Spatio-Temporal Assessment of Land Use/Land Cover Change, Land Surface Temperature, and Groundwater Fluctuations Using Remote Sensing and GIS: A Case Study of Ghaziabad District

Abstract

Urbanization has been increasing at a rapid rate, which has led to transformation in the land use/land cover (LULC) and thus has a significant impact on groundwater resources and land surface temperature (LST) in rapidly developing cities. The present study aims to identify the spatio-temporal dynamics of LULC, LST, and the variability of groundwater in Ghaziabad District, Uttar Pradesh, India, from 2013 to 2023 using Remote Sensing and GIS techniques. Multi-temporal Landsat data were classified using the Maximum Likelihood Supervised Classification algorithm for the LULC maps that included 5 classes: built-up area, agriculture, vegetation, barren land, and water bodies. The accuracy of the classifications was assessed by the Kappa coefficient, and the Ordinary Kriging (OK) method was applied to spatially interpolate the groundwater depth in ArcGIS 10.8. Between 2013 and 2023, substantial increases in built-up areas and loss of vegetation cover were observed in the findings. Over the same time period, groundwater depth continued to decline in a progressive manner, and high LST areas became larger, especially in dense urban settings. The integrated analysis shows that surface thermal conditions and groundwater stress have intensified due to LULC transformation. The results highlight the importance of sustainable urban planning, groundwater recharge initiatives, and green infrastructure to reduce thermal risks and promote environmental sustainability in rapidly urbanizing areas.