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9 articles for “Predicting land cover changes”
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Decision Fusion Approaches to Spatiotemporal Change Prediction in Satellite Images: A Comparative Study
Abstract: Predicting changes in satellite images remains one of the major challenges in the remote sensing field. However, this process is usually accompanied by several imperfections leading sometimes to erroneous decisions. In order to solve this problem, we propose to introduce knowledge discovery methods to improve the prediction process in satellite images and to decrease the associated imperfections. The proposed approach addresses this issue through the use of two fusion methods …
Published in Journal of Remote Sensing & GIS · Vol. 3, Issue 2, 2012 · pp. 13–23 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Identifying Trends in Landuse/Landcover Changes in Hisar Tehsil: A LCM Based Approach
Abstract: Land is a source of all basic human needs, (e.g., agriculture, forest, water supply etc.) which is being continuously depleted by various agents. Urban growth and urbanization are considered as one of the major factors responsible for change in landcover dynamics and depletion of land resources. As compared with other landcover classes such as agricultural land, urban land has smaller area coverage but its impact to the surrounding environment is …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 1–8 Read article
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Spatiotemporal Modeling of Soil Erosion Under Agricultural Expansion in the Amravati Basin, India Using RUSLE–GIS
Abstract: Agricultural expansion and soil erosion are important environmental issues in areas where agriculture is a major source of livelihood. This study analyzes the spatial and temporal patterns of soil erosion in the Amravati Basin of Maharashtra and evaluates the impact of agricultural expansion using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) techniques. Multi-source data, such as satellite imagery, rainfall records, soil characteristics, and topography …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 50–62 Read article
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Building a Resilient Climate Regulatory Ecosystem for Nigeria
Abstract: Terrestrial ecosystems, which store more carbon than the atmosphere, are vital to influencing carbon dioxide-driven climate change. Climate and land-use change are critical and interlinked components of the Carbon budget in human-dominated landscape, using the InVEST model maps of land use and stocks in four Carbon pools (aboveground biomass, belowground biomass, soil, dead organic matter) are used to estimate the amount of Carbon currently stored in the landscape and the …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 11, Issue 2, 2020 · pp. 46–62 Read article
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Satellite Sensing in Climate Change: A Study
Abstract: Satellite sensing has become an indispensable tool in the study of climate change, providing critical data that enhances our understanding of atmospheric, terrestrial, and oceanic processes. By employing advanced remote sensing technology, satellites facilitate the collection of extensive datasets on key climate indicators, such as temperature variations, greenhouse gas concentrations, and changes in land cover. This aerial perspective allows researchers to monitor large-scale environmental changes with unparalleled precision and consistency, …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 1, 2025 · pp. 10–19 Read article
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Innovations in Atmospheric Remote Sensing: From Satellites to Lidar and Beyond
Abstract: Atmospheric remote sensing plays a vital role in monitoring and understanding the Earth's atmosphere, providing essential data for climate studies, weather forecasting, and environmental management. This review discusses various remote sensing technologies, including satellites, radiometers, lidar, radar, and GPS radio occultation, each contributing unique capabilities for atmospheric observations. Satellite remote sensing allows for global coverage and continuous monitoring of atmospheric parameters, while ground-based systems enhance localized measurements. Key applications include …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 10–15 Read article
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Trend analysis of Normalized Difference Vegetation Index using Landsat Satellite data: Study from in and Gondar town, North West Ethiopia
Abstract: Abstract This current research study presents the change detection method for the study of Satellite image supported on Normalized Difference Vegetation Index (NDVI). NDVI utilizes the Multi-Spectral remote sensing data method to determine Vegetation Index, land cover classification, vegetation, water bodies, bush land, agricultural area, thick forest and thin forest with few bands grouping of the remote sensed data. Land resources are easily understood by calculating their Normalized Difference Vegetation …
Published in Journal of Control & Instrumentation · Vol. 10, Issue 3, 2019 · pp. 25–33 Read article
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Correlation between Enhanced Vegetation Indices and Rainfall Patterns of Kurnool District, Andhra Pradesh
Abstract: Vegetation indices enhance vegetation spectral signatures by combining bands of red (630–700 nm) and near-infrared wavelengths (700–1100 nm). This can be best suited to study vital activity of vegetation on land surface. Kurnool district is chosen to assess the capability of continuous spatial and temporal coverage; MODIS-derived enhanced vegetation indices (EVI) data were utilized to monitor the vegetation seasonal dynamics and their relationship with precipitation. Statistical analysis of mandal-wise mean …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 1, 2013 · pp. 7–12 Read article