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Journal articles on the topic 'Land cover'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Azevedo, Thiago, and Lindon Fonseca Matias. "Urban Land Use and Land Cover Mapping." Agua y Territorio / Water and Landscape, no. 23 (September 7, 2023): e7251. http://dx.doi.org/10.17561/at.23.7251.

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The Brazilian urbanization process produced a complex urban space, with a variety of urban land use and cover as a result. The study of these forms through a classification system is essential, but most current systems don’t capture this complexity, condensing it. Urban forms are difficult to distinguish and classify, resulting in the need for a system with a high degree of detail, for a more accurate urban planning. The objective of this work is to propose a classification system for urban land use and cover, which can demonstrate the multiplicities through remote sensing, using data from CBE

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Agone, Vikram, and Arvind Suryawanshi. "Assessing Land Use and Land Cover Changes in Waghur Basin: A Remote Sensing and Machine Learning Approach for Sustainable Land Management." JOURNAL OF RESEARCH AND DEVELOPMENT 15, no. 19 (2023): 5–15. https://doi.org/10.5281/zenodo.12570062.

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This research focuses on the importance of studying land use and land cover changes in densely populated countries, with a specific focus on the Waghur Basin in India. It emphasizes the significance of remote sensing techniques for detecting and analyzing these changes. The study uses remote sensing data and machine learning algorithms to classify and analyze land use and land cover patterns in the Waghur Basin from 1990 to 2022. The results reveal significant changes in land utilization, including an increase in agricultural land and a decrease in forest and bare land areas. These changes hav

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Strode, Georgianna, Victor Mesev, Benjamin Thornton, Marjorie Jerez, Thomas Tricarico, and Tyler McAlear. "Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams." Proceedings of the ICA 1 (May 16, 2018): 1–5. http://dx.doi.org/10.5194/ica-proc-1-106-2018.

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The terms ‘land use’ and ‘land cover’ typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cove

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Kumar, R. Shiva, and Afsana Tabassum. "Changes of Land Use Land Cover in Bandipur National Park." Geo-Eye 10, no. 1 (2021): 22–26. https://doi.org/10.53989/bu.ge.v10i1.4.

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This study mainly focusses on changes of land use land cover (LULC) in Bandipur National Park in 2001, 2011and 2019. Methodology have been used for LULC analysis, downloaded satellite imageries of Landsat 8 (OLI) for 2019, Landsat (ETM+) for 2001, and Landsat 4-5 (TM) for 2011. with the help of Geoinformatics tools clipped the area with 5 km buffer in context to our study area and processed it with supervised classification of water, dense forest, open forest, urban, agriculture, current fallow to get LULC map for the study area. In three decades, areawise changes noticed in LULC analysis reve

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Morales, Narkis S., and Ignacio C. Fernández. "Land-Cover Classification Using MaxEnt: Can We Trust in Model Quality Metrics for Estimating Classification Accuracy?" Entropy 22, no. 3 (2020): 342. http://dx.doi.org/10.3390/e22030342.

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MaxEnt is a popular maximum entropy-based algorithm originally developed for modelling species distribution, but increasingly used for land-cover classification. In this article, we used MaxEnt as a single-class land-cover classification and explored if recommended procedures for generating high-quality species distribution models also apply for generating high-accuracy land-cover classification. We used remote sensing imagery and randomly selected ground-true points for four types of land covers (built, grass, deciduous, evergreen) to generate 1980 classification maps using MaxEnt. We calcula

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Oliveira, J. C., R. A. C. Lamparelli, G. K. D. A. Figueiredo, et al. "PASTURE LAND COVER CHANGE IN SÃO PAULO STATE, BRAZIL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (November 6, 2020): 321–26. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-321-2020.

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Abstract. Pastures are complex land covers with a variety of land use systems. This land cover occupies large areas in the globe and is mainly used for livestock production. Brazil is one of the largest livestock producers and has extensive pasture areas. We analyzed the pasture land cover change of the São Paulo State between the years 2000 to 2015. São Paulo was chosen as study case due to its large industrial and agricultural importance and its expressive land cover changes over past decades. It was analyzed land covers databases generated by the Brazilian Annual Land Use and Land Cover Map

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Parsa, I. Made. "supabase Please extract the text as it is Here is the extracted text from the image: DENOSING OF HIGH RESOLUTION REMOTE SENSING DATA USING STATIONARY WAVELET TRANSFORM Danang Surya Candra Peneliti Bidang Jianta, Pusdata, LAPAN e-mail: thedananx@yahoo." Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital 10, no. 2 (2013): 113–21. https://doi.org/10.30536/inderaja.v10i2.3279.

