Journal articles: 'Productivity maps'

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Rozhkov, V. A., and A. Z. Shvidenko. "The first digital maps of biological productivity parameters." Eurasian Soil Science 43, no. 11 (November 2010): 1202–10. http://dx.doi.org/10.1134/s1064229310110025.

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Oral, Emel Laptali, and Mustafa Oral. "Predicting construction crew productivity by using Self Organizing Maps." Automation in Construction 19, no. 6 (October 2010): 791–97. http://dx.doi.org/10.1016/j.autcon.2010.05.001.

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Dalposso, Gustavo Henrique, Miguel Angel Uribe-Opazo, and Fernanda De Bastiani. "Spatial-temporal Analysis of Soybean Productivity Using Geostatistical Methods." Journal of Agricultural Studies 9, no. 2 (May 2, 2021): 283. http://dx.doi.org/10.5296/jas.v9i2.18494.

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To have information about the soybean productivity over the crop years is essential to define strategies to increase profits and reduce costs and most important to reduce environmental impacts. One form of monitoring is the use of Geostatistical methods, which allow us to obtain maps with more accurate predictions. In this paper, an area of 127.16 ha was studied during six crop years between 2012/2013 and 2017/2018. We found that productivity values vary between crop years, mainly due to uncontrollable climatic factors. The removal of influential points caused changes in the predicted values showed in the maps, and the use of scaled semivariograms allowed us to obtain similar maps to those obtained considering the model without influential points, then there was no need to exclude observations. The use of a model with replicates helped to identify regions where productivity was lower. The use of explanatory variables allowed us to elaborate a more accurate thematic map in the 2017/2018 crop year, which was well evidenced by the prediction standard error map.

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Kim, Jeong-Cheol, Hyung-Sup Jung, and Saro Lee. "Spatial Mapping of the Groundwater Potential of the Geum River Basin Using Ensemble Models Based on Remote Sensing Images." Remote Sensing 11, no. 19 (September 30, 2019): 2285. http://dx.doi.org/10.3390/rs11192285.

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This study analyzed the Groundwater Productivity Potential (GPP) of Okcheon city, Korea, using three different models. Two of these three models are data mining models: Boosted Regression Tree (BRT) model and Random Forest (RF) model. The other model is the Logistic Regression (LR) model. The three models are based on the relationship between groundwater-productivity data (specific capacity (SPC) and transmissivity (T)) and the related hydro-geological factors from thematic maps, such as topography, lineament, geology, land cover, and etc. The thematic maps which are generated from the remote sensing images. Groundwater productivity data were collected from 86 wells locations. The resulting GPP maps were validated through area-under-the-curve (AUC) analysis using wells data that had not been used for training the model. When T was used in the BRT, RF, and LR models, the obtained GPP maps had 81.66%, 80.21%, and 85.04% accuracy, respectively, and when SPC was used, the maps had 81.53%, 78.57%, and 82.22% accuracy, respectively. The LR model, which is a statistical model, showed the highest verification accuracy, also the other two models showed high accuracies. These observations indicate that all three models can be useful for groundwater resource development.

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Nakamura, Noboru, Teruaki Yuta, Mariko Senda, and Taku Mizuta. "Monitoring Avian Productivity and Survivorship (MAPS) Programin Fukushima, Japan (2018 to 2020)." Journal of the Yamashina Institute for Ornithology 53, no. 1 (June 30, 2021): 44–56. http://dx.doi.org/10.3312/jyio.53.44.

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Gopalakrishnan, Ranjith, Jobriath Kauffman, Matthew Fagan, John Coulston, Valerie Thomas, Randolph Wynne, Thomas Fox, and Valquiria Quirino. "Creating Landscape-Scale Site Index Maps for the Southeastern US Is Possible with Airborne LiDAR and Landsat Imagery." Forests 10, no. 3 (March 6, 2019): 234. http://dx.doi.org/10.3390/f10030234.

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Sustainable forest management is hugely dependent on high-quality estimates of forest site productivity, but it is challenging to generate productivity maps over large areas. We present a method for generating site index (a measure of such forest productivity) maps for plantation loblolly pine (Pinus taeda L.) forests over large areas in the southeastern United States by combining airborne laser scanning (ALS) data from disparate acquisitions and Landsat-based estimates of forest age. For predicting canopy heights, a linear regression model was developed using ALS data and field measurements from the Forest Inventory and Analysis (FIA) program of the US Forest Service (n = 211 plots). The model was strong (R2 = 0.84, RMSE = 1.85 m), and applicable over a large area (~208,000 sq. km). To estimate the site index, we combined the ALS estimated heights with Landsat-derived maps of stand age and planted pine area. The estimated bias was low (−0.28 m) and the RMSE (3.8 m, relative RMSE: 19.7%, base age 25 years) was consistent with other similar approaches. Due to Landsat-related constraints, our methodology is valid only for relatively young pine plantations established after 1984. We generated 30 m resolution site index maps over a large area (~832 sq. km). The site index distribution had a median value of 19.4 m, the 5th percentile value of 13.0 m and the 95th percentile value of 23.3 m. Further, using a watershed level analysis, we ranked these regions by their estimated productivity. These results demonstrate the potential and value of remote sensing based large-area site index maps.

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Suszek, Grazieli, Eduardo G. de Souza, Miguel A. Uribe-Opazo, and Lucia H. P. Nobrega. "Determination of management zones from normalized and standardized equivalent produtivity maps in the soybean culture." Engenharia Agrícola 31, no. 5 (October 2011): 895–905. http://dx.doi.org/10.1590/s0100-69162011000500007.

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Through the site-specific management, the precision agriculture brings new techniques for the agricultural sector, as well as a larger detailing of the used methods and increase of the global efficiency of the system. The objective of this work was to analyze two techniques for definition of management zones using soybean yield maps, in a productive area handled with localized fertilization and other with conventional fertilization. The sampling area has 1.74 ha, with 128 plots with site-specific fertilization and 128 plots with conventional fertilization. The productivity data were normalized by two techniques (normalized and standardized equivalent productivity), being later classified in management zones. It can be concluded that the two methods of management zones definition had revealed to be efficient, presenting similarities in the data disposal. Due to the fact that the equivalent standardized productivity uses standard score, it contemplates a better statistics justification.

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Chang, Jinfeng, Philippe Ciais, Mario Herrero, Petr Havlik, Matteo Campioli, Xianzhou Zhang, Yongfei Bai, et al. "Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management." Biogeosciences 13, no. 12 (June 29, 2016): 3757–76. http://dx.doi.org/10.5194/bg-13-3757-2016.

