Advances of Remote Sensing in Land Cover and Land Use Mapping
Résumé
Understanding and monitoring land use and land cover (LULC) dynamics have become increasingly critical in the face of mounting socio-economic, political, and environmental challenges, including climate change, urbanization, and resource degradation [1,2]. Effective spatial planning and sustainable development strategies necessitate the integration of up-to-date information on land use and land cover changes, which are driven by complex interactions among climatic variability, demographic shifts, and economic transformations [3,4]. Addressing these challenges requires robust methods for observing, mapping, monitoring, analyzing, and modeling land surface processes. Remote sensing has emerged as a fundamental tool in this domain, benefiting from recent advances in artificial intelligence and machine learning, the expansion of Earth observation platforms, and the increasing availability of high resolution satellite and airborne data, often supplemented with ancillary geospatial datasets [5,6]. These developments have significantly enhanced the capacity to map, characterize, and interpret land cover and land use changes at various spatial and temporal scales for a variety of applications.
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