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Land cover change, from bare land, water and to vegetation, or vice versa can be used as the basis for paddy fields mapping using the theory of probability, that is probability a land cover can be regarded as an paddy fields if a sequence of land cover changes of water, vegetation and bare land or vice versa on multitemporal images have been detected. The data being used were Landsat multitemporal imagery, while the methods being used in this analysis is the transformation of vegetation index and converted to land covers (bare land, water and vegetation). Detection of three types of land cover

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TOWNSHEND, J. R. G. "Land cover." International Journal of Remote Sensing 13, no. 6-7 (1992): 1319–28. http://dx.doi.org/10.1080/01431169208904193.

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9

Remlalruata. "STUDIES ON LAND USE AND LAND COVER CHANGE IN AIZAWL DISTRICT, MIZORAM." International Journal of Recent Research in Social Sciences and Humanities (IJRRSSH) 10, no. 2 (2023): 107–16. https://doi.org/10.5281/zenodo.8042670.

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<strong>Abstract:</strong> The Assessment of land use and land cover change is important for the development of a policy by the government. Land cover change is still a very interesting and hot topic in todays world even in Mizoram. For supporting decision-making processes, identifying LULCC and comprehending the underlying forces are crucial. We examined and analyze the changing variation of land use and land cover during the period of 2000 to 2020 using Three Landsat Thematic Mapper (TM) 4-5 C1 level-1 satellite imagery for 2000, 2010 and Landsat 8 OLI/TIRS C1 level-1 imagery for 2020. Accur

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Shumila, Petronillah Mutenyi, Mutavi Irene Nzisa, and Denis Mutama Masika. "Effects of Land Use Land Cover Changes on Vegetation Cover Types in Khwisero Sub County, Kakamega County, Kenya." Indiana Journal of Humanities and Social Sciences 5, no. 7 (2024): 11–28. https://doi.org/10.5281/zenodo.12740878.

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Land use land cover changes have to a great extent changed the world's landscapes rebuilding environments and what they provide to humans during the time spent supporting the rising population across the globe. However, the LULCCs affect land quality in terms of loss of vegetation cover types and altering soil quality to great extent. Misango Hills natural forest and other forms of vegetation cover types in Khwisero Sub County have been changed over completely to farming and built up regions. Cross sectional descriptive and longitudinal research designs were used. Purposive sampling was used t

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Anua, S. N., and W. V. C. Wong. "Utilizing Landsat 8 OLI for land cover classification in plantations area." IOP Conference Series: Earth and Environmental Science 1053, no. 1 (2022): 012027. http://dx.doi.org/10.1088/1755-1315/1053/1/012027.

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Abstract Identifying the land cover in plantations is crucial to assist the management of an area. Today, land cover classification can be achieved using free satellite data. The objective of this study is to perform a supervised classification using LANDSAT 8 OLI to differentiate the land cover in Brumas Camp which consists of non-vegetation, oil palm, forest, and forest plantations. The overall accuracy and Kappa’s coefficients were 71.64% and 0.62, respectively. We found out that the accuracy of classification for non-vegetation is relatively higher compared to vegetation land cover types.

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Comber, A. J. "Land use or land cover?" Journal of Land Use Science 3, no. 4 (2008): 199–201. http://dx.doi.org/10.1080/17474230802465140.

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13

Isola, Federica, Sabrina Lai, Federica Leone, and Corrado Zoppi. "Land Take and Landslide Hazard: Spatial Assessment and Policy Implications from a Study Concerning Sardinia." Land 12, no. 2 (2023): 359. http://dx.doi.org/10.3390/land12020359.

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Land take and soil sealing imply land cover transitions that may possibly result in decreased capacity to resist landslides; hence, this study focuses on the relations between land-taking processes and landslide hazard by addressing the following research question: “To what extent do land-taking processes increase landslide hazard?” The impact of land take is assessed through a regression model which relates the level of landslide hazard to a set of land cover variables which include artificialized land; that is, land taken up through urbanization processes, and a set of covariates that repres

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Sheikh, Iqbal. "Comparative analysis of soil organic carbon storage under different land use and land cover in Achanakmar, Chhattisgarh." Journal of Biodiversity and Environmental Sciences (JBES) 10, no. 1 (2017): 11–19. https://doi.org/10.5281/zenodo.2588180.

