no. 8 (July 31, 2021): 987. http://dx.doi.org/10.3390/atmos12080987.
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The Himalayas, especially the Everest region, are highly sensitive to climate change. Although there are research works on this region related to cryospheric work, the ecological understandings of the alpine zone and climate impacts are limited. This study aimed to assess the changes in surface water including glacier lake and streamflow and the spatial and temporal changes in alpine vegetation and examine their relationships with climatic factors (temperature and precipitation) during 1995–2019 in the Everest region and the Dudh Koshi river basin. In this study, Landsat time-series data, European Commission’s Joint Research Center (JRC) surface water data, ECMWF Reanalysis 5th Generation (ERA5) reanalysis temperature data, and meteorological station data were used. It was found that the glacial lake area and volume are expanding at the rates of 0.0676 and 0.0198 km3/year, respectively; the average annual streamflow is decreasing at the rate of 2.73 m3/s/year. Similarly, the alpine vegetation greening as indicated by normalized difference vegetation index (NDVI) is increasing at the rate of 0.00352 units/year. On the other hand, the annual mean temperature shows an increasing trend of 0.0329 °C/year, and the annual precipitation also shows a significant negative monotonic trend. It was also found that annual NDVI is significantly correlated with annual temperature. Likewise, the glacial lake area expansion is strongly correlated with annual minimum temperature and annual precipitation. Overall, we found a significant alteration in the alpine ecosystem of the Everest region that could impact on the water–energy–food nexus of the Dudh Koshi river basin.
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Szczygieł, Ryszard, Mirosław Kwiatkowski, and Bartłomiej Kołakowski. "The attempt to assess the fire risk of non-forest terrestrial ecosystems of Biebrza National Park – A case study." Folia Forestalia Polonica 63, no. 2 (June 1, 2021): 167–75. http://dx.doi.org/10.2478/ffp-2021-0017.
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Abstract On 19th April, the largest wildfire of the entire history of Biebrza National Park broke out and consumed 5526 ha, mostly overdried grassland with sedges and reeds of Biebrza marshes. The very rapid spread of the fire in the open space, with the blowing wind changing directions and the inaccessibility of the area for fire-fighting vehicles were the main reasons of this third largest wildfire in Poland, after the tragic forest fires in Kuźnia Raciborska (9060 ha burnt) and Potrzebowice (5600 ha burnt) in the memorable year of 1992. After this event, activities were undertaken to develop a fire protection plan for the Biebrza National Park. It took into account an innovative approach during the analysis of the existing fire risk, primarily regarding the non-forest terrestrial ecosystems composed of herbaceous vegetation, which constitutes as much as 61.2% of the park’s area, and to propose protection methods adequate to the threat. The work was completed in the framework of the project entitled ‘Development of the method for assessing the fire risk of non-forest ecosystems and the principles of fire protection for the Biebrza National Park – stage I,’ commissioned for the Forest Research Institute by the Biebrza National Park, financed by the State Forests from the forest fund, in accordance with the contract EZ.0290.1.24.2020. The article presents a preliminary method of classifying the fire risk of non-forest ecosystems, considering the occurrence of the fires in the Biebrza National Park in the years 2007–2020 and the type of vegetation burnt. This method, after supplementary field tests planned in 2021, will enable evaluation of the fire risk, which shall be a premise for the development of a fire protection plan.
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Hu, B., J. Li, J. Wang, and B. Hall. "The Early Detection of the Emerald Ash Borer (EAB) Using Advanced Geospacial Technologies." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2 (November 11, 2014): 213–19. http://dx.doi.org/10.5194/isprsarchives-xl-2-213-2014.
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The objectives of this study were to exploit Light Detection And Ranging (LiDAR) and very high spatial resolution (VHR) data and their synergy with hyperspectral imagery in the early detection of the EAB presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, individual trees were first extracted and then classified into different species based on their spectral information derived from hyperspectral imagery, spatial information from VHR imagery, and for each ash tree its health state and EAB infestation stage were determined based on hyperspectral imagery. The developed framework and methods were demonstrated to be effective according to the results obtained on two study sites in the city of Toronto, Ontario Canada. The individual tree delineation method provided satisfactory results with an overall accuracy of 78 % and 19 % commission and 23 % omission errors when used on the combined very high-spatial resolution imagery and LiDAR data. In terms of the identification of ash trees, given sufficient representative training data, our classification model was able to predict tree species with above 75 % overall accuracy, and mis-classification occurred mainly between ash and maple trees. The hypothesis that a strong correlation exists between general tree stress and EAB infestation was confirmed. Vegetation indices sensitive to leaf chlorophyll content derived from hyperspectral imagery can be used to predict the EAB infestation levels for each ash tree.
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Hill, David A., Raj Prasad, and Donald G. Leckie. "Mapping of Scotch Broom (Cytisus scoparius) with Landsat Imagery." Weed Technology 30, no. 2 (June 2016): 539–58. http://dx.doi.org/10.1614/wt-d-15-00038.1.