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Abstract. Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5° by 0.5°. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 1901–2012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, rising CO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 × 106 km2 in 1901 to 12.3 × 106 km2 in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and interannual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here.

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Alegria, Cristina, Natália Roque, Teresa Albuquerque, Paulo Fernandez, and Maria Margarida Ribeiro. "Modelling Maritime Pine (Pinus pinaster Aiton) Spatial Distribution and Productivity in Portugal: Tools for Forest Management." Forests 12, no. 3 (March 19, 2021): 368. http://dx.doi.org/10.3390/f12030368.

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Research Highlights: Modelling species’ distribution and productivity is key to support integrated landscape planning, species’ afforestation, and sustainable forest management. Background and Objectives: Maritime pine (Pinus pinaster Aiton) forests in Portugal were lately affected by wildfires and measures to overcome this situation are needed. The aims of this study were: (1) to model species’ spatial distribution and productivity using a machine learning (ML) regression approach to produce current species’ distribution and productivity maps; (2) to model the species’ spatial productivity using a stochastic sequential simulation approach to produce the species’ current productivity map; (3) to produce the species’ potential distribution map, by using a ML classification approach to define species’ ecological envelope thresholds; and (4) to identify present and future key factors for the species’ afforestation and management. Materials and Methods: Spatial land cover/land use data, inventory, and environmental data (climate, topography, and soil) were used in a coupled ML regression and stochastic sequential simulation approaches to model species’ current and potential distributions and productivity. Results: Maritime pine spatial distribution modelling by the ML approach provided 69% fitting efficiency, while species productivity modelling achieved only 43%. The species’ potential area covered 60% of the country’s area, where 78% of the species’ forest inventory plots (1995) were found. The change in the Maritime pine stands’ age structure observed in the last decades is causing the species’ recovery by natural regeneration to be at risk. Conclusions: The maps produced allow for best site identification for species afforestation, wood production regulation support, landscape planning considering species’ diversity, and fire hazard mitigation. These maps were obtained by modelling using environmental covariates, such as climate attributes, so their projection in future climate change scenarios can be performed.

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KAWAJI, Noritomo, and Tatsuya NAKADA. "Effective Use of the Monitoring Avian Productivity and Survivorship (MAPS) Program in Japan." Bulletin of the Japanese Bird Banding Association 27, no. 1 (2015): 14–22. http://dx.doi.org/10.14491/jbba.00065.

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Guedes Filho, Osvaldo, Sidney Rosa Vieira, Marcio Koiti Chiba, and Célia Regina Grego. "Geostatistical analysis of crop yield maps in a long term no tillage system." Bragantia 69, suppl (2010): 9–18. http://dx.doi.org/10.1590/s0006-87052010000500003.

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It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

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Bai, Wei, Zhan Xiang Sun, Jia Ming Zheng, Li Shuang Wang, and Zhi Yan Hou. "Studies on Climate Potential Productivity of Dryland Farming in Fuxin of Liaoning Province." Advanced Materials Research 726-731 (August 2013): 4900–4905. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.4900.

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Based on the meteorological data for the period of 1951-2009 in Fuxin,the article estimates the photosynthesis, photo-temperature and climate potential productivity of dryland farming in Fuxin of Liaoning province, and analyzes the potential productivity interannual change in crop growth period (April-September). The result shows that the long-time average value of the photosynthesis, photo-temperature and climate potential productivity are 31.89×104kg/hm2, 26.80×104kg/hm2and 18.29×104kg/hm2in Fuxin. The interannual change trend of potential productivity is that the photosynthesis, photo-temperature and climate potential productivity are overall reduced, the photosynthesis and photo-temperature potential productivity are not obvious, and the climate potential productivity is obvious. The monthly climate potential productivity contour maps show that the climate potential productivity change dramatically, and the low evalue areas of crop growth period have the continue expansion trend after 2009.

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Neves, Mirna A., and Norberto Morales. "Structural control over well productivity in the Jundiaí River Catchment, Southeastern Brazil." Anais da Academia Brasileira de Ciências 79, no. 2 (June 2007): 307–20. http://dx.doi.org/10.1590/s0001-37652007000200012.

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The well productivity in crystalline terrains is extremely changeable and depends on external factors, in addition to the intrinsic properties of rocks. In the Jundiaí River Catchment, Southeastern Brazil, the main factor that influences well productivity is the existence of open discontinuities permeability in geologic environments that favor groundwater recharge. In that area, Pre-Cambrian shear and fault zones were reactivated throughout geologic time, controlling the morphostructural compartments and the Cenozoic sedimentary deposition. Superposition of productivity data and structural maps showed that more productive wells are concentrated mainly along the regional geologic structures. The structural control over well productivity is also noticeable in detailed scale. Using fine scale maps we show that the most productive wells are located in areas where brittle structures with NW-SE and E-W directions denote the action of neotectonic transtensional stress. The comprehension of evolutionary geologic history allied to fracturing analysis proved to be an efficient and a low cost technique, which is adequate for selecting areas for further developments using more expensive methods.

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Oliveira, Danilo Tedesco de, Leonardo Bernache, Luan Pereira de Oliveira, Murilo Aparecido Voltarelli, and Rouverson Pereira da Silva. "A New Approach to Statistical Process Control: Identification of Outliers in Yield Maps." Journal of Agricultural Science 10, no. 8 (July 10, 2018): 334. http://dx.doi.org/10.5539/jas.v10n8p334.

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The tools of precision agriculture are of utmost importance in the Brazilian agribusiness, enabling increases in yields and reducing production costs. The use of harvest monitoring systems makes it possible due the possibility to identify pontual problems in an area, however, it becomes necessary to be working properly so it does not acquire incorrect information. Therefore, the purpose with this study was to propose a new approach to identify discrepant points in harvesting maps using statistical process control, as well as to define the best multiple of the standard deviation to identificate these points. The work was conducted during the soybean harvesting at São Geronimo farm in an area of 38 hectares in the municipality of Candido Mota, located in the the state of São Paulo. For gathering information, it was used a Stara crop monitoring system (model Topper Maps) set to record information during harvest in each three second. The productivity data were used to generate an individual control chart to identify points that were out of control so they could be removed. Two standard deviation multiples, that presented an average productivity closer to the average real productivity of the area, were selected. The multiples of the deviations that came closest were the 2σ and 3σ. Two multiples of standard deviation presented an average yield closer to the average real yield of the area. Individual control charts can be used to set control limits and identify possible discrepancies. The multiple of standard deviation 3σ presented information with greater reliability.

