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  • Open Access

    ARTICLE

    Integrating Temporal Change Detection and Advanced Hybrid Modeling to Predict Urban Expansion in Jaipur, a UNESCO World Heritage City

    Saurabh Singh1,2, Sudip Pandey3,*, Ankush Kumar Jain1

    Revue Internationale de Géomatique, Vol.34, pp. 899-914, 2025, DOI:10.32604/rig.2025.071156 - 09 December 2025

    Abstract Urban expansion in semi-arid regions poses critical challenges for sustainable land management, ecological resilience, and heritage conservation. Jaipur, India—a United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage City located in a semi-arid environment—faces rapid urbanization that threatens agricultural productivity, fragile ecosystems, and cultural assets. This study quantifies past and projects future land use/land cover (LULC) dynamics in Jaipur to support evidence-based planning. Using the Dynamic World dataset, we generated annual 10-m LULC maps from 2016 to 2025 within the municipal boundary. Temporal change detection was conducted through empirical transition probability analysis, and future… More >

  • Open Access

    ARTICLE

    Forecasting LULC Dynamics of Soran under Future Climate Scenarios Using Machine Learning

    Abdulqadeer Rash1,*, Yaseen T. Mustafa2,3,4, Rahel Hamad5

    Revue Internationale de Géomatique, Vol.34, pp. 381-414, 2025, DOI:10.32604/rig.2025.065870 - 29 July 2025

    Abstract Changes in land use/land cover (LULC) are a substantial environmental subject with considerable consequences for human well-being, climate, and ecosystems. Innovative investigations for predicting LULC changes are essential for effective land management and sustainable development. This study used Landsat images and supplementary spatial factors to evaluate spatiotemporal LULC changes in Erbil Province, Kurdistan Region-Iraq. It predicts future changes in 2040 using four climates scenario-based Shared Socioeconomic Pathways (SSPs). The Random Forest (RF) model was used to classify and forecast LULC changes, which are crucial for effective land management and sustainable development. The RF model was… More >

  • Open Access

    ARTICLE

    Mapping of Land Use and Land Cover (LULC) Using EuroSAT and Transfer Learning

    Suman Kunwar1,*, Jannatul Ferdush2

    Revue Internationale de Géomatique, Vol.33, pp. 1-13, 2024, DOI:10.32604/rig.2023.047627 - 27 February 2024

    Abstract As the global population continues to expand, the demand for natural resources increases. Unfortunately, human activities account for 23% of greenhouse gas emissions. On a positive note, remote sensing technologies have emerged as a valuable tool in managing our environment. These technologies allow us to monitor land use, plan urban areas, and drive advancements in areas such as agriculture, climate change mitigation, disaster recovery, and environmental monitoring. Recent advances in Artificial Intelligence (AI), computer vision, and earth observation data have enabled unprecedented accuracy in land use mapping. By using transfer learning and fine-tuning with red-green-blue More > Graphic Abstract

    Mapping of Land Use and Land Cover (LULC) Using EuroSAT and Transfer Learning

  • Open Access

    ARTICLE

    Smart Techniques for LULC Micro Class Classification Using Landsat8 Imagery

    Mutiullah Jamil1, Hafeez ul Rehman1, SaleemUllah1, Imran Ashraf2,*, Saqib Ubaid1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5545-5557, 2023, DOI:10.32604/cmc.2023.033449 - 28 December 2022

    Abstract Wheat species play important role in the price of products and wheat production estimation. There are several mathematical models used for the estimation of the wheat crop but these models are implemented without considering the wheat species which is an important independent variable. The task of wheat species identification is challenging both for human experts as well as for computer vision-based solutions. With the use of satellite remote sensing, it is possible to identify and monitor wheat species on a large scale at any stage of the crop life cycle. In this work, nine popular… More >

  • Open Access

    ARTICLE

    Quantification of Urban Sprawl for Past-To-Future in Abha City, Saudi Arabia

    Saeed AlQadhi1, Javed Mallick1,*, Swapan Talukdar2, Ahmed Ali Bindajam3, Ahmed Ali A. Shohan3, Shahfahad4

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 755-786, 2021, DOI:10.32604/cmes.2021.016640 - 08 October 2021

    Abstract Given that many cities in Saudi Arabia have been observing rapid urbanization since the 1990s, scarce studies on the spatial pattern of urban expansion in Saudi Arabia have been conducted. Therefore, the present study investigates the evidence of land use and land cover (LULC) dynamics and urban sprawl in Abha City of Saudi Arabia, which has been experiencing rapid urbanization, from the past to the future using novel and sophisticated methods. The SVM classifier was used in this study to classify the LULC maps for 1990, 2000, and 2018. The LULC dynamics between 1990–2000, 2000–2018,… More >

  • Open Access

    ARTICLE

    Observed Impacts of Climate Variability on LULC in the Mesopotamia Region

    Muntaha Alzubade1,*, Orkan Ozcan1, Nebiye Musaoglu1, Murat Türkeş2

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2255-2269, 2021, DOI:10.32604/cmc.2021.013565 - 05 February 2021

    Abstract Remote sensing analysis techniques have been investigated extensively, represented by a critical vision, and are used to advance our understanding of the impacts of climate change and variability on the environment. This study aims to find a means of analysis that relies on remote sensing techniques to demonstrate the effects of observed climate variability on Land Use and Land Cover (LULC) of the Mesopotamia region, defined as a historical region located in the Middle East. This study employed the combined analysis of the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and two statistical… More >

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