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Methods were developed and tested for mapping the distribution of Scotch broom, an invasive shrub species expanding its range and disrupting native species and habitats in several parts of the world. During spring, the Scotch broom produces yellow flowers. Landsat imagery during the flower bloom period and during summer was acquired for several years for a study area on Vancouver Island, British Columbia, Canada. Ground-based reflectance measurements plus statistical separability tests were conducted to determine the effectiveness for identifying Scotch broom with Landsat spectral bands, band ratios, vegetation indices, and combinations of bloom and nonbloom imagery. Maximum likelihood classifications of three Scotch broom density classes (dense, ≥ 75% cover; moderate, 25 to 75%; low, 10 to 25%) and other land covers were run with various image and band sets and tested against independent reference sites. Accuracies of classifications using the better band combinations for moderate and dense Scotch broom patches combined were on the order of 80%, with unreliable results for sites of low Scotch broom density. Scotch broom patches less than 0.5 ha were often missed. Some commission error occurred (areas erroneously classified as Scotch broom). Suggested improvements are the use of time series of classifications over multiple years, incorporating knowledge of Scotch broom spread mechanisms or temperature and elevation limitations, and use of higher resolution satellites if the expense warrants it. Despite some limitations, a satellite-based remote sensing approach may be useful for aspects of Scotch broom management.
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Chu, Thuan, Xulin Guo, and Kazuo Takeda. "Temporal dependence of burn severity assessment in Siberian larch (Larix sibirica) forest of northern Mongolia using remotely sensed data." International Journal of Wildland Fire 25, no. 6 (2016): 685. http://dx.doi.org/10.1071/wf15182.
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Assessing burn severity is critical for understanding both the short- and long-term effects of fire disturbance on forest ecosystems. This study proposed a methodology to reconstruct burn severity from the Landsat imagery at different time lags after a fire (≤18 years) in Siberian larch (Larix sibirica) forest. The estimated accuracy of the burn severity models we developed indicated strong effects of forest recovery, image acquisition date and remote sensing predictors on the burn severity assessment. In the first several years after the fire, the dNBR (differenced Normalized Burn Ratio) was the most important remotely sensed index for assessing burn severity, followed by the dNDMI (differenced Normalized Difference Moisture Index) and dNDVI (differenced Normalized Difference Vegetation Index). However, the dNDMI was more important than the dNBR and dNDVI in explaining burn severity when larch forest regrowth dominated. The overall accuracy of the classification and regression tree models showed a decrease in accuracy from 83% to 62% depending on the lag times of burn severity assessment. The high severity class had the lowest omission and commission errors, followed by the low and moderate classes among lag times. Our evaluation of model transferability and thresholds of burn severity index demonstrates the advantage of the proposed methodology for rapid assessment of fire effects in boreal larch forest that will assist in understanding the complex relationships among forest fires and ecological processes in Eurasian boreal ecosystems.
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Luti, Tania, Paolo De Fioravante, Ines Marinosci, Andrea Strollo, Nicola Riitano, Valentina Falanga, Lorella Mariani, Luca Congedo, and Michele Munafò. "Land Consumption Monitoring with SAR Data and Multispectral Indices." Remote Sensing 13, no. 8 (April 19, 2021): 1586. http://dx.doi.org/10.3390/rs13081586.
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Land consumption is the increase in artificial land cover, which is a major issue for environmental sustainability. In Italy, the Italian Institute for Environmental Protection and Research (ISPRA) and National System for Environmental Protection (SNPA) have the institutional duty to monitor land consumption yearly, through the photointerpretation of high-resolution images. This study intends to develop a methodology in order to produce maps of land consumption, by the use of the semi-automatic classification of multitemporal images, to reduce the effort of photointerpretation in detecting real changes. The developed methodology uses vegetation indices calculated over time series of images and decision rules. Three variants of the methodology were applied to detect the changes that occurred in Italy between the years 2018 and 2019, and the results were validated using ISPRA official data. The results show that the produced maps include large commission errors, but thanks to the developed methodology, the area to be photointerpreted was reduced to 7300 km2 (2.4% of Italian surface). The third variant of the methodology provided the highest detection of changes: 70.4% of the changes larger than 100 m2 (the pixel size) and over 84.0% of changes above 500 m2. Omissions are mainly related to single pixel changes, while larger changes are detected by at least one pixel in most of the cases. In conclusion, the developed methodology can improve the detection of land consumption, focusing photointerpretation work over selected areas detected automatically.
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Ilyina, I. S., and T. K. Yurkovskaya. "Contribution of V. B. Sochava to the development of vegetation cartography." Geobotanical mapping, no. 1996 (1997): 3–12. http://dx.doi.org/10.31111/geobotmap/1996.3.