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Degbelo, Auriol, Jan Kruse, and Max Pfeiffer. "Interactive maps, productivity and user experience: A user study in the e‐mobility domain." Transactions in GIS 23, no. 6 (September 6, 2019): 1352–73. http://dx.doi.org/10.1111/tgis.12576.

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Alegria, Cristina, Natália Roque, Teresa Albuquerque, Saki Gerassis, Paulo Fernandez, and Maria Margarida Ribeiro. "Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal." Forests 11, no. 8 (August 12, 2020): 880. http://dx.doi.org/10.3390/f11080880.

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Species ecological envelope maps were obtained for the two main Portuguese wood-production species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. Background and Objectives: The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. Materials and Methods: Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The official land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. Results: The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ afforestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to differentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. Conclusions: These findings are key to support recommendations for future afforestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios.

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Vilela, Raúl, and Jose María Bellido. "Fishing suitability maps: helping fishermen reduce discards." Canadian Journal of Fisheries and Aquatic Sciences 72, no. 8 (August 2015): 1191–201. http://dx.doi.org/10.1139/cjfas-2013-0522.

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Discards poses a serious problem for the productivity and sustainability of European fisheries and thus is an important fisheries and ecological management issue to be solved. In this paper we present a statistical tool, based on the random forest technique, that aims to reduce the negative ecological impact of fishing by providing fishermen with near-real-time maps of a fishing suitability index based on haul-by-haul catch and discard rates, indicating the most suitable areas for fishing. These easy-to-interpret maps are to be accessible to users via an online geoportal. Observer data from the Spanish discard sampling program from 2004 to 2008 for several species caught in the Cantabrian Sea (ICES area VIIIc) were used to illustrate the random forest approach. Results in the case study varied among species and seasons, with better results achieved for balanced datasets, such as those for economically valuable target species with segregated life stages. We discuss how this online tool could be useful for fisheries management, particularly in the context of the European Common Fisheries Policy reform and the discard ban on commercial species.

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Saatchi, S., Y. Malhi, B. Zutta, W. Buermann, L. O. Anderson, A. M. Araujo, O. L. Phillips, et al. "Mapping landscape scale variations of forest structure, biomass, and productivity in Amazonia." Biogeosciences Discussions 6, no. 3 (June 4, 2009): 5461–505. http://dx.doi.org/10.5194/bgd-6-5461-2009.

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Abstract. Landscape and environmental variables such as topography, geomorphology, soil types, and climate are important factors affecting forest composition, structure, productivity, and biomass. Here, we combine a network of forest inventories with recently developed global data products from satellite observations in modeling the potential distributions of forest structure and productivity in Amazonia and examine how geomorphology, soil, and precipitation control these distributions. We use the RAINFOR network of forest plots distributed in lowland forests across Amazonia, and satellite observations of tree cover, leaf area index, phenology, moisture, and topographical variations. A maximum entropy estimation (Maxent) model is employed to predict the spatial distribution of several key forest structure parameters: basal area, fraction of large trees, fraction of palms, wood density, productivity, and above-ground biomass at 5 km spatial resolution. A series of statistical tests at selected thresholds as well as across all thresholds and jackknife analysis are used to examine the accuracy of distribution maps and the relative contributions of environmental variables. The final maps were interpreted using soil, precipitation, and geomorphological features of Amazonia and it was found that the length of dry season played a key role in impacting the distribution of all forest variables except the wood density. Soil type had a significant impact on the wood productivity. Most high productivity forests were distributed either on less infertile soils of western Amazonia and Andean foothills, on crystalline shields, and younger alluvial deposits. Areas of low elevation and high density of small rivers of Central Amazonia showed distinct features, hosting mainly forests with low productivity and smaller trees.

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Davletbakova, L. A., S. I. Gabitova, V. Yu Klimov, D. V. Shuvaev, I. Ya Edelman, and S. А. Shmidt. "A new method for monitoring wells productivity index dynamics." PROneft’. Proffessional’no o nefti 6, no. 2 (June 30, 2021): 33–38. http://dx.doi.org/10.51890/2587-7399-2021-6-2-33-38.

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А method for monitoring wells productivity index dynamics from the moment of its start-ups is proposed. It allows detecting candidates for conducting well tests (WT) and well interventions for the increase of a daily production. The method is based on an integral analysis using pressure maps and well tests. Application of this method on the Salym group of oilfields has allowed concluding about wells stock status, about productivity index dynamics in time, also to make an assumption about the reasons for its change. The analysis showed that productivity index relative changes in horizontal wells lower than in slanted wells.

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Dalposso, Gustavo H., Miguel A. Uribe-Opazo, Erivelto Mercante, Jerry A. Johann, and Joelmir A. Borssoi. "Comparison measures of maps generated by geostatistical methods." Engenharia Agrícola 32, no. 1 (February 2012): 174–83. http://dx.doi.org/10.1590/s0100-69162012000100018.

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This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

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Nakamura, Noboru, Mariko Senda, and Kiyoaki Ozaki. "Annual Report of the Monitoring Avian Productivity and Survivorship (MAPS) Program in Fukushima, Japan (2017)." Journal of the Yamashina Institute for Ornithology 49, no. 2 (February 28, 2018): 97–108. http://dx.doi.org/10.3312/jyio.49.97.

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Latta, Gregory, Hailemariam Temesgen, and Tara M. Barrett. "Mapping and imputing potential productivity of Pacific Northwest forests using climate variables." Canadian Journal of Forest Research 39, no. 6 (June 2009): 1197–207. http://dx.doi.org/10.1139/x09-046.

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Regional estimation of potential forest productivity is important to diverse applications, including biofuels supply, carbon sequestration, and projections of forest growth. Using PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate and productivity data measured on a grid of 3356 Forest Inventory and Analysis plots in Oregon and Washington, we evaluated four possible imputation methods to estimate potential forest productivity: nearest neighbour, multiple linear regression, thin plate spline functions, and a spatial autoregressive model. Productivity, measured by potential mean annual increment at culmination, is explained by the interaction of annual temperature, precipitation, and climate moisture index. The data were randomly divided into 2237 reference plots and 1119 target plots 30 times. Each imputation method was evaluated by calculating the coefficient of determination, bias, and root mean square error of both the target and reference data set and was also tested for evidence of spatial autocorrelation. Potential forest productivity maps of culmination potential mean annual increment were produced for all Oregon and Washington timberland.

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Dhakal, Bhola Nath. "Reciprocity between agricultural management and productivity in Nawalparasi district." Geographical Journal of Nepal 12 (April 1, 2019): 119–34. http://dx.doi.org/10.3126/gjn.v12i1.23419.

