Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands

The available global or national land use and land cover (LULC) maps are not explicitly focused on wetland management. However, developing a LULC focused on wetlands has become crucial to mitigate the challenges related to water resource management, specifically where anthropogenic stress is high. T...

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Main Authors: Ghosh, Surajit, Guha, A.
Format: Preprint
Language:Inglés
Published: 2025
Subjects:
Online Access:https://hdl.handle.net/10568/180494
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author Ghosh, Surajit
Guha, A.
author_browse Ghosh, Surajit
Guha, A.
author_facet Ghosh, Surajit
Guha, A.
author_sort Ghosh, Surajit
collection Repository of Agricultural Research Outputs (CGSpace)
description The available global or national land use and land cover (LULC) maps are not explicitly focused on wetland management. However, developing a LULC focused on wetlands has become crucial to mitigate the challenges related to water resource management, specifically where anthropogenic stress is high. This study addresses the paucity of tailored LULC classification methodologies for such dynamic peri-urban wetland ecosystems, taking the case of the East Kolkata Wetlands (EKW), a Ramsar site recognized for its community-managed wastewater-fed aquaculture system, threaten by rapid urban expansion and hydrological alteration. The multi-temporal Sentinel-2 MSI imagery (February–May 2025) and a Random Forest (RF) classifier (with an 80:20 training/testing ratio) within Google Earth Engine (GEE) were used. The study developed a hierarchical seven-stage sequential LULC classification significant to wetland management: (1) water vs. non-water; (2) vegetation vs. non-vegetation; (3) built-up vs. fallow land/pond; (4) aquatic vs. terrestrial vegetation; (5) agricultural vs. other vegetation; (6) fallow land vs. fallow pond; and (7) landfill sub-classes (active/closed dump). Various spectral indices related to soil, vegetation, and water quality, with FABDEM data, were used to build the RF model. Thus, the hierarchical framework proposed improves the class separability over conventional RF approaches, producing a detailed LULC map (with an overall accuracy of 89.29%) that distinguishes between aquaculture ponds, marshes, agricultural areas, fallow lands, built-up areas, and landfill sites. These results provide a granular, operationally relevant insights for effective resource management of wetland ecosystems and the sustainable governance of urban wetlands.
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spelling CGSpace1804942026-01-23T09:36:08Z Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands Ghosh, Surajit Guha, A. wetlands land use land cover satellite imagery ecosystems The available global or national land use and land cover (LULC) maps are not explicitly focused on wetland management. However, developing a LULC focused on wetlands has become crucial to mitigate the challenges related to water resource management, specifically where anthropogenic stress is high. This study addresses the paucity of tailored LULC classification methodologies for such dynamic peri-urban wetland ecosystems, taking the case of the East Kolkata Wetlands (EKW), a Ramsar site recognized for its community-managed wastewater-fed aquaculture system, threaten by rapid urban expansion and hydrological alteration. The multi-temporal Sentinel-2 MSI imagery (February–May 2025) and a Random Forest (RF) classifier (with an 80:20 training/testing ratio) within Google Earth Engine (GEE) were used. The study developed a hierarchical seven-stage sequential LULC classification significant to wetland management: (1) water vs. non-water; (2) vegetation vs. non-vegetation; (3) built-up vs. fallow land/pond; (4) aquatic vs. terrestrial vegetation; (5) agricultural vs. other vegetation; (6) fallow land vs. fallow pond; and (7) landfill sub-classes (active/closed dump). Various spectral indices related to soil, vegetation, and water quality, with FABDEM data, were used to build the RF model. Thus, the hierarchical framework proposed improves the class separability over conventional RF approaches, producing a detailed LULC map (with an overall accuracy of 89.29%) that distinguishes between aquaculture ponds, marshes, agricultural areas, fallow lands, built-up areas, and landfill sites. These results provide a granular, operationally relevant insights for effective resource management of wetland ecosystems and the sustainable governance of urban wetlands. 2025-12-30 2026-01-23T09:31:25Z 2026-01-23T09:31:25Z Preprint https://hdl.handle.net/10568/180494 en Open Access Ghosh, S.; Guha, A. 2025. Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands. ResearchGate, 39p. doi: https://doi.org/10.13140/RG.2.2.22196.92807
spellingShingle wetlands
land use
land cover
satellite imagery
ecosystems
Ghosh, Surajit
Guha, A.
Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands
title Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands
title_full Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands
title_fullStr Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands
title_full_unstemmed Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands
title_short Land use and land cover classification of wetlands: addressing paucity with the case of the East Kolkata Wetlands
title_sort land use and land cover classification of wetlands addressing paucity with the case of the east kolkata wetlands
topic wetlands
land use
land cover
satellite imagery
ecosystems
url https://hdl.handle.net/10568/180494
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