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Academician Victor B. Sochava is a prominent scientist of the present time – a botanist, geographer, ecologist. He is the author of significant scientific works on the theory, methodology and applied aspects of geobotany, the author and editor of numerous vegetation maps of Russia as well as maps of continents and the world as a whole. This communication concerns the role and significance of his works for the recent development of vegetation cartography. Sochava's name is connected with the new phytoecological stage of the thematic cartography. It is in his works that the ideas of phytoecological mapping, its theoretical and methodological foundations have been laid. Just in the 60-s he, time and again, raised the problem of increasing the information capacity of geobotanical maps. The further development in this direction has resulted in elaborating the principles of correlation cartography. The ecological- phytocoenotical map of Asian Russia, s. 1 : 7 500 000, created and edited under his leadership in 1977, became an excellent example of this approach. The system paradigm, developed in the Sochava's works, has given a new impulse to the modern phytoecological mapping and has determined its high level that has reflected in the creation of the phytoecosystem maps synthesizing the properties of vegetation and environments on the base of their structure-forming relations. Then in the paper the main theoretical concepts by V. B. Sochava are considered, such as the two-row classification of vegetation , its structural-dynamic analysis, the concept of epitaxon, the regional concept proper. The application of these and other theoretical concepts and their modern development are illustrated by the vegetation maps of some extensive regions: the European part of the USSR, West Siberia, the southern East Siberia, the drainage-basin of the Amur R., as well as by the new vegetation map of the USSR, s. 1 : 4 000 000, published in 1990. Considerable attention in the communication has been paid to the applied aspects of V. B. Sochava's activity: the creation of specialized thematic maps, such as the prognosis ones, the estimation, resource, nature conservation, medical-geographic, etc. V. B. Sochava kept diverse connections with foreign scientists, he was an active member of various international societies, commissions and associations, participated in international conferences, symposia, published works in different languages, promoting the authority of the national science. At the same time he considered the study of foreign scientific experience to be a necessary condition for successful development of the scientific research in our country.
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Mooney, C., and D. Farrier. "A micro case study of the legal and administrative arrangements for river health in the Kangaroo River (NSW)." Water Science and Technology 45, no. 11 (June 1, 2002): 161–68. http://dx.doi.org/10.2166/wst.2002.0391.
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Kangaroo Valley is a drinking water supply catchment for Kangaroo Valley village, parts of the Southern Highlands and Sydney. It is also a popular recreation area both for swimming and canoeing. Land use has traditionally been dominated by dairy farming but there has been significant and continuing development of land for hobby farms and rural residential subdivision. Dairy industry restructuring has affected the viability of some farms in the Valley and created additional pressure for subdivision. River health is a function of flows, water quality, riparian vegetation, geomorphology and aquatic habitat and riverine biota. River flows in the Kangaroo River are affected by water extraction and storage for urban water supply and extraction by commercial irrigators and riparian land holders which have a significant impact at low flows. Current water quality often does not meet ANZECC Guidelines for primary contact and recreation and the river is a poor source of raw drinking water. Key sources of contaminants are wastewater runoff from agriculture, and poorly performing on-site sewage management systems. Riparian vegetation, which is critical to the maintenance of in-stream ecosystems suffers from uncontrolled stock access and weed infestation. The management of land use and resulting diffuse pollution sources is critical to the long term health of the river. The Healthy Rivers Commission of New South Wales Independent Inquiry into the Shoalhaven River System Final Report July, 1999 found that the longer term protection of the health of the Kangaroo River is contingent upon achievement of patterns of land use that have regard to land capability and also to the capability of the river to withstand the impacts of inappropriate or poorly managed land uses. This micro case study of Kangaroo Valley examines the complex legal and administrative arrangements with particular reference to the management of diffuse pollution for river health. In the past, diffuse pollution has fallen through the gaps in legislation and its administration. Although water pollution legislation is broad enough to embrace diffuse pollution, in practice the Environment Protection Authority has focused on regulating point sources. Water legislation has traditionally been concerned with issues of water quantity rather than water quality. Legislation which allows agency intervention in relation to land degradation has grown from soil conservation roots, neglecting the flow-on effects upon water quality. Under the land use planning system existing land uses are protected from new regulatory requirements. A number of recent developments in NSW law and its administration have set the scene for addressing this past neglect. Water planning provisions in the Water Management Act 2000 have the potential to enable community based Water Management Committees to move away from a narrow focus on water quantity to the broader issues of river health, including water quality. Improved management of on-site sewage management systems is expected as a result of the Local Government (Approvals) Amendment (Sewage Management Regulation) 1998. A draft Regional Environmental Plan prepared for the Sydney Catchment Authority aims to improve the assessment of new development in terms of its impact on drinking water quality. It also moves away from an exclusive concern with controlling new development towards grappling with existing uses. Proposed amendments to the Environmental Planning and Assessment Act, 1979 as detailed in the White Paper, Plan First (2001) include the integration of imperatives derived from catchment strategies and water management plans into local land use plans.
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Moseby, K. E., R. Brandle, and M. Adams. "Distribution, habitat and conservation status of the rare dusky hopping-mouse, Notomys fuscus (Rodentia : Muridae)." Wildlife Research 26, no. 4 (1999): 479. http://dx.doi.org/10.1071/wr97061.