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Farm management is the making, organizing and operating a farm through the appropriate and timely inputs for maximum production and profit. This paper seeks to explore farm land management practices in-terms of input use in three different sites: Jahada, Palhi and Ramnagar of Nawalparasi district. The paper is based on collected primary data through household questionnaire survey, Focus Group Discussion (FGD), Key Informant Interview (KII) and field observation methods. Secondary sources of data through topographic and cadastral maps have also been used in this study. Use of different types of labour force, increasing the input use of manure, chemical fertilizers and pesticides, use of modern machineries, development of irrigation facilities, land intensification and crop diversification are the major strategies for agricultural development adopted by local peoples in the study sites.

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Vignolles, Cécile, Rainer Sauerborn, Peter Dambach, Christian Viel, Jean-Michel Soubeyroux, Ali Sié, Christophe Rogier, and Yves M. Tourre. "RE-EMERGING MALARIA VECTORS IN RURAL SAHEL (NOUNA, BURKINA FASO): THE PALUCLIM PROJECT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 2016): 237–42. http://dx.doi.org/10.5194/isprsarchives-xli-b8-237-2016.

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The Paluclim project applied the tele-epidemiology approach, linking climate, environment and public health (CNES, 2008), to rural malaria in Nouna (Burkina Faso). It was to analyze the climate impact on vectorial risks, and its consequences on entomological risks forecast. The objectives were to: 1) produce entomological risks maps in the Nouna region, 2) produce dynamic maps on larvae sites and their productivity, 3) study the climate impact on malaria risks, and 4) evaluate the feasibility of strategic larviciding approach.

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Vignolles, Cécile, Rainer Sauerborn, Peter Dambach, Christian Viel, Jean-Michel Soubeyroux, Ali Sié, Christophe Rogier, and Yves M. Tourre. "RE-EMERGING MALARIA VECTORS IN RURAL SAHEL (NOUNA, BURKINA FASO): THE PALUCLIM PROJECT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 2016): 237–42. http://dx.doi.org/10.5194/isprs-archives-xli-b8-237-2016.

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The Paluclim project applied the tele-epidemiology approach, linking climate, environment and public health (CNES, 2008), to rural malaria in Nouna (Burkina Faso). It was to analyze the climate impact on vectorial risks, and its consequences on entomological risks forecast. The objectives were to: 1) produce entomological risks maps in the Nouna region, 2) produce dynamic maps on larvae sites and their productivity, 3) study the climate impact on malaria risks, and 4) evaluate the feasibility of strategic larviciding approach.

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Teich, Ingrid, Mariano Gonzalez Roglich, María Laura Corso, and César Luis García. "Combining Earth Observations, Cloud Computing, and Expert Knowledge to Inform National Level Degradation Assessments in Support of the 2030 Development Agenda." Remote Sensing 11, no. 24 (December 6, 2019): 2918. http://dx.doi.org/10.3390/rs11242918.

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Monitoring progress towards the 2030 Development Agenda requires the combination of traditional and new data sources in innovative workflows to maximize the generation of relevant information. We present the results of a participatory and data-driven land degradation assessment process at a national scale, which includes use of earth observation (EO) data, cloud computing, and expert knowledge for Argentina. Six different primary productivity trend maps were produced from a time series of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset (2000–2018), including the most widely used trajectory approach and five alternative methods, which include information on the timing and magnitude of the changes. To identify the land productivity trend map which best represented ground conditions, an online application was developed, allowing 190 experts to choose the most representative result for their region of expertise nationwide. Additionally, the ability to detect decreases in land productivity of each method was assessed in 43,614 plots where deforestation had been recorded. The widely used trajectory indicator was the one selected by most experts as better reflecting changes in land condition. When comparing indicators’ performance to identify deforestation-driven reductions in productivity, the Step-Wise Approach Trend Index (SWATI), which integrates short- and long-term trends, was the one which performed the best. On average, decreases of land productivity indicate that 20% of the Argentine territory has experienced degradation processes between 2000 and 2018. The participatory data generation and verification workflow developed and tested here represents an innovative low cost, simple, and fast way to validate maps of vegetation trends and other EO-derived indicators, supporting the monitoring of progress towards land degradation neutrality by 2030.

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Clarke, Jared B., and Bob Ewart. "New ‘Monitoring Avian Productivity and Survival’ (Maps) Station Established in Wascana Centre, Regina, Saskatchewan, Summer 2010." Blue Jay 68, no. 4 (December 25, 2010): 174–78. http://dx.doi.org/10.29173/bluejay317.

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Senda, Mariko, Noboru Nakamura, and Kiyoaki Ozaki. "Annual Report of the Monitoring Avian Productivity and Survivorship (MAPS) Program in Fukushima, Japan (2012–2015)." Journal of the Yamashina Institute for Ornithology 47, no. 2 (March 20, 2016): 140–55. http://dx.doi.org/10.3312/jyio.47.140.

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Senda, Mariko, Noboru Nakamura, and Kiyoaki Ozaki. "Annual Report of the Monitoring Avian Productivity and Survivorship (MAPS) Program in Fukushima, Japan (2012–2016)." Journal of the Yamashina Institute for Ornithology 48, no. 2 (March 20, 2017): 117–29. http://dx.doi.org/10.3312/jyio.48.117.

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Kimball, J. S., A. R. Keyser, S. W. Running, and S. S. Saatchi. "Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps." Tree Physiology 20, no. 11 (June 1, 2000): 761–75. http://dx.doi.org/10.1093/treephys/20.11.761.

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Kazerooni, Matin, Phuong Nguyen, and Aminah Robinson Fayek. "Prioritizing Construction Labor Productivity Improvement Strategies Using Fuzzy Multi-Criteria Decision Making and Fuzzy Cognitive Maps." Algorithms 14, no. 9 (August 24, 2021): 254. http://dx.doi.org/10.3390/a14090254.

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Construction labor productivity (CLP) is affected by various interconnected factors, such as crew motivation and working conditions. Improved CLP can benefit a construction project in many ways, such as a shortened project life cycle and lowering project cost. However, budget, time, and resource restrictions force companies to select and implement only a limited number of CLP improvement strategies. Therefore, a research gap exists regarding methods for supporting the selection of CLP improvement strategies for a given project by quantifying the impact of strategies on CLP with respect to interrelationships among CLP factors. This paper proposes a decision support model that integrates fuzzy multi-criteria decision making with fuzzy cognitive maps to prioritize CLP improvement strategies based on their impact on CLP, causal relationships among CLP factors, and project characteristics. The proposed model was applied to determine CLP improvement strategies for concrete-pouring activities in building projects as an illustrative example. This study contributes to the body of knowledge by providing a systematic approach for selecting appropriate CLP improvement strategies based on interrelationships among the factors affecting CLP and the impact of such strategies on CLP. The results are expected to support construction practitioners with identifying effective improvement strategies to enhance CLP in their projects.