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In context to the India’s climate pledge and the goal of limiting global warming below 2C to reduce the emissions intensity of its GDP by 33 to 35 percent by 2030 from 2005 level and to create an additional carbon sink of 2.5 to 3 billion tons of CO2 equivalent through additional forest and tree cover by 2030. Forest vegetation and forest soils represent a significant sink for atmospheric CO2, soil biota functioning, reduction of greenhouse gases, modification of pollutants and maintenance of soil quality. The great importance of carbon sequestration emphasizes the need to understand th

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Kumar, Ranjeet. "Rathod, V. N. (2025). Freshwater Diatoms of Waghur Dam Jalgaon, Maharashtra. Journal of Research & Development, 17(4), 102–110. https://doi.org/10.5281/zenodo.15544137." Journal of Research & Development 17, no. 4 (2025): 111–15. https://doi.org/10.5281/zenodo.15544188.

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<strong><em>Abstract</em></strong>                 <em>Land use and land cover are two important components to understand the global land status; they shows present as well as past status of the earth surface. Land use and land cover are two separate terminologies which are often used interchangeably (Dimyati et al 1994). Land cover is a basic parameter which evaluates the content of earth surface as an important factor that affects the condition and functioning of the ecosystem. Land cover is a biophysical state of the

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Kumar, Ranjeet. "Land Use Pattern in Gaya District, Bihar: A Geographical and Environmental Analyse." Journal of Research & Development 17, no. 4 (2025): 111–15. https://doi.org/10.5281/zenodo.15544206.

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<strong><em>Abstract</em></strong>                 <em>Land use and land cover are two important components to understand the global land status; they shows present as well as past status of the earth surface. Land use and land cover are two separate terminologies which are often used interchangeably (Dimyati et al 1994). Land cover is a basic parameter which evaluates the content of earth surface as an important factor that affects the condition and functioning of the ecosystem. Land cover is a biophysical state of the

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17

Mahesh, R., R. Neelakantan, R. Anbalagan, P. Parthiban, and A. Das. "Spatio-Temporal Assessment of Land use / Land cover using Normalized Difference Vegetation Index (NDVI) of Satellite Imageries and its relationship with Landslide-prone Zones in Kodaikanal Hill Station of Tamil Nadu, India." Disaster Advances 15, no. 10 (2022): 35–41. http://dx.doi.org/10.25303/1510da035041.

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The land use exercises at last influence the land cover briefly as well as spatially. The primary consideration liable for the adjustment in land cover is to satisfy the developing requests of expanding populace through horticultural increase for nourishment and clearing of typical land covers like the forests and sparsely inhabited regions for settlement and business activities. The adjustment in land cover additionally upsets the other characteristic parts like soil ripeness, soil disintegration, environment, biodiversity, air quality and water system of the upset area. Remote sensing and GI

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Svenningsen, Cecilie S., Birte Peters, Diana E. Bowler, Robert R. Dunn, Aletta Bonn, and Anders P. Tøttrup. "Insect biomass shows a stronger decrease than species richness along urban gradients." Insect Conservation and Diversity 17, no. 2 (2024): 182–88. http://dx.doi.org/10.1111/icad.12694.

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Abstract Anthropogenic land cover change is a major driver of biodiversity loss, with urbanisation and farmland practices responsible for some of the most drastic modifications of natural habitats. The relative importance of different land covers for shaping insect communities, however, is unclear. This study examines the effect of urban and farmland covers, along with land cover heterogeneity, at a landscape scale on species richness, evenness and biomass of flying insects using citizen science carnet sampling across Denmark. Increasing urban cover had a negative effect on insect richness but

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19

Sewnet, Amare. "Land Use/Cover Change at Infraz Watershed, Northwestren Ethiopia." Journal of Landscape Ecology 8, no. 1 (2015): 69–83. http://dx.doi.org/10.1515/jlecol-2015-0005.