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The distribution, habitat and conservation status of Notomys fuscus were determined by collating past records of the species and conducting field investigations covering areas of historical distribution and similar habitats. Detailed population sampling was carried out in two geographically distinct locations where populations appeared to be extant. Evidence of N. fuscus was found throughout the Strzelecki Desert east and south of the Strzelecki Creek in South Australia and in an isolated group of dunes south-east of the Diamantina River in south-west Queensland. Populations were located in a variety of sand dune habitats (excepting those dominated by Triodia) throughout these areas, implying that the species is a habitat-generalist with a preference for a sandy substrate. Eight floristic groups were identified from the 66 sites sampled, three of which supported N. fuscus populations. These ranged from extremely degraded dune and sand plain systems in the southern Strzelecki Desert, supporting mostly ephemeral plants, to well-vegetated dunes covered by sandhill canegrass,Zygochloa paradoxa, in south-west Queensland. However, the results suggest that the presence of consolidated dunes and perennial vegetation are important for the maintenance of stable populations. Relatively dense populations of N. fuscus were recorded only in the vicinity of major drainage systems. It is hypothesised that the higher nutrient status of the soils surrounding such systems may be an important factor affecting the distribution of N. fuscus. The study reaffirmed the species’ decline since European settlement of Australia, and recommends that the present vulnerable status of the species (IUCN Species Survival Commission (SSC) Rodent Specialist Group) be maintained.
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Al-Shammari, Dhahi, Ignacio Fuentes, Brett M. Whelan, Patrick Filippi, and Thomas F. A. Bishop. "Mapping of Cotton Fields Within-Season Using Phenology-Based Metrics Derived from a Time Series of Landsat Imagery." Remote Sensing 12, no. 18 (September 17, 2020): 3038. http://dx.doi.org/10.3390/rs12183038.
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A phenology-based crop type mapping approach was carried out to map cotton fields throughout the cotton-growing areas of eastern Australia. The workflow was implemented in the Google Earth Engine (GEE) platform, as it is time efficient and does not require processing in multiple platforms to complete the classification steps. A time series of Normalised Difference Vegetation Index (NDVI) imagery were generated from Landsat 8 Surface Reflectance Tier 1 (L8SR) and processed using Fourier transformation. This was used to produce the harmonised-NDVI (H-NDVI) from the original NDVI, and then phase and amplitude values were generated from the H-NDVI to visualise active cotton in the targeted fields. Random Forest (RF) models were built to classify cotton at early, mid and late growth stages to assess the ability of the model to classify cotton as the season progresses, with phase, amplitude and other individual bands as predictors. Results obtained from leave-one-season-out cross validation (LOSOCV) indicated that Overall Accuracy (OA), Kappa, Producer’s Accuracies (PA) and User’s Accuracy (UA), increased significantly when adding amplitude and phase as predictor variables to the model, than prediction using H-NDVI or raw bands only. Commission and omission errors were reduced significantly as the season progressed and more in-season imagery was available. The methodology proposed in this study can map cotton crops accurately based on the reconstruction of the unique cotton reflectance trajectory through time. This study confirms the importance of phenological metrics in improving in-season cotton fields mapping across eastern Australia. This model can be used in conjunction with other datasets to forecast yield based on the mapped crop type for improved decision making related to supply chain logistics and seasonal outlooks for production.
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Lee, M., S. Malyshev, E. Shevliakova, P. C. D. Milly, and P. R. Jaffé. "Capturing interactions between nitrogen and hydrological cycles under historical climate and land use: Susquehanna watershed analysis with the GFDL land model LM3-TAN." Biogeosciences 11, no. 20 (October 20, 2014): 5809–26. http://dx.doi.org/10.5194/bg-11-5809-2014.
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Abstract. We developed a process model LM3-TAN to assess the combined effects of direct human influences and climate change on terrestrial and aquatic nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a soil denitrification, point N sources to streams (i.e., sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of the transport and fate of N in the vegetation–soil–river system in a comprehensive and consistent framework which is responsive to climatic variations and land-use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River Basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 16 monitoring stations as well as a reported budget for the entire basin. By accounting for interannual hydrologic variability, the model was able to capture interannual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream Susquehanna River Basin Commission station Marietta (40°02' N, 76°32' W), it captured the N loads well at multiple locations within the basin with different climate regimes, land-use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contributing to the various ecosystems are stored, lost, and exported via the river. Local analysis of six sub-basins showed combined effects of land use and climate on soil denitrification rates, with the highest rates in the Lower Susquehanna Sub-Basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna Sub-Basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification, indicating that anthropogenic N applications could drive substantial increase of N2O emission, an intermediate of the denitrification process.
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Ilichkina, N. P., N. E. Samofalova, T. S. Makarova, and O. A. Dubinina. "‘YUBILYARKA’ – NEW VARIETY OF WINTER DURUM WHEAT." TAURIDA HERALD OF THE AGRARIAN SCIENCES 4 (24) (November 2020): 62–71. http://dx.doi.org/10.33952/2542-0720-2020-4-24-62-71.