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Hammes, Ursula, Ray Eastwood, Guin McDaid, Emilian Vankov, S. Amin Gherabati, Katie Smye, James Shultz, Eric Potter, Svetlana Ikonnikova, and Scott Tinker. "Regional assessment of the Eagle Ford Group of South Texas, USA: Insights from lithology, pore volume, water saturation, organic richness, and productivity correlations." Interpretation 4, no. 1 (February 1, 2016): SC125—SC150. http://dx.doi.org/10.1190/int-2015-0099.1.

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A comprehensive regional investigation of the Eagle Ford Shale linking productivity to porosity-thickness (PHIH), lithology ([Formula: see text]), pore volume (PHIT), organic matter (TOC), and water-saturation ([Formula: see text]) variations has not been presented to date. Therefore, isopach maps across the Eagle Ford Shale play west of the San Marcos Arch were constructed using thickness and log-calculated attributes such as TOC, [Formula: see text], [Formula: see text], and porosity to identify sweet spots and spatial distribution of these geologic characteristics that influence productivity in shale plays. The Upper Cretaceous Eagle Ford Shale in South Texas is an organic-rich, calcareous mudrock deposited during a second-order transgression of global sea level on a carbonate-dominated shelf updip from the older Sligo and Edwards (Stuart City) reef margins. Lithology and organic-matter deposition were controlled by fluvial input from the Woodbine delta in the northeast, upwelling along the Cretaceous shelf edge, and volcanic and clastic input from distant Laramide events to the north and west. Local oxygen minimum events along the South Texas margin contributed to the preservation of this organic-rich source rock related to the Cenomanian/Turonian global organic anoxic event (OAE2). Paleogeographic and deep-seated tectonic elements controlled the variations of lithology, amount and distribution of organic matter, and facies that have a profound impact on production quality. Petrophysical modeling was conducted to calculate total organic carbon, water saturation, lithology, and porosity of the Eagle Ford Group. Thickness maps, as well as PHIH maps, show multiple sweet spots across the study area. Components of the database were used as variables in kriging, and multivariate statistical analyses evaluated the impact of these variables on productivity. For example, TOC and clay volume ([Formula: see text]) show an inverse relationship that is related to production. Mapping petrophysical parameters across a play serves as a tool to predict geologic drivers of productivity across the Eagle Ford taking the geologic heterogeneity into account.

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Hemingway, Halli, and Mark Kimsey. "Estimating Forest Productivity Using Site Characteristics, Multipoint Measures, and a Nonparametric Approach." Forest Science 66, no. 6 (August 15, 2020): 645–52. http://dx.doi.org/10.1093/forsci/fxaa023.

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Abstract Understanding the productivity of forestland is essential in sustainable management of forest ecosystems. The most common measure of site productivity is breast height–age site index (BHASI). BHASI has limitations as a productivity measure and can compound error in predictive models. We explored the accuracy of productivity predictions using an alternative productivity measure (10-meter site index) and a nonparametric approach. An orthogonal sampling design ensured samples were collected across the range of conditions known to influence Douglas-fir (Pseudotsuga menziesii var. glauca) height-growth rates. Using climate, soil, and topographic data along with 10-meter site index measurements, we compared five possible models to estimate forest productivity. Model parameters, performance, and predictions were compared. Twelve validation sites were used to test the accuracy of model predictions. Model performance was significantly improved when smoothing span values were optimized and elevation was added as a predictor. A four-predictor nonparametric model with a bias-corrected Akaike information criterion–optimized smoothing span value produced the most accurate results and was used to produce forest productivity maps for the study area. The low resolution of currently available climatic data and the complex nature of the study area landscape necessitate a topographic variable for accurate productivity predictions. Study Implications Defining and understanding forest productivity is of interest to a wide variety of natural resource professionals including ecologists, climate change experts, forest biometricians, and forest managers. A new method of defining forest productivity using multipoint height-age pairs at 10 and 20 meters and calculated growth rates combined with an appropriate landscape-scale stratification and a nonparametric approach provides accurate productivity estimates. This method is more widely applicable and more precise for specific locations than previous productivity estimation methods. Better productivity and tree growth information will provide more accurate estimates of future forest condition and structure.

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Panidi, E., V. Tsepelev, N. Torlopova, and A. Bobkov. "MAPPING OF THE LAND COVER SPATIOTEMPORAL CHARACTERISTICS IN NORTHERN RUSSIA CAUSED BY CLIMATE CHANGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 997–1002. http://dx.doi.org/10.5194/isprsarchives-xli-b8-997-2016.

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The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. <br><br> On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.

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Panidi, E., V. Tsepelev, N. Torlopova, and A. Bobkov. "MAPPING OF THE LAND COVER SPATIOTEMPORAL CHARACTERISTICS IN NORTHERN RUSSIA CAUSED BY CLIMATE CHANGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 997–1002. http://dx.doi.org/10.5194/isprs-archives-xli-b8-997-2016.

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The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. <br><br> On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.

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Kiseleva, Nadezda. "Principles and methods of developing a map “Geographical patterns of natural regeneration and forest stand productivity”." InterCarto. InterGIS 26, no. 4 (2020): 73–89. http://dx.doi.org/10.35595/2414-9179-2020-4-26-73-89.

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A special series of small-scale maps (approximate scale 1 : 7 500 000–1 : 8 000 000) is necessary for more effective forestry management in Russia and ensuring the stable functioning of this sector of the economy to create. These maps should give a holistic spatial representation of the object of forestry activity, they will allow to give a realistic assessment of the forest resource potential of the country. One of the maps in the series is “Geographical patterns of natural regeneration and forest stand productivity”. The basic principles of the map constructing are: general geographical patterns of main forest-forming species natural regeneration on clearings and general geographical patterns of productivity of the stand of all forest-forming species (in bonitet); the idea of V.V. Dokuchaev about the similarity of altitudinal mountain zonation to natural zones and subzones of plains. Zonal, subzonal, and altitudinal-zonal natural complexes, the formation of which is determined by the climate, serve as units of mapping. The methodology for constructing the map was verified using the example of the thermal conditions of forest growth in Central Siberia. Four indicators from 147 weather stations were used for this (calculated for the period from 1881 to 1980). Three indicators — the average monthly air temperatures in January and July and the average annual air temperature give a general idea of the thermal conditions of forest growth in Central Siberia. The sum of the average daily air temperatures above 10°C, which is the fourth indicator, characterizes the period of the most active vegetation of tree species. These indicators are summarized in a table constructed on the basis of the similarity of altitudinal zonation of natural complexes to zonal and subzonal. The article presents construction methodology, a fragment and the map legend.