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Abstract Land cover is the physical and biological cover of the surface whereas land use covers the results of human activities for the exploitation of it. The land cover and landuse change is caused by both, natural and anthropogenic factors. The objective of this study was to detect land cover/use changes in Infraz Watershed. The study has used ArcGIS10 and ERDAS IMAGINE10, landsat images of 1973, 1986, 1995 and 2011 and socio-economic data to analyze land cover and landuse changes of Infraz watershed. The study has found that due to the population increase and improper agricultural activity

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Samsuri, A. Zaitunah, AG Ahmad, and I. Pasaribu. "Lands Cover Dynamics of Siais Lake Catchment Area, Tapanuli Selatan District, Indonesia." IOP Conference Series: Earth and Environmental Science 1116, no. 1 (2022): 012084. http://dx.doi.org/10.1088/1755-1315/1116/1/012084.

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Abstract The Siais Lake Catchment Area (SLCA) is a water resource that includes various types of land cover and land use in Rianiate village, Angkola Sangkunur sub-district, and Tapanuli Selatan district. The SLCA lake catchment area has altered the land cover and increased the surface area of Siais Lake. The purpose of this study was to determine the type of land cover that changed in the Siais lake catchment area between 1990 and 2018. The land cover classification was obtained using Landsat 5 and Landsat 8 OLI images. Make use of supervised classification. Forest, plantation, bare land, pad

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Zhu, Linye, Mingming Shi, Deqin Fan, Kun Tu, and Wenbin Sun. "Analysis of Changes in Vegetation Carbon Storage and Net Primary Productivity as Influenced by Land-Cover Change in Inner Mongolia, China." Sustainability 15, no. 6 (2023): 4735. http://dx.doi.org/10.3390/su15064735.

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Exploring the influence of vegetation carbon stocks over land-cover change and the relationship between land-cover change and net primary production (NPP) is of great practical importance for achieving China’s carbon neutrality target. Therefore, this paper analyses the spatio-temporal distribution of land-cover change and NPP change in Inner Mongolia from 2000 to 2020 and explores the vegetation carbon stock change caused by land-cover change, the relationship between land cover and NPP, and the relationship between land-cover change and NPP change. The results show that the main land-cover c

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Nganro, Sudirman, Slamet Trisutomo, Roland Barkey, et al. "Prediction of Future Land Use and Land Cover (LULC) in Makassar City." TATALOKA 23, no. 2 (2021): 183–89. http://dx.doi.org/10.14710/tataloka.23.2.183-189.

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Migration from rural area to urban area increases urban population. It increases and needs for settlements, leading to conversion of agricultural lands into settlement areas. Inconsistent land use compared with spatial planning causes change in land use. Spatial land use expansion can be monitored and predicted by modeling. NetLogo application is a software integrated with Agent-Based Modeling (ABM), which can be used to predict change of land use with various complex parameters. The present study used population growth as a parameter to predict change of land use of Makassar in 2050 based on

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Shyamala, R., and E. Hemavathy. "Land Use and Land Cover Change Detection in Sriperumbudur Taluk, Kanchipuram District." International Journal of Scientific Engineering and Research 6, no. 11 (2018): 35–39. https://doi.org/10.70729/ijser18383.

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Sushmitha, S., and B. Chandrashekara. "A Geospatial Assessment of Land Use Land Cover Changes in Mysuru Taluk." Geo-Eye 12, no. 1 (2023): 41–45. https://doi.org/10.53989/bu.ge.v12i1.6.

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The research places its emphasis on comprehending the intricacies and fluctuations in the utilization and coverage of land in Mysuru Taluk, a locale nestled in the southern reaches of India. The study uses Sentinel-2 multitemporal satellite data from the Esri to examine land dynamics in Mysuru Taluk between 2017 and 2022, employing ArcMap software for mapping and statistical techniques for quantifying variations in land cover categories such as built-up areas, agricultural land, and water bodies. The investigation endeavors to pinpoint the catalysts that have influenced the transformation of l

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Šetka, Josip, Petra Radeljak Kaufmann, and Luka Valožić. "Modelling land use and land cover changes in the Lower Neretva Region." Hrvatski geografski glasnik/Croatian Geographical Bulletin 85, no. 1 (2023): 41–63. http://dx.doi.org/10.21861/hgg.2023.85.01.02.