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The developed varieties of winter durum wheat (Triticum durum Desf.) should combine potential productivity with high grain quality and resistance to abiotic and biotic environmental factors. The purpose of the current study was to evaluate a new winter durum wheat variety ‘Yubilyarka’ included in the State Register of Breeding Achievements of the Russian Federation in 2019 as permitted for use in the North Caucasus Region due to its productivity, resistance to stress factors and grain quality. The study of the variety was carried out at the test plot of the State Scientific Establishment “Agricultural research center “Donskoy” in 2013–2019. In the field trials (competitive variety testing), the winter durum wheat variety ‘Yubilyarka’ was sown after green fallow, peas, maize for grain, sunflower. Intraspecific step hybridization with a subsequent individual selection was the main method for creating variety ‘Yubilyarka’. The experimental part of the study was carried out according to the methods of the Commission for the Testing and Protection of Selection Achievements (Gossortcommission) and the methodology of field experiments. In the course of the research, the morphological, biological, and economically valuable traits of the variety ‘Yubilyarka’ were evaluated. During the study in the competitive variety testing, the yield increase, if compared to standard variety ‘Donchanka’, when sown after green fallow, was 0.99 t/ha. The new variety is more heat and drought tolerant (both in the initial phases of plant growth and development and in subsequent periods of active vegetation), is sufficiently winter hardy, and resistant to the main diseases in the region. The quality indicators of grain, groats, and pasta comply with the requirements of GOST RF 9353-2016 and existing standards for durum wheat. The grain vitreousness, on average, was 91 % and more, hectolitre weight – 784 g/l, protein content – 14.29 %, gluten content – 24.7 %, gluten quality (SDS test) – 33 ml, pasta color – 4.1 points. The introduction of the new variety into production will allow improving the gross yield of durum wheat both for the processing industry and for export use.
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Guo, Yangnan, Cangjiao Wang, Shaogang Lei, Junzhe Yang, and Yibo Zhao. "A Framework of Spatio-Temporal Fusion Algorithm Selection for Landsat NDVI Time Series Construction." ISPRS International Journal of Geo-Information 9, no. 11 (November 4, 2020): 665. http://dx.doi.org/10.3390/ijgi9110665.
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Spatio-temporal fusion algorithms dramatically enhance the application of the Landsat time series. However, each spatio-temporal fusion algorithm has its pros and cons of heterogeneous land cover performance, the minimal number of input image pairs, and its efficiency. This study aimed to answer: (1) how to determine the adaptability of the spatio-temporal fusion algorithm for predicting images in prediction date and (2) whether the Landsat normalized difference vegetation index (NDVI) time series would benefit from the interpolation with images fused from multiple spatio-temporal fusion algorithms. Thus, we supposed a linear relationship existed between the fusion accuracy and spatial and temporal variance. Taking the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM) as basic algorithms, a framework was designed to screen a spatio-temporal fusion algorithm for the Landsat NDVI time series construction. The screening rule was designed by fitting the linear relationship between the spatial and temporal variance and fusion algorithm accuracy, and then the fitted relationship was combined with the graded accuracy selecting rule (R2) to select the fusion algorithm. The results indicated that the constructed Landsat NDVI time series by this paper proposed framework exhibited the highest overall accuracy (88.18%), and lowest omission (1.82%) and commission errors (10.00%) in land cover change detection compared with the moderate resolution imaging spectroradiometer (MODIS) NDVI time series and the NDVI time series constructed by a single STARFM or ESTARFM. Phenological stability analysis demonstrated that the Landsat NDVI time series established by multiple spatio-temporal algorithms could effectively avoid phenological fluctuations in the time series constructed by a single fusion algorithm. We believe that this framework can help improve the quality of the Landsat NDVI time series and fulfill the gap between near real-time environmental monitoring mandates and data-scarcity reality.
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Taguas, E. V., C. Arroyo, A. Lora, G. Guzmán, K. Vanderlinden, and J. A. Gómez. "Exploring the linkage between spontaneous grass cover biodiversity and soil degradation in two olive orchard microcatchments with contrasting environmental and management conditions." SOIL 1, no. 2 (November 9, 2015): 651–64. http://dx.doi.org/10.5194/soil-1-651-2015.
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Abstract. Spontaneous grass covers are an inexpensive soil erosion control measure in olive orchards. Olive farmers allow grass to grow on sloping terrain to comply with the basic environmental standards derived from the Common Agricultural Policy (CAP, European Commission). However, to date there are few studies assessing the environmental quality considering such covers. In this study, we measured biodiversity indices for spontaneous grass cover in two olive orchards with contrasting site conditions and management regimes in order to evaluate the potential for biodiversity metrics to serve as an indicator of soil degradation. In addition, the differences and temporal variability of biodiversity indicators and their relationships with environmental factors such as soil type and properties, precipitation, topography and soil management were analysed. Different grass cover biodiversity indices were evaluated in two olive orchard catchments under conventional tillage and no tillage with grass cover, during 3 hydrological years (2011–2013). Seasonal samples of vegetal material and photographs in a permanent grid (4 samples ha−1) were taken to characterize the temporal variations of the number of species, frequency of life forms, diversity and modified Shannon and Pielou indices. Sorensen's index showed strong differences in species composition for the grass covers in the two olive orchard catchments, which are probably linked to the different site conditions. The catchment (CN) with the best site conditions (deeper soil and higher precipitation) and most intense management presented the highest biodiversity indices as well as the highest soil losses (over 10 t ha−1). In absolute terms, the diversity indices of vegetation were reasonably high for agricultural systems in both catchments, despite the fact that management activities usually severely limit the landscape and the variety of species. Finally, a significantly higher content of organic matter in the first 10 cm of soil was found in the catchment with worse site conditions in terms of water deficit, average annual soil losses of 2 t ha−1 and the least intense management. Therefore, the biodiversity indices considered in this study to evaluate spontaneous grass cover were not found to be suitable for describing the soil degradation in the study catchments.