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Garner, Jon, Alan L. Porter, Andreas Leidolf, and Michelle Baker. "Measuring and Visualizing Research Collaboration and Productivity." Journal of Data and Information Science 3, no. 1 (March 13, 2018): 54–81. http://dx.doi.org/10.2478/jdis-2018-0004.

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Abstract Purpose This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns. Design/methodology/approach We compile publications by 45 researchers in each of 1) the iUTAH project, which we consider here to be analogous to a “research center,” 2) CG1— a comparison group of participants in two other Utah environmental research centers, and 3) CG2—a comparison group of Utah university environmental researchers not associated with a research center. We draw bibliometric data from Web of Science and from Google Scholar. We gather publications for a period before iUTAH had been established (2010–2012) and a period after (2014–2016). We compare these research outputs in terms of publications and citations thereto. We also measure interdisciplinarity using Integration scoring and generate science overlay maps to locate the research publications across disciplines. Findings We find that participation in the iUTAH project appears to increase research outputs (publications in the After period) and increase research citation rates relative to the comparison group researchers (although CG1 research remains most cited, as it was in the Before period). Most notably, participation in iUTAH markedly increases co-authoring among researchers—in general; and for junior, as well as senior, faculty; for men and women: across organizations; and across disciplines. Research limitations The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls. Practical implications This study demonstrates a viable approach for research assessment of a center or program for which random assignment of control groups is not possible. It illustrates use of bibliometric indicators to inform R&D program management. Originality/value New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohorts.

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Triyatmo, Bambang. "KAJIAN MORFOMETRI BERDASARKAN TOPOGRAFI DAN POTENSI PERIKANAN WADUK SERMO." Jurnal Perikanan Universitas Gadjah Mada 3, no. 1 (January 26, 2001): 27. http://dx.doi.org/10.22146/jfs.8867.

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The objectives of this studies was to know morphometric characteristics, primary productivity of water, and the fisheries potency of Sermo reservoir. Topography and fisheries potency were estimated based on a morphometrical study of Sermo reservoir after inundation. The study was conducted on the topographical maps with 1 : 12,500 scale and 10 m contour intervals. The primary productivity of Sermo reservoir after inundation was observed.The results showed that Sermo reservoir had an optimal level 136.6 m msl with a total water area 157 ha, water volume 25 millions m3, length of shore line 16,3 km and shore line development index 3,67. The primary productivity of water ranged from 2.2 to 178.7 mg C/m3/h. Potential area for fish culture using floating net cage was 1.5 ha with total production around 300 ton/year. The potency for endogenous and introduction fish production in the Sermo reservoir was approximately 5-10 ton/year.

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Condro, Aryo Adhi, Yudi Setiawan, Lilik Budi Prasetyo, Rahmat Pramulya, and Lasriama Siahaan. "Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform." Land 9, no. 10 (October 8, 2020): 377. http://dx.doi.org/10.3390/land9100377.

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Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the main commodities in Indonesia using spatially-explicit tools is essential to understand the precise productivity derived from the agricultural sectors. Many previous studies have used predictions developed using binary maps of general crop cover. Here, we present national commodity maps for Indonesia based on remote sensing data using Google Earth Engine. We evaluated a machine learning algorithm—i.e., Random Forest to parameterize how the area in commodity varied in Indonesia. We used various predictors to estimate the productivity of various commodities based on multispectral satellite imageries (36 predictors) at 30-meters spatial resolution. The national commodity map has a relatively high accuracy, with an overall accuracy of about 95% and Kappa coefficient of about 0.90. The results suggest that the oil palm plantation was the highest commodity product that occupied the largest land of Indonesia. However, this study also showed that the land area in rubber, rice paddies, and cacao commodities was underestimated due to its lack of training samples. Improvement in training data collection for each commodity should be done to increase the accuracy of the commodity maps. The commodity data can be viewed online (website can be found in the end of conclusions). This data can further provide significant information related to the agricultural sectors to investigate food provisioning, particularly in Indonesia.

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Pinandito, Aryo, Didik Dwi Prasetya, Yusuke Hayashi, and Tsukasa Hirashima. "Semi-Automatic Concept Map Generation Approach of Web-Based Kit-Build Concept Map Authoring Tool." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 08 (April 23, 2021): 50. http://dx.doi.org/10.3991/ijim.v15i08.20489.

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Apart from contributing to students’ learning outcomes, learning activities with digital concept maps were useful, fun, and engaging. Kit-Build concept map is a learning framework that incorporated concept map recomposition as its essential activity. It has been used to learn English as a Foreign Language (EFL) reading comprehension. Students learn through recomposing digital concept maps from a set of teacher’s concept map components; hence, the teacher’s concept map is essential in Kit-Build. A teacher’s concept map should reflect the learning context and strategy, the teacher’s purpose and intention, students’ understanding level, and focus questions. However, automatic-generated concept maps with Concept Map Mining (CMM) can only produce general concept maps that are not fit and difficult to correspond to said reasons. As teacher’s concept maps are essential in learning with Kit-Build, improving teachers’ productivity in composing concept maps of a particular learning material becomes necessary. This study proposed a semi-automatic concept map generation approach of EFL reading comprehension texts with CMM to assist teachers composed their concept maps. The proposed concept map generation approach was integrated into the current Kit-Build concept map authoring tool as an authoring support feature. The accuracy of the support feature in generating concept map components is presented in this research. The result suggested that the proposed authoring support tool is better used to refine a concept map.

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Moursy, Ali, Abdelgalil A, Ibrahim M.S, Abdelhady A.A, and Mustafa A.A. "Actual and Potential Land Productivity of Some Soils of Sohag-Red Sea Road Sides, Eastern Desert, Egypt." International Journal of Agricultural and Applied Sciences 1, no. 1 (June 30, 2020): 68–74. http://dx.doi.org/10.52804/ijaas2020.1114.

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Egyptian Government focuses on development projects especially in new lands such as Sohag-Red Sea road to improve tourism and agricultural activities. This study aims to assess the actual and potential land productivity. Seventeen soil profiles were chosen depending on the six mapping units of the study area. Soil profiles were drilled and soil samples were collected from each horizon. Nine land characteristics were measured/estimated viz. soil moisture content (H), drainage (D), depth (P), texture (T), soluble salts content (S), average nutrient content (N), organic matter content (O), cationic exchange capacity (A) and reserves weatherable minerals (M). Soil samples were analyzed for their mentioned parameters using the standard methods of soil analysis. Accordingly, land productivity (PI) and potentiality (P⸌I) indices were calculated for all studied soil profiles. The results revealed that actual land productivity of the studied area is extremely poor and can be enhanced 17 times by improving soil moisture content, texture, and organic matter content as the most important controlling-factors. Actual and potential land productivity maps were generated using Arc GIS 10.1 software. These results may help decision-makers for new lands reclamation planning and better agricultural production.

