2021
DOI: 10.3390/su132413758
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Analysis of Land Use and Land Cover Using Machine Learning Algorithms on Google Earth Engine for Munneru River Basin, India

Abstract: The growing human population accelerates alterations in land use and land cover (LULC) over time, putting tremendous strain on natural resources. Monitoring and assessing LULC change over large areas is critical in a variety of fields, including natural resource management and climate change research. LULC change has emerged as a critical concern for policymakers and environmentalists. As the need for the reliable estimation of LULC maps from remote sensing data grows, it is critical to comprehend how differen… Show more

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Cited by 90 publications
(59 citation statements)
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“…Figure S1 depicts the RCM grid points and sub-basins in the study area. This basin has been chosen as the study area as part of the ongoing research project IWMM-BIS, titled "Integrated Water Management Model for Brazil, India and South Africa under climate change scenarios" [43].…”
Section: Study Areamentioning
confidence: 99%
“…Figure S1 depicts the RCM grid points and sub-basins in the study area. This basin has been chosen as the study area as part of the ongoing research project IWMM-BIS, titled "Integrated Water Management Model for Brazil, India and South Africa under climate change scenarios" [43].…”
Section: Study Areamentioning
confidence: 99%
“…We obtained that optical satellite images are beneficial for land and land-cover maps. Some approaches that use the same technologies and tools for the land-cover map are [48,50,64].…”
Section: Discussionmentioning
confidence: 99%
“…Some studies in the literature used Sentinel-2 and the three classification algorithms mentioned. Praticó et al [48] and Loukika et al [64] used Sentinel-2 and the RF, SVM, and CART algorithms. The best results obtained were with RF and SVM.…”
Section: Discussionmentioning
confidence: 99%
“…Today, with the development of cloud-based platforms such as Google Earth Engine (GEE), it has been possible to process remote sensing data online without downloading [20]. Various studies showed the effectiveness of GEE in different remote sensing applications such as landcover classification [21,22], wetland detection [23], water quality monitoring [24], flood mapping [19], and impact analysis of drought and floods on croplands [25].…”
Section: Introductionmentioning
confidence: 99%