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López-Andreu, Francisco Javier, Manuel Erena, Jose Antonio Dominguez-Gómez, and Juan Antonio López-Morales. "Sentinel-2 Images and Machine Learning as Tool for Monitoring of the Common Agricultural Policy: Calasparra Rice as a Case Study." Agronomy 11, no. 4 (March 25, 2021): 621. http://dx.doi.org/10.3390/agronomy11040621.
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The European Commission introduces the Control by Monitoring through new technologies to manage Common Agricultural Policy funds through the Regulation 2018/746. The advances in remote sensing have been considered one of these new technologies, mainly since the European Space Agency designed the Copernicus Programme. The Sentinel-1 (radar range) and Sentinel-2 (optical range) satellites have been designed for monitoring agricultural problems based on the characteristics they provide. The data provided by the Sentinel 2 missions, together with the emergence of different scientific disciplines in artificial intelligence —especially machine learning— offer the perfect basis for identifying and classifying any crop and its phenological state. Our research is based on developing and evaluating a pixel-based supervised classification scheme to produce accurate rice crop mapping in a smallholder agricultural zone in Calasparra, Murcia, Spain. Several models are considered to obtain the most suitable model for each element of the time series used; pixel-based classification is performed and finished with a statistical treatment. The highly accurate results obtained, especially across the most significant vegetative development dates, indicate the benefits of using Sentinel-2 data combined with Machine Learning techniques to identify rice crops. It should be noted that it was possible to locate rice crop areas with an overall accuracy of 94% and standard deviation of 1%, which could be increased to 96% (±1%) if we focus on the months of the crop’s highest development state. Thanks to the proposed methodology, the on-site inspections carried out, 5% of the files, have been replaced by remote sensing evaluations of 100% of the analyzed season files. Besides, by adjusting the model input data, it is possible to detect unproductive or abandoned plots.
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Wan Mohd Jaafar, Wan, Iain Woodhouse, Carlos Silva, Hamdan Omar, Khairul Abdul Maulud, Andrew Hudak, Carine Klauberg, Adrián Cardil, and Midhun Mohan. "Improving Individual Tree Crown Delineation and Attributes Estimation of Tropical Forests Using Airborne LiDAR Data." Forests 9, no. 12 (December 5, 2018): 759. http://dx.doi.org/10.3390/f9120759.
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Individual tree crown (ITC) segmentation is an approach to isolate individual tree from the background vegetation and delineate precisely the crown boundaries for forest management and inventory purposes. ITC detection and delineation have been commonly generated from canopy height model (CHM) derived from light detection and ranging (LiDAR) data. Existing ITC segmentation methods, however, are limited in their efficiency for characterizing closed canopies, especially in tropical forests, due to the overlapping structure and irregular shape of tree crowns. Furthermore, the potential of 3-dimensional (3D) LiDAR data is not fully realized by existing CHM-based methods. Thus, the aim of this study was to develop an efficient framework for ITC segmentation in tropical forests using LiDAR-derived CHM and 3D point cloud data in order to accurately estimate tree attributes such as the tree height, mean crown width and aboveground biomass (AGB). The proposed framework entails five major steps: (1) automatically identifying dominant tree crowns by implementing semi-variogram statistics and morphological analysis; (2) generating initial tree segments using a watershed algorithm based on mathematical morphology; (3) identifying “problematic” segments based on predetermined set of rules; (4) tuning the problematic segments using a modified distance-based algorithm (DBA); and (5) segmenting and counting the number of individual trees based on the 3D LiDAR point clouds within each of the identified segment. This approach was developed in a way such that the 3D LiDAR points were only examined on problematic segments identified for further evaluations. 209 reference trees with diameter at breast height (DBH) ≥ 10 cm were selected in the field in two study areas in order to validate ITC detection and delineation results of the proposed framework. We computed tree crown metrics (e.g., maximum crown height and mean crown width) to estimate aboveground biomass (AGB) at tree level using previously published allometric equations. Accuracy assessment was performed to calculate percentage of correctly detected trees, omission and commission errors. Our method correctly identified individual tree crowns with detection accuracy exceeding 80 percent at both forest sites. Also, our results showed high agreement (R2 > 0.64) in terms of AGB estimates using 3D LiDAR metrics and variables measured in the field, for both sites. The findings from our study demonstrate the efficacy of the proposed framework in delineating tree crowns, even in high canopy density areas such as tropical rainforests, where, usually the traditional algorithms are limited in their performances. Moreover, the high tree delineation accuracy in the two study areas emphasizes the potential robustness and transferability of our approach to other densely forested areas across the globe.
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Romashchenko, M. I., A. P. Shatkovskyi, V. V. Vasiuta, S. V. Usatyi, L. G. Usata, S. V. Riabkov, O. V. Zhuravlov, R. A. Kupiedinova, V. V. Bezruk, and Yu O. Cherevychnyi. "SCIENTIFIC SCHOOL OF MICROIRRIGATION: ACHIEVEMENTS AND DEVELOPMENT PROSPECTS." Міжвідомчий тематичний науковий збірник "Меліорація і водне господарство", no. 2 (December 12, 2019): 68–77. http://dx.doi.org/10.31073/mivg201902-199.
