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ORIGINAL RESEARCH article

Front. Environ. Sci.

Sec. Land Use Dynamics

Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1540140

Predicting Changes in Land Use and Land Cover using Remote Sensing and Land Change Modeler

Provisionally accepted
Brijmohan Bairwa Brijmohan Bairwa 1Rashmi Sharma Rashmi Sharma 1Arnab Kundu Arnab Kundu 2Saad Shauket Sammen Saad Shauket Sammen 3Fahad Alshehri Fahad Alshehri 4Chaitanya Pande Chaitanya Pande 5Zoltan Orban Zoltan Orban 6Ali Salem Ali Salem 6,7*
  • 1 Banasthali University, Vanasthali, Rajasthan, India
  • 2 bankura university, West Bengal, India
  • 3 University of Diyala, Baqubah, Diyala, Iraq
  • 4 King Saud University, Riyadh, Riyadh, Saudi Arabia
  • 5 Al-Ayen University, Nasiriyah, Dhi Qar, Iraq
  • 6 Faculty of Engineering and Information Technology, University of Pécs, Pécs, Hungary
  • 7 Minia University, Minya, Minya, Egypt

The final, formatted version of the article will be published soon.

    Human activities and climate change exert significant influence on global land-use and land-cover (LULC) alteration. The integration of geo-spatial and remote sensing technologies is pivotal in comprehending these dynamics and formulating strategies for future natural resource management. This research is centered on the modeling of spatio-temporal trajectories of landscape transformation spanning from 1988 to 2018, with a forward-looking scenario up to 2040. By leveraging imagery from Landsat 5, LISS-3, and Sentinel 2A MSI, a detailed assessment of LULC changes was carried out for the Mashi Dam command (CMD) area in Rajasthan, India, covering a total expanse of 90.07 km 2 . Rigorous validation of the 2018 land cover map against ground-truth data ensured the reliability of predictions, which were subsequently utilized to forecast LULC patterns for 2031 and 2041. The analysis uncovered significant impacts on cropland, barren land, built-up areas, and scrub land throughout the study period. Notably, built-up areas, water bodies, and barren land exhibited substantial growth from 2008 to 2018, while cropland experienced a decline of 4.75% in the same timeframe. Projections indicate a further reduction in cropland by 2041, accompanied by an expansion of barren land. These results underscore the critical imperative for effective land management strategies to mitigate the conversion of cropland and scrub land into barren areas, thereby ensuring the sustainable utilization of agricultural resources in the region.

    Keywords: transformation, Future prediction, LULC, Geoinformatics, Rajasthan (India)

    Received: 05 Dec 2024; Accepted: 24 Mar 2025.

    Copyright: © 2025 Bairwa, Sharma, Kundu, Sammen, Alshehri, Pande, Orban and Salem. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ali Salem, Faculty of Engineering and Information Technology, University of Pécs, Pécs, 7624, Hungary

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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