DOI: https://doi.org/10.14710/geoplanning.12.1.%25p

Land Cover Classification of Indonesian Archipelago Using Digital Spectroscopy to Support Spatial Planning in Indonesia

*Guntur Bagus Pamungkas orcid scopus publons  -  Study Program of Urban and Regional Planning, Faculty of Science and Technology, Universitas Terbuka, Indonesia
Muhammad Reffi Firmansyah  -  Study Program of Urban and Regional Planning, Faculty of Science and Technology, Universitas Terbuka, Indonesia
Ratna Sari  -  Study Program of Urban and Regional Planning, Faculty of Science and Technology, Universitas Terbuka, Indonesia
Anindya Putri Tamara  -  Study Program of Urban and Regional Planning, Faculty of Engineering, Universitas Semarang, Indonesia
Zainul Rahadian orcid scopus  -  Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Negeri Padang, Indonesia

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Abstract

In the context of urban and regional planning, this study aims to produce land classification products covering 230 pathrows throughout Indonesia, which can be 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 that include water bodies, vegetation canopies, green open spaces, vacant land, settlements, and built-up areas, as well as additional classifications of cloud cover, provide a comprehensive overview of land conditions in Indonesia. The results of this classification are then verified through field observation surveys to ensure their accuracy and validity. The output of this research is a land classification product that can be used as an important tool in project-based learning and planning studio courses. With target users that include students, practitioners, and academics, this product can be an invaluable support in land cover analysis for various research and planning projects in various fields. In addition, this study offers a more potential alternative in 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 in supporting natural resource planning and management as well as infrastructure development and sustainable development policies in Indonesia.

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Keywords: Spectroscopy; Remote Sensing; Project-Based Learