Abstract: Satellite images are commonly used to monitor land use land cover (LULC) changes. Unfortunately, publicly available images often lack the resolution required for detailed urban studies. In ...

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A Google Earth Engine Land use (crops) classification workflow using Random Forest, one year of ground data, Sentinel-2, and Landsats; to produce multiyear annual 30-m crop maps This project focuses ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

Land use and land cover (LULC) analysis has become increasingly significant in environmental studies due to its direct impact on the environment. Changes in LULC affect the ecological and climatic ...

This work will present the challenges in using quantum-enhanced support vector machines (QSVM) for classification tasks on multi-spectral Earth Observation (EO) data. The main areas of investigation ...

Introduction: This study delves into the spatiotemporal dynamics of land use and land cover (LULC) in a Metropolitan area over three decades (1991–2021) and extends its scope to forecast future ...

1 Laboratoire Eau, Energie, Environnement, Ecole Nationale d’Ingénieurs de Sfax, Sfax, Tunisia. 2 Faculte des Sciences de Gafsa, Campus Universitaire, Gafsa, Tunisia. 3 Geoengine, Geomatics and ...