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Guo, Baozhu, Manish K. Pandey, Guohao He, Xinyou Zhang, Boshou Liao, Albert Culbreath, Rajeev K. Varshney, Victor Nwosu, Richard F. Wilson, and H. Thomas Stalker. "Recent Advances in Molecular Genetic Linkage Maps of Cultivated Peanut." Peanut Science 40, no. 2 (July 1, 2013): 95–106. http://dx.doi.org/10.3146/ps13-03.1.

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ABSTRACT The competitiveness of peanuts in domestic and global markets has been threatened by losses in productivity and quality that are attributed to diseases, pests, environmental stresses and allergy or food safety issues. Narrow genetic diversity and a deficiency of polymorphic DNA markers severely hindered construction of dense genetic maps and quantitative trait loci (QTL) mapping in order to deploy linked markers in marker-assisted peanut improvement. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to a global effort in 2006 to address these issues through coordination of international efforts in genome research beginning with molecular marker development and improvement of map resolution and coverage. Ultimately, a peanut genome sequencing project was launched in 2012 by the Peanut Genome Consortium (PGC). We reviewed the progress for accelerated development of peanut genomic resources in peanut, such as generation of expressed sequenced tags (ESTs) (252,832 ESTs as December 2012 in the public NCBI EST database), development of molecular markers (over 15,518 SSRs), and construction of peanut genetic linkage maps, in particular for cultivated peanut. Several consensus genetic maps have been constructed, and there are examples of recent international efforts to develop high density maps. An international reference consensus genetic map was developed recently with 897 marker loci based on 11 published mapping populations. Furthermore, a high-density integrated consensus map of cultivated peanut and wild diploid relatives also has been developed, which was enriched further with 3693 marker loci on a single map by adding information from five new genetic mapping populations to the published reference consensus map.

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Watt, Michael S., David J. Palmer, Mark O. Kimberley, Barbara K. Höck, Tim W. Payn, and David J. Lowe. "Development of models to predict Pinus radiata productivity throughout New Zealand." Canadian Journal of Forest Research 40, no. 3 (March 2010): 488–99. http://dx.doi.org/10.1139/x09-207.

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Development of spatial surfaces describing variation in productivity across broad landscapes at a fine resolution would be of considerable use to forest managers as decision support tools to optimize productivity. In New Zealand, the two most widely used indices to quantify productivity of Pinus radiata D. Don are Site Index and 300 Index. Using an extensive national data set comprising a comprehensive set of national extent maps, multiple regression models and spatial surfaces of these indices for P. radiata were constructed. The final models accounted for 64% and 53%, respectively, of the variance in Site Index and 300 Index. For Site Index, variables included in the final model in order of importance were mean annual air temperature, fractional mean annual available root-zone water storage, mean annual windspeed, length and slope factor, categories describing Land Environments of New Zealand (LENZ), and major soil parent material. The variables included in the final model of 300 Index in order of importance included the degree of ground frost during autumn, fractional mean annual available root-zone water storage, categories describing LENZ, vegetation classification, foliar nitrogen, taxonomic soil order, and major soil parent material. These results highlight the utility of thematic spatial layers as driving variables in the development of productivity models.

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Vu, Quyet Manh, Venkat Lakshmi, and John Bolten. "Assessment of the Biomass Productivity Decline in the Lower Mekong Basin." Remote Sensing 11, no. 23 (November 26, 2019): 2796. http://dx.doi.org/10.3390/rs11232796.

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This study aimed to delineate the geographic hotspots of negative trends in biomass productivity in the Lower Mekong Basin countries (Vietnam, Cambodia, Laos, and Thailand) and identify correlated regional environmental and anthropogenic factors. A long-term time-series (1982–2015) of Normalized Difference Vegetation Index at a resolution of approximately 9.16 km × 9.16 km was used to specify the areas with significant decline or increase in productivity. The relationships between vegetation changes and land attributes, such as climate, population density, soil/terrain conditions, and land-cover types, were examined. Rainfall time-series maps were used to identify areas that might have been affected by land degradation from those correlated with rainfall. Most of the detected potentially degraded areas were found in Cambodia, the Northwest and the Highland of Vietnam, the Northern Mountains of Thailand and Laos, and the mountainous border between Laos, Vietnam, and Cambodia. About 15% of the total land area of these four countries experienced a reduction in biomass productivity during the 34-year study period. The map of hotspots of changes in productivity can be used to direct further studies, including those at finer spatial resolution that may support policy makers and researchers in targeting the strategies for combating land degradation.

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Gaudėšius, Rimvydas. "DRAWING UP MAPS OF INFERTILE SOIL PLOTS USING GEOGRAPHIC INFORMATION SYSTEMS." Geodesy and cartography 42, no. 4 (December 20, 2016): 140–45. http://dx.doi.org/10.3846/20296991.2016.1268437.

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There are quite a lot of unused plots of lands that are suitable for agriculture or other business in the territory of Lithuania. This has happened because of various social, natural and economic reasons. Scientists emphasize that all intensity of agricultural production is determined by different conditions of development of agricultural activities. Productivity of soil is highly significant in this case. Big farmers control vast territories in which natural conditions are different. Some farmers engage in one type of activities in their farms, whereas others develop different business. Using the territory used for agriculture to engage in different activities is more efficient economically because different crops need different conditions to grow; therefore, it is possible to obtain higher economic efficiency taking into account the characteristics of soil. Taking into account the relevance of such a map in practice, it was decided to try to draw it up using geographic information systems. The biggest problem while performing this task is the fact that initial information is saved in different formats. The article also describes the capacities of software. It is noteworthy that the situation is analyzed in respect of drawing up a map of individual holdings not a mass map of unproductive land. The article is more of practical nature; therefore, the results reflect program capacities and theoretical ideas more that could be useful in business and expand the capabilities of land management officers‘ activities.

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Marthews, T. R., C. A. Quesada, D. R. Galbraith, Y. Malhi, C. E. Mullins, M. G. Hodnett, and I. Dharssi. "High-resolution hydraulic parameter maps for surface soils in tropical South America." Geoscientific Model Development 7, no. 3 (May 6, 2014): 711–23. http://dx.doi.org/10.5194/gmd-7-711-2014.

