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Assessment and prediction of LULCC dynamics in a part of Indo-Gangetic Alluvial Plain (IGAP) using geospatial techniques on multi-temporal Landsat imageries

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Abstract

The Indo-Gangetic Alluvial Plain (IGAP) rank among world’s most densely populated areas with total population exceeding 400 million. This population expansion has resulted into vast change in land use-land cover (LULC) of region. So, there is a need to quantify land use-land cover change (LULCC) to study its future impact. This study demonstrates a methodology for obtaining LULC information, detecting LULCC dynamics and predicting future LULC in a part of IGAP. The study area consists of some regions of Prayagraj, Pratapgarh, Kaushambi, and Chitrakoot, Uttar Pradesh, India. First, LULC maps are prepared by executing Maximum Likelihood Classification (MLC) on Landsat images of 1990, 2003, and 2014. Seven LULC classes are identified, namely, urban settlement, stoney waste, water body, river bed, cultivated land, open scrub, and dense vegetation. Then, change detection is performed by using image differencing from 1990–2003, 2003–2014, and 1990–2014. The study depicts overall average rate of increment from 1990 to 2014 in urban settlement, cultivated land, open scrub, and river bed as 37.73%, 51.78%, 14.71%, and 38.96%, respectively, whereas overall average rate of reduction in water body, dense vegetation, and stoney waste is found to be 12.8%, 59.14%, and 22.12% from 1990 to 2014. Based on these estimated average change rate coefficients, future LULC predictions are done by 2024, 2034, and 2044. These results would help the planners to formulate policies for land management to benefit society. Moreover, this study is useful to determine hydrological impacts of LULCC to predict flooding and drought conditions in study area.

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Availability of data and material

All the Landsat images were downloaded from https://earthexplorer.usgs.gov free of cost. Toposheet no. 63G was obtained from GIS Cell, MNNIT Allahabad.

Code availability

ArcGis 10.5 and Erdas Imagine 2014 software are used.

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Funding was provided by MNNIT Allahabad, Uttar Pradesh, India.

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    Shilpi

  2. Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh, India

    Raj Mohan Singh

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Prof. R. M. Singh supervised this research, whereas Dr. Shilpi performed all the practical work related to research.

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Shilpi, Singh, R.M. Assessment and prediction of LULCC dynamics in a part of Indo-Gangetic Alluvial Plain (IGAP) using geospatial techniques on multi-temporal Landsat imageries. Arab J Geosci 15, 1076 (2022). https://doi.org/10.1007/s12517-022-09892-9

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  • DOI: https://doi.org/10.1007/s12517-022-09892-9

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