Using logit model to identify the drivers of landuse landcover change in the Lower Gangetic Basin, India

Abstract

ABSTRACT:The Lower Gangetic Basin is one of the most highly populated areas of India, covering an area of 286,899 km 2 with a population density of 720 persons per km 2 . 64% of the area is covered under agriculture which is supported by the highly fertile alluvial soil. Landuse and landcover (LULC) changes due to an ever increasing human population, natural disasters induced by climate change can alter agricultural productivity which in turn can affect the food security of the region. The current study found out the change in LULC over a span of 20 years , and identified the factors driving this change. LULC data was generated from geo-corrected satellite data of LANDSAT-MSS, IRS LISS-I and IRS LISS-III for pre monsoon and post monsoon seasons for the years 1985-86, 1994-95 and 2004-05 respectively, using onscreen visual interpretation at 1:250,000 scale. We used cross-tabulation matrix to investigate landuse and landcover transformation. The most significant transformation has been to built-up category, contributed by agricultural land (515 km 2 ) and scrubland (53 km 2 ). The other notable transformations are from agriculture to plantation (247 km 2 ), fallow to scrubland (838 km 2 ) and from water body to scrubland (407 km 2 ). We generated change no-change matrix and analyzed it using logistic regression to investigate the drivers of LULC change. We identified availability of water for irrigation, literacy, sexratio and the availability of different sources of livelihoods, as the major drivers of LULC change in the Lower Gangetic Basin.

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Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China

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Using SHAP to interpret XGBoost predictions of grassland degradation in Xilingol, China

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