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Abstract. Modern land surface model simulations capture soil profile water movement through the use of soil hydraulics sub-models, but good hydraulic parameterisations are often lacking, especially in the tropics. We present much-improved gridded data sets of hydraulic parameters for surface soil for the critical area of tropical South America, describing soil profile water movement across the region to 30 cm depth. Optimal hydraulic parameter values are given for the Brooks and Corey, Campbell, van Genuchten–Mualem and van Genuchten–Burdine soil hydraulic models, which are widely used hydraulic sub-models in land surface models. This has been possible through interpolating soil measurements from several sources through the SOTERLAC soil and terrain data base and using the most recent pedotransfer functions (PTFs) derived for South American soils. All soil parameter data layers are provided at 15 arcsec resolution and available for download, this being 20x higher resolution than the best comparable parameter maps available to date. Specific examples are given of the use of PTFs and the importance highlighted of using PTFs that have been locally parameterised and that are not just based on soil texture. We discuss current developments in soil hydraulic modelling and how high-resolution parameter maps such as these can improve the simulation of vegetation development and productivity in land surface models.

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Karim, Hawber A., and Diary A. Al-Manmi. "Integrating GIS-based and geophysical techniques for groundwater potential assessment in Halabja Said Sadiq sub-basin, Kurdistan, NE Iraq." Tikrit Journal of Pure Science 24, no. 6 (November 3, 2019): 81. http://dx.doi.org/10.25130/j.v24i6.891.

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Groundwater is an important resource in Halabja Said Sadiq sab-basin, Sulaymaniyah district for agricultural and other uses. Continuous dramatic extraction of groundwater from legal and illegal wells led to a severe decline in the water table for the last thirty years. The objectives of this study are to delineate the groundwater productivity zones by combining the geographic information system and geoelectrical survey, which serves to recognize the locations of good groundwater storage and recharge zones. The Halabja Said Sadiq sub-basin has been selected as a case study to delineate the groundwater productivity zones. Four geoelectrical resistivity profiles conducted with electrode spacing 10 m and the length of the profiles is equal to 710 m. Themes such as hydrogeology, land use/land cover, topography, drainage density, soil type, slope, lineaments and rainfall maps are created. The thematic maps made with GIS platform and appropriate weights put to the attributes taking into account the influence on the storage potential of groundwater. The results of geoelectrical profiles revealed that the aquifer thickness is 150 m. Three zones of groundwater potential delineated which are low, moderate and high and cover 33 %, 24 %, and 42 % of the total area respectively. Spatially, the highest zone is located along with the Quaternary deposits which characterized by high lineament density, low slop, and pediment deposition The output of the groundwater potential model is verified by testing the discharge rate of the existing 580 wells. The results are revealed that most of the high yield wells are located within the high groundwater potential zone. Results of such verifications proved that the groundwater productivity areas recognized by GIS (AHP) and geoelectrical techniques are dependable and practical. http://dx.doi.org/10.25130/tjps.24.2019.112

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Dosma Sitanggang, Marisa. "COMPARATIVE ANALYSIS OF MAN POWER, PRODUCTIVITY, AND OUTPUT IN THE SHORT AND LONG CONVEYOR CONVEYOR USING MICRO MOTION (CASE STUDY: PT.EDS MANUFACTURING INDONESIA)." Dinasti International Journal of Education Management And Social Science 1, no. 3 (February 11, 2020): 306–18. http://dx.doi.org/10.31933/dijemss.v1i3.148.

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The thesis is compiled to analyze the ratio of man power, productivity and output between short and long conveyor conveyor. In addition to analyzing the conveyor which is better to be applied in PT. EDS Manufacturing Indonesia by using micro motions. The analysis used by researchers working maps, motion studies and calculation of standard time obtained from the data retrieval researchers with methods of micro motion (use a stop watch).The sample in this study is that there are in the final process assy namely setting. From the results, it can be calculated that for man power has the addition of 58% from 7 to 12, to the output increase from be 51.17 units and poduktivitas takttime increased 9% from 4 units to 4.41 units and 20% productivity standard time of 3.35 units to 4.2 units.

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Ramdan, Ade, Vicky Zilvan, Endang Suryawati, Hilman F. Pardede, and Vitria Puspitasari Rahadi. "Tea clone classification using deep CNN with residual and densely connections." Jurnal Teknologi dan Sistem Komputer 8, no. 4 (October 13, 2020): 289–96. http://dx.doi.org/10.14710/jtsiskom.2020.13768.

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Tea clone of Gambung series is a superior variety of tea that has high productivity and quality. Smallholder farmers usually plant these clones in the same areas. However, each clone has different productivity or quality, so it is difficult to predict the production quality in the same area. To uniform the variety of clones in an area, smallholder farmers still need experts to identify each plant because one and other clones share the same visual characteristics. We propose a tea clone identification system using deep CNN with skip connection methods, i.e., residual connections and densely connections, to tackle this problem. Our study shows that the proposed method is affected by the hyperparameter setting and the combining feature maps method. For the combining method, the concatenation method on a densely connected network shows better performance than the summation method on a residual connected network.

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Romano, Elio, Simone Bergonzoli, Ivano Pecorella, Carlo Bisaglia, and Pasquale De Vita. "Methodology for the Definition of Durum Wheat Yield Homogeneous Zones by Using Satellite Spectral Indices." Remote Sensing 13, no. 11 (May 21, 2021): 2036. http://dx.doi.org/10.3390/rs13112036.

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One of the main questions facing precision agriculture is the evaluation of different algorithms for the delineation of homogeneous management zones. In the present study, a new approach based on the use of time series of satellite imagery, collected during two consecutive growing seasons, was proposed. Texture analysis performed using the Gray-Level Co-Occurrence Matrix (GLCM) was used to integrate and correct the sum of the vegetation indices maps (NDVI and MCARI2) and define the homogenous productivity zones on ten durum wheat fields in southern Italy. The homogenous zones identified through the method that integrates the GLCM indices with the spectral indices studied showed a greater accuracy (0.18–0.22 Mg ha−1 for ∑NDVIs + GLCM and 0.05–0.49 Mg ha−1 for ∑MCARI2s + GLCM) with respect to the methods that considered only the sum of the indices. Best results were also obtained with respect to the homogeneous zones derived by using yield maps of the previous year or vegetation indices acquired in a single day. Therefore, the survey methods based on the data collected over the entire study period provided the best results in terms of estimated yield; the addition of clustering analysis performed with the GLCM method allowed to further improve the accuracy of the estimate and better define homogeneous productivity zones of durum wheat fields.

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Journal articles on the topic 'Productivity maps'

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