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It has been shown that simulation models are reliable tools for predicting land changes, which contributes to better understanding and management of human impact on the environment. Land use and land cover changes in the Lower Neretva Region between 1990 and 2035 have been analysed and modelled in this study. The final simulation model of future changes was created based on cellular automata and artificial neural networks, implemented in the MOLUSCE plugin for QGIS. In addition, a test simulation model for 2020 was created, which showed high accuracy. Input variables for the final simulation m

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Deshpande, Srinivas, and Rohan S. Gurav. "Change Detection of Land Use and Land Cover Over Ghataprabha River Basin." International Journal of Science and Research (IJSR) 12, no. 10 (2023): 71–78. http://dx.doi.org/10.21275/sr23930164256.

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Sharma, Namita, Rimlee Bora, and Jyotishma Bordoloi. "Hotspots of Land Use Land Cover Change: World’s Largest Riverine Island Scenario." Indian Journal Of Science And Technology 17, no. 43 (2024): 4536–45. http://dx.doi.org/10.17485/ijst/v17i43.3030.

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Objectives: The study gives priority to the Land Use Land Cover (LULC) changes and changing hotspot locations of Majuli, which is the largest riverine island in Assam. Methods: Satellite imageries for the years 2002, 2011, and 2022 have been utilized to observe spatiotemporal dynamics using the iso cluster unsupervised classification technique. The Iso cluster unsupervised classification method can identify clusters of an image automatically and classify it based on its clusters. The analysis of change has been taken into account by assigning six land use classes, viz. cropland, forest, waterb

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Sarah, Namayengo. "Dynamics of land use and land cover changes and their effect on carbon stocks of Rwenzori Mountains National Park." Journal of Biodiversity and Environmental Sciences (JBES) 25, no. 2 (2024): 111–25. https://doi.org/10.5281/zenodo.15378775.

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This study characterized the extent of land use land cover changes in Rwenzori Mountains National Park (RMNP) and determined the effect of observed land use land cover changes on the park’s carbon stocks. Landsat 5 images were obtained of 1990; Landsat 7 of 2000 and 2010 and Landsat 8 of 2020 for Rwenzori Mountains National Park and analyzed using GIS tools in ArcGIS 10.5 using supervised classification. The Landsat scenes were obtained from path and row (171, 060) and (172, 060). The effect of land use land cover changes on the park’s carbon stocks was determined by estimating the

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Sarah, Namayengo. "Dynamics of land use and land cover changes and their effect on carbon stocks of Rwenzori Mountains National Park." Journal of Biodiversity and Environmental Sciences (JBES) 25, no. 2 (2024): 111–25. https://doi.org/10.5281/zenodo.15379093.

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This study characterized the extent of land use land cover changes in Rwenzori Mountains National Park (RMNP) and determined the effect of observed land use land cover changes on the park’s carbon stocks. Landsat 5 images were obtained of 1990; Landsat 7 of 2000 and 2010 and Landsat 8 of 2020 for Rwenzori Mountains National Park and analyzed using GIS tools in ArcGIS 10.5 using supervised classification. The Landsat scenes were obtained from path and row (171, 060) and (172, 060). The effect of land use land cover changes on the park’s carbon stocks was determined by estimating the

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Alvarez Gebelin, Ana, Martín Borretti, Carlos Cohn, and Guillermo Minutti. "Land Cover and Land Use in Uruguay Using Land Cover Classification System Methodology." Land 13, no. 12 (2024): 2168. https://doi.org/10.3390/land13122168.

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Mapping land cover in Uruguay is essential to meet the growing demand for accurate data to support sustainable development policies and manage natural resources, while also addressing the United Nations Sustainable Development Goals (SDGs) and other international conventions. In recent decades, collaboration between the FAO and the Government of Uruguay has led to the development of key products that strengthen the country’s planning processes, including a detailed, standardized national land cover database. By using the FAO’s Land Cover Classification System (LCCS), Uruguay has achieved a mul

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Nirea, Abadi Gidey, and Kassa Teka. "Analysis of Land Use and Land Cover Dynamics in the Highlands of Northern Ethiopia." Asian Journal of Research in Agriculture and Forestry 10, no. 4 (2024): 262–72. http://dx.doi.org/10.9734/ajraf/2024/v10i4334.