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Microirrigation is by far the most progressive irrigation method, with efficiencies reaching 92-98 %. According to the International Commission on Irrigation and Drainage, the world's agricultural land, which is irrigated through micro-irrigation systems, is constantly growing and now stands at over 20 million hectares. By the "Irrigation and drainage strategy in Ukraine until 2030" micro-irrigation methods are defined as one of the strategic directions of the state policy of the branch.
Research on the direction of "micro-irrigation of crops" in Ukraine began from the late 60's of the last century. The historical aspect of the development of research in this area is thoroughly covered in previous scientific papers. Therefore, the purpose of this study is a comprehensive analysis of the basic fundamental and applied results of research of the scientific school on micro irrigation IWPaLR NAAS in the early XXI century and substantiation of perspective directions of their development.
Using theoretical methods of scientific research (analysis and synthesis, comparison, classification and generalization), the authors systematized the most significant scientific results in terms of normative, methodological, technical and technological components. The list of normative and methodological documents prepared by IWPaLR NAAS in the direction of microirrigation is given. The results of developments in the technological component are detailed according to the research objects: water regime and processes of water consumption of crops, fertigation, pestigation, the influence of local moistening, fertilizers and water of different quality on the soil-plant-technical means of irrigation system, the formation of soil moisture zones, methods of appointment timing of vegetation irrigation and irrigation management systems. The key scientific results of the irrigation facilities’ testing laboratory are highlighted. The list of developed and implemented by the IWPaLR NAAS technical means of microirrigation systems is given. The strategic directions of further scientific research are substantiated, which should meet the global trend for environmentally friendly irrigation, as well as resource and energy conservation. The need of Ukraine in the systems of microirrigation of agricultural crops for the period up to 2030, the role of current and future developments of the scientific school of micro irrigation IWPaLR NAAS on their implementation are determined.
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Ward Thompson, Catharine, Eva Silveirinha de Oliveira, Sara Tilley, Aldo Elizalde, Willings Botha, Andrew Briggs, Steven Cummins, et al. "Health impacts of environmental and social interventions designed to increase deprived communities’ access to urban woodlands: a mixed-methods study." Public Health Research 7, no. 2 (January 2019): 1–172. http://dx.doi.org/10.3310/phr07020.
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BackgroundContact with natural environments can bring health benefits, but research is lacking on how changes in access to natural environments might improve health, especially for deprived populations.ObjectiveTo evaluate the health impacts of woodland environment interventions intended to increase communities’ engagement with these woodlands.DesignA prospective study of Forestry Commission Scotland’s Woods In and Around Towns (WIAT) programme in deprived communities to enhance public access to natural environments. The study investigated the impact that WIAT had on community-level mental health over time.SettingThree intervention and three control woodland sites, and associated communities within 1.5 km of the woodlands, located in central Scotland and eligible for WIAT support.ParticipantsA core community survey was administered at each site in three waves, at baseline and after each phase of intervention (n = 5460, panel A). The completed survey contained a nested longitudinal cohort (n = 609, panel B). Community members also undertook 6-monthly environmental audits at all sites (n = 256) and participated in post-intervention focus groups (n = 34).InterventionsPhase 1 involved physical changes to the woodlands, including footpaths, entrances and vegetation. Phase 2 involved community engagement events promoting woodland use.Main outcome measuresThe primary outcome was the Perceived Stress Scale (PSS). Other health measures included health-related quality of life (HRQoL) EuroQol-5 Dimensions (EQ-5D), physical activity (PA) [International Physical Activity Questionnaire (IPAQ)], connectedness to nature [Inclusion of Nature in Self (INS) scale] and social cohesion.ResultsThe PSS scores significantly increased in the intervention group and marginally decreased in the control group. Multilevel regression models showed a differential impact between the intervention and the control at survey wave 3 in panel A [B(unstandardised coefficient) 3.58, 95% confidence interval (CI) 2.85 to 4.31;p < 0.001] and in panel B [B3.03, 95% CI 1.54 to 4.52;p < 0.001]. Using the same analytical approach, no significant change in HRQoL was associated with the intervention. Economic assessment included an illustrative cost–utility analysis and a cost–consequences analysis. The differential in stress between the intervention group and the control group was lower or non-significant in those who visited ‘nature’ in the previous year [panel A,B1.9, 95% CI 0.8 to 3.0;p < 0.001; panel B,B0.64, 95% CI –1.60 to 2.88;p = 0.57]. The IPAQ score showed a positive association with the intervention for moderate levels of PA [panel B,B559.3, 95% CI 211.3 to 907.2;p = 0.002] and overall PA [panel B,B861.5, 95% CI 106.5 to 1616.4;p = 0.025]. The intervention was also associated with increased nature connectedness and social cohesion by wave 3 – significant for panel A only. Qualitative and quantitative evidence showed that interventions increased the perceived quality of the woodland environment and enhanced its enjoyment for different activities, but the increase in use of natural environments post intervention was only 6% (panel B).LimitationsThis study was limited to three intervention sites. External factors may be the primary influence on health outcomes.ConclusionsThe WIAT interventions did not improve community-level health within 6 months of completion, and hence there was no basis for demonstrating cost-effectiveness. However, the WIAT interventions are low cost (average £11.80 per person in the eligible population) and have potential for cost-effectiveness, if health benefits were found in the longer term.Future workUsing routinely collected data to consider a whole-programme evaluation is recommended.FundingThe National Institute for Health Research Public Health Research programme.
