Journal of Remote Sensing & GIS
Volume 17, Issue 1 (2026)
Table of contents
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Urban Green space Site Suitability analysis of Angul City, Odisha – A Geospatial Approach
Abstract: The urban ecological system is crucial for human survival in cities. Residents receive various services directly or indirectly from the functions of ecosystems, known as ecosystem services. Heat stress in urban areas can be particularly harmful, as the negative effects of increasing urbanization lead to significant temperature changes that impact both vulnerable species and human health. While there are several methods, such as modifying roof materials and using lighter colors, …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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An In-Depth Assessment of Flood Susceptibility using Geo-informatics – A Detailed Review
Abstract: In recent years, the world has faced many disasters, but the effects of floods have received considerable focus due to their harmful consequences. More than half of the global destruction and damage from floods takes place in Asia, leading to loss of life, infrastructure damage, and community panic. The main goal is to improve the understanding of flood hazard management by conducting flood vulnerability assessments. Vulnerability is central to analyzing …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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A multi-index remote sensing analysis for Characterizing water stress, and environmental indicators in Girnar Wildlife Sanctuary, Gujarat, India
Abstract: Water scarcity is a critical concern in arid and semi-arid regions, with implications for ecological stability, public health, and sustainable resource management. The Girnar Wildlife Sanctuary, Gujarat, presents a case where ecological fragility intersects with cultural and religious pressures. This study employs satellite remote sensing and GIS-based approach to characterize water stress parameters within the sanctuary. Key spectral indices along with Land Use and Land Cover (LULC) were integrated through …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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The Impact of Using High-Resolution Satellite Images on Improving Geographic Maps
Abstract: By integrating high-resolution satellite images into pre-existing mapping frameworks, this study tackles the problem of guaranteeing correctness and dependability in geospatial data updates. The main goal is to assess which satellite imagery sources—SuperView, Ikonos, QuickBird, and WorldView—are appropriate for updating maps at 1:2500 and 1:5000 scales. The process entails evaluating radiometric quality, geometric dependability, spatial correctness, and picture resolution and comparing the results to the specifications of different mapping tasks. …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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Fusion of deep learning autoencoders with random forest for wetland classification using Sentinel-2A data: A case study on Sirpur wetland
Abstract: Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied. These inputs sets comprise the reconstructed data through compression of original 13 bands into 4 bands using decoder algorithm, first four Principal Components, all spectral bands, and spectral indices. Random Forest classifier (RF) is used to …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 25–35 Read article