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In the highlands of northern Ethiopia, many land use and land cover changes (LULCC) have occurred during different activities of the populations. Despite its coverage and unwise use of natural resources, these land uses and land covers are facing increasing or decreasing their area coverage. Information derived from land use and land cover change detection is important to land conservation, sustainable development, and management of Natural resources. This purpose of this study is therefore concerned with identifying the change in land use and land cover detection of the Wejic watershed. To id

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Kobayashi, Toshiyuki, Ryutaro Tateishi, Bayan Alsaaideh, et al. "Production of Global Land Cover Data – GLCNMO2013." Journal of Geography and Geology 9, no. 3 (2017): 1. http://dx.doi.org/10.5539/jgg.v9n3p1.

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Global land cover products have been created for global environmental studies by several institutions and organizations. The Global Mapping Project coordinated by the International Steering Committee for Global Mapping (ISCGM) has been periodically producing global land cover datasets asone of the eight basic global datasets. It has produced a new fifteen-second (approximately 500 m resolution at the equator) global land cover dataset – GLCNMO2013 (or GLCNMO version 3). This paper describes the method of producing GLCNMO2013. GLCNMO2013 has 20 land cover classes, and they were mapped by improv

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Guliyeva, S. H. "LAND COVER / LAND USE MONITORING FOR AGRICULTURE FEATURES CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 61–65. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-61-2020.

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Abstract. Remote sensing applications are directed to agricultural observation and monitoring. It has been huge of scientific papers are dedicated to the research of the contribution of remote sensing for agriculture studies. There are several global challenges needed to be considered within agriculture activities. It can be embraced by the main agriculture sector facing the obstacles impacting the production and productivity of the sector. These are the following options that can be pointed out: biomass and yield estimation; vegetation vigor and drought stress monitoring; assessment of crop p

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Phi, Dinh Cao, and Nguyen Hai Hoa. "USING ATMOSPHERICALLY RESISTANT VEGETATION INDEX TO DETECT FOREST COVER CHANGE IN LAC DUONG DISTRICT, LAM DONG PROVINCE." Journal of Forestry Science and Technology, no. 14 (2022): 129–40. http://dx.doi.org/10.55250/jo.vnuf.2022.14.129-140.

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This study tested the potential of using Sentinel-2-derived ARVI for land covers mapping compared to NDVI in Lac Duong district, Lam Dong province. Overall accuracy assessments of ARVI-based land covers mapping are calculated from 88.9% (in 2016) to 92.0% (in 2022) with Kappa coefficients of 0.79 and 0.86, respectively. The comparison between Sentinel-2-derived NDVI and ARVI for land covers mapping indicated that ARVI has performed well in land covers mapping in Lac Duong district. The Sentinel-2 time series were therefore used to generate spectral-temporal changes in land covers based on ARVI

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Ahmad and R. Utomowati. "Dynamics types of land use and land cover to determine time of the value erosion coefficient criticism in Keduang Watershed." IOP Conference Series: Earth and Environmental Science 986, no. 1 (2022): 012056. http://dx.doi.org/10.1088/1755-1315/986/1/012056.

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Abstract This research aims to: (1) Determine the trends in change of the type of plants planted by the community within a year for each type of land use in Keduang Watershed; (2) Understand the dynamics of land cover in each land-use unit in Keduang Watershed; (3) Determine the influential factors of the dynamics land use and land cover in Keduang Watershed; (4) Understand in what circumstances the criticality of erosion coefficient (C value) occurs in Keduang Watershed. The methods used are: (1) analysis of trends in changes of crop types are determined based on the rotation of the plant spe

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Shao, Mengmeng, Xiao Xie, Kaiyuan Li, Changgui Li, and Xiran Zhou. "Semantic-Enhanced Foundation Model for Coastal Land Use Recognition from Optical Satellite Images." Applied Sciences 14, no. 20 (2024): 9431. http://dx.doi.org/10.3390/app14209431.

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Coastal land use represents the combination of various land cover forms in a coastal area, which helps us understand the historical events, current conditions, and future progress of a coastal area. Currently, the emergence of high-resolution optical satellite images significantly extends the scope of coastal land cover recognition, and deep learning models provide a significant possibility of extracting high-level abstract features from an optical satellite image to characterize complicated coastal land covers. However, recognition systems for labeling are always defined differently for speci

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Wahyuni, Nurlita, Abdul Hasyim, and Soemarno Soemarno. "Dynamic of the Land Use and Land Cover Change in Banyuwangi Regency From 1995-2019." Jurnal Wasian 8, no. 2 (2021): 121–32. http://dx.doi.org/10.20886/jwas.v8i2.6707.

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The land use and land cover change phenomenon has become one concern over many regions worldwide, including Indonesia. Land use and land cover change due to human activities triggered alteration terrestrial ecosystems and its services including climate control functions. The study aimed to analyze land use and land cover change in Banyuwangi regency during 1995 – 2019. Four satellite images from acquisition year 1995, 2000, 2014 and 2019 were used to analyze the spatial and temporal changes along with field observations. The classification processes of land use and land cover included determin

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Adugna, Alemayehu, Assefa Abegaz, Asmamaw Legass, and Diogenes L. Antille. "RANDOM AND SYSTEMATIC LAND-COVER TRANSITIONS IN NORTH-EASTERN WOLLEGA, ETHIOPIA." BOIS & FORETS DES TROPIQUES 332 (September 18, 2017): 3–15. http://dx.doi.org/10.19182/bft2017.332.a31329.

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Africa has seen significant changes in land cover at different spatial scales. Changes in Land Use and Land Cover (LULC) include deforestation and subse- quent use of the land for arable cropping, conversion to grassland or urbanization. The work reported in this article was conducted to examine land cover transi- tions in north-eastern Wollega (Ethiopia) between 2005 and 2015. The analysis focused on land cover transitions that occurred systematically or randomly, and identified the main drivers for these changes. Landsat data from 2005 and 2015 were examined to better unders- tand the variou

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Kolar, Jan. "Land cover accounting." International Journal of Environment and Pollution 15, no. 6 (2001): 695. http://dx.doi.org/10.1504/ijep.2001.004988.

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Wulder, Michael A., Nicholas C. Coops, David P. Roy, Joanne C. White, and Txomin Hermosilla. "Land cover 2.0." International Journal of Remote Sensing 39, no. 12 (2018): 4254–84. http://dx.doi.org/10.1080/01431161.2018.1452075.

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Dewi, R. A., A. Triyogo, and E. Faridah. "Diversity of Collembola on Various Post-Rehabilitation Land Covers." Jurnal Manajemen Hutan Tropika (Journal of Tropical Forest Management) 30, no. 1 (2024): 40–50. http://dx.doi.org/10.7226/jtfm.30.1.40.

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The success of rehabilitation has altered environmental conditions from critical land to new habitats for living organisms. One of the representative and sensitive mesofauna to environmental changes is Collembola. Various vegetation cover almost all of the rehabilitation area, which has impacts on microclimate and soil quality as important factors to Collembola existence. This study investigated the diversity and abundance of Collembola and its relation to environmental factors on various land covers, including teak, grass, and mixed stand land cover. Data were collected in an observation plot

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Zeng, Tian, Lei Wang, Zengxiang Zhang, Qingke Wen, Xiao Wang, and Le Yu. "An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps." Remote Sensing 11, no. 15 (2019): 1777. http://dx.doi.org/10.3390/rs11151777.

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In land cover mapping, an area with complex topography or heterogeneous land covers is usually poorly classified and therefore defined as a low-accuracy area. The low-accuracy areas are important because they restrict the overall accuracy (OA) of global land cover classification (LCC) data generated. In this paper, low-accuracy areas in China (extracted from the MODIS global LCC maps) were taken as examples, identified as the regions having lower accuracy than the average OA of China. An integrated land cover mapping method targeting low-accuracy regions was developed and tested in eight repre

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Hanafi, Fahrudin, Dinda Putri Rahmadewi, and Fajar Setiawan. "Land Cover Changes Based on Cellular Automata for Land Surface Temperature in Semarang Regency." Geosfera Indonesia 6, no. 3 (2021): 301. http://dx.doi.org/10.19184/geosi.v6i3.23471.

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Land cover changes based on cellular automata for surface temperature in Semarang Regency has increased significantly due to the continuous rise in its population. Therefore, this study aims to identify, analyze and predict multitemporal land cover changes and surface temperature distribution in 2028. Data on the land cover map were obtained from Landsat 7 and 8 based on supervised classification, while Land Surface Temperature (LST) was calculated from its thermal bands. The collected data were analyzed for accuracy through observation, while Cellular Automata - Markov Chain was used to predi

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Gaillard, M. J., S. Sugita, F. Mazier, et al. "Holocene land-cover reconstructions for studies on land cover-climate feedbacks." Climate of the Past 6, no. 4 (2010): 483–99. http://dx.doi.org/10.5194/cp-6-483-2010.

