Mapping and monitoring of land use dynamics with their change hotspot in North 24-Parganas district, India: a geospatial- and statistical-based approach

Modeling Earth Systems and Environment(2019)

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摘要
Interlinking between anthropogenic activities and natural environment can be monitored through the changing pattern of land use dynamics. The present research has been completed with the amalgamation of Geographical Information System (GIS) and statistical techniques in Sundarbans contiguity North 24 Parganas district. This study aims towards unveiling the existing land use/land cover and their recent transformation pattern, rate and their change ‘hotspot’ over the entire 27-year period. In this study, integration of supervised maximum likelihood classification approach (MLCA) and post-classification comparison approach (PCCA) have been used for accumulating the dynamic information regarding the land use dynamics. The result undoubtedly indicates that the built-up area had been drastically increased and vegetation area had been extremely decreased. Transition matrix shows that the maximum agricultural land was converted into a built-up area and water bodies at the same time agriculture have lost maximum area and built up gained maximum area. However, Moran’s I and Getis–Ord (Gi*) statistic indicate that most of the hotspot have been found in built-up area spacially in the western and south-western part of the district. The overall accuracy of the classification is an acceptable range (> 85%). Finally, this study concludes, the present trend of existing land use and land cover should be monitored for the preservation of standing vegetation, control the lopsided growth of built-up area and natural resource to maintain the natural ecosystem. The potential transformation among the land use classes is imperative towards the planning for sustainable land resource management, appropriate land use for the exact purpose, and potential development in this area.
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关键词
Land use/land cover, Maximum likelihood classification (MLC)/post-classification comparison (PCC), Transition matrix, Change hotspot/cold spot, North 24 Parganas
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