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4 articles for “land use change detection”
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Assessing Land use Dynamics and Policies in the Waghur Basin Using Geospatial Techniques
Abstract: Changes in land use and land cover (LULC) are key indicators of human–environment interactions, especially in river basins where anthropogenic pressure is increasing. This study evaluated land use change and policy implications in the Waghur Basin, India, through a geospatial analysis of 35 years (1990–2025). Remote sensing and GIS-based supervised classification with the help of machine learning methods were applied to multi-temporal Land satellite images to create LULC maps and …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 38–49 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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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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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article