<![CDATA[In the context of urban and regional planning, this study aims to produce land classification products covering 230 paths/rows throughout Indonesia, which can serve as an important tool in supporting planning and research projects. The research method used combines remote sensing in Geographic Information Systems (GIS) with the utilization of spectroscopy through QGIS software with Dzetsaka plugins (semi-automatic classification tools). Land cover classifications, which include water bodies, vegetation canopies, green open spaces, bare grounds, settlements, and built-up areas, as well as additional classifications of cloud cover, provide a comprehensive overview of land conditions in Indonesia. Based on the results of the study, the average distribution of land classes reached 10,116. The standard deviation was 14,786, which shows the level of variation in the data against the average value, with the higher value indicating the most significant variation in land classification. This study offers a more potential alternative by using Landsat 8 OLI 2022 satellite imagery data from the USGS as a basis for a more in-depth and accurate analysis of land classification. Thus, the results of this study not only contribute to mapping and understanding land use in Indonesia but also provide useful tools for supporting natural resource planning and management, as well as infrastructure development and sustainable development policies in Indonesia]]>
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