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Abstract. The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS re

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Gaillard, M. J., S. Sugita, F. Mazier, et al. "Holocene land-cover reconstructions for studies on land cover-climate feedbacks." Climate of the Past Discussions 6, no. 2 (2010): 307–46. http://dx.doi.org/10.5194/cpd-6-307-2010.

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Abstract. The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS re

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Nguyen, Lan H., and Geoffrey M. Henebry. "Characterizing Land Use/Land Cover Using Multi-Sensor Time Series from the Perspective of Land Surface Phenology." Remote Sensing 11, no. 14 (2019): 1677. http://dx.doi.org/10.3390/rs11141677.

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Due to a rapid increase in accessible Earth observation data coupled with high computing and storage capabilities, multiple efforts over the past few years have aimed to map land use/land cover using image time series with promising outcomes. Here, we evaluate the comparative performance of alternative land cover classifications generated by using only (1) phenological metrics derived from either of two land surface phenology models, or (2) a suite of spectral band percentiles and normalized ratios (spectral variables), or (3) a combination of phenological metrics and spectral variables. First

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Abuzar, Mohammad, Andy McAllister, Des Whitfield, and Kathryn Sheffield. "Remotely-Sensed Surface Temperature and Vegetation Status for the Assessment of Decadal Change in the Irrigated Land Cover of North-Central Victoria, Australia." Land 9, no. 9 (2020): 308. http://dx.doi.org/10.3390/land9090308.

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Monitoring of irrigated land cover is important for both resource managers and farmers. An operational approach is presented to use the satellite-derived surface temperature and vegetation cover in order to distinguish between irrigated and non-irrigated land. Using an iterative thresholding procedure to minimize within-class variance, the bilevel segmentation of surface temperature and vegetation cover was achieved for each irrigation period (Spring, Summer and Autumn). The three periodic profiles were used to define irrigation land covers from 2008–2009 to 2018–2019 in a key agricultural reg

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Purboyo, Alvian Aji, Andri Kurniawan, and Luthfi Muta'ali. "Identifikasi Tutupan Lahan Menggunakan Support Vector Machine di Kawasan Perkotaan Cekungan Bandung." Jurnal Komtika (Komputasi dan Informatika) 8, no. 1 (2024): 54–64. http://dx.doi.org/10.31603/komtika.v8i1.11140.

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The current mapping challenge is to obtain land cover information with a very high level of accuracy. This information can be useful for regional development, especially in the Bandung Basin Urban Area (KPCB). One of the problems in KPCB is spatial planning issues regarding land cover development. One approach to obtaining land cover information is by utilizing remote sensing technology using the Support Vector Machine (SVM) method. The research method employed in this study is remote sensing, with a unit of analysis based on Regency/City administrative boundaries. The data used in this resear

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Misrah, Misrah, and Ida Arianingsih. "Analysis of Land Cover Changes In The Forest Area of Lindu Citra District Using Sentinel 2A Images." Journal of Social Research 4, no. 6 (2025): 1063–74. https://doi.org/10.55324/josr.v4i6.2568.

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Land cover change in forest areas are complex phenomena that have ecological, social, and economic impacts. Remote sensing is very useful for monitoring and mapping land cover changes because it can provide information about the earth's surface quickly, accurately, easily, and covers a wide area. Sentinel-2A imagery is a satellite remote sensing data with a high spatial resolution and has been widely used for land cover mapping. The study intends to analyze land cover changes in the forest area of Lindu District using Sentinel-2A imagery. The study was conducted in the forest region of Lindu S

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Achmad, Eva, Fazriyas, Bambang Irawan, and Adi Karta Kusuma. "Forest cover changes analysis using Landsat Imageries over Pengabuan Watershed in Jambi Province." IOP Conference Series: Earth and Environmental Science 1095, no. 1 (2022): 012024. http://dx.doi.org/10.1088/1755-1315/1095/1/012024.

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Abstract The availability of land cover in the form of forest is very important in the watershed system (DAS). The decrease in forest cover and the carbon content stored in a watershed also shows a decline in the quality of the watershed. The research aims to examine changes in land cover that occurred during the last twenty years in the Pengabuan Watershed. Changes in land cover were obtained by classifying Landsat imagery from 1996 to 2017. Classification was carried out using the supervised classification method and visual interpretation and then followed by change detection analysis. The r

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