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Regos, Adrián, and Jesús Domínguez. "The contribution of Earth observation technologies to the reporting obligations of the Habitats Directive and Natura 2000 network in a protected wetland." PeerJ 6 (March 21, 2018): e4540. http://dx.doi.org/10.7717/peerj.4540.
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Background Wetlands are highly productive systems that supply a host of ecosystem services and benefits. Nonetheless, wetlands have been drained and filled to provide sites for building houses and roads and for establishing farmland, with an estimated worldwide loss of 64–71% of wetland systems since 1900. In Europe, the Natura 2000 network is the cornerstone of current conservation strategies. Every six years, Member States must report on implementation of the European Habitats Directive. The present study aims to illustrate how Earth observation (EO) technologies can contribute to the reporting obligations of the Habitats Directive and Natura 2000 network in relation to wetland ecosystems. Methods We analysed the habitat changes that occurred in a protected wetland (in NW Spain), 13 years after its designation as Natura 2000 site (i.e., between 2003 and 2016). For this purpose, we analysed optical multispectral bands and water-related and vegetation indices derived from data acquired by Landsat 7 TM, ETM+ and Landsat 8 OLI sensors. To quantify the uncertainty arising from the algorithm used in the classification procedure and its impact on the change analysis, we compared the habitat change estimates obtained using 10 different classification algorithms and two ensemble classification approaches (majority and weighted vote). Results The habitat maps derived from the ensemble approaches showed an overall accuracy of 94% for the 2003 data (Kappa index of 0.93) and of 95% for the 2016 data (Kappa index of 0.94). The change analysis revealed important temporal dynamics between 2003 and 2016 for the habitat classes identified in the study area. However, these changes depended on the classification algorithm used. The habitat maps obtained from the two ensemble classification approaches showed a reduction in habitat classes dominated by salt marshes and meadows (24.6–26.5%), natural and semi-natural grasslands (25.9–26.5%) or sand dunes (20.7–20.9%) and an increase in forest (31–34%) and reed bed (60.7–67.2%) in the study area. Discussion This study illustrates how EO–based approaches might be particularly useful to help (1) managers to reach decisions in relation to conservation, (2) Member States to comply with the requirements of the European Habitats Directive (92/43/EEC), and (3) the European Commission to monitor the conservation status of the natural habitat types of community interest listed in Annex I of the Directive. Nonetheless, the uncertainty arising from the large variety of classification methods used may prevent local managers from basing their decisions on EO data. Our results shed light on how different classification algorithms may provide very different quantitative estimates, especially for water-dependent habitats. Our findings confirm the need to account for this uncertainty by applying ensemble classification approaches, which improve the accuracy and stability of remote sensing image classification.
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Willoughby, Ian. "Future alternatives to the use of herbicides in British forestry." Canadian Journal of Forest Research 29, no. 7 (August 1, 1999): 866–74. http://dx.doi.org/10.1139/x99-043.
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Weed control is often crucial for successful tree establishment in British forestry. Herbicides currently offer the most cost-effective means available for achieving this, but research into alternatives is required. Recent experiments have been conducted by the Great Britain Forestry Commission investigating the use of 19 alternative ground cover and silvicultural treatments for newly planted ash (Fraxinus excelsior L.) and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) established on fertile lowland ex-agricultural sites. Most ground cover treatments proved difficult to establish and were more competitive to trees than naturally occurring vegetation. White clover (Trifolium repens L.) showed some potential for suppressing weed vegetation without reducing tree growth. Closer initial tree planting densities appeared to offer a practical means of reducing herbicide inputs, whilst still permitting good rates of growth. It is concluded that a comprehensive review of other alternative methods of weed control is now required to set a framework for future Great Britain Forestry Commission research in this field.
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TAKAHASHI, Toshimori, Yoriko HATASE, Tomoko MINAGAWA, and Yoshinobu HOSHINO. "Study on Riverine Vegetation Transition Using Multi-temporal Vegetation Maps." Journal of The Japanese Institute of Landscape Architecture 68, no. 5 (2005): 647–50. http://dx.doi.org/10.5632/jila.68.647.
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McGrath, Melissa A., Mark T. Lemmon, Regis Courtin, Luisa M. Lara, Sang Joon Kim, Leonid V. Ksanfomality, David Morrison, Viktor G. Tejfel, and Padma A. Yanamandra-Fisher. "COMMISSION 16: PHYSICAL STUDY OF PLANETS & SATELLITES." Proceedings of the International Astronomical Union 6, T27B (May 14, 2010): 173–74. http://dx.doi.org/10.1017/s1743921310004953.
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The Business Meeting of IAU Commission 16 was held at the General Assembly in Rio de Janeiro on August 13, 2009. The meeting was called to order at 9:15am by Commission President, Régis Courtin, with 12 members present. Commission 16 now has 312 members, up from 271 at the last General Assembly. It is now the third largest Commission in Division III, after Commission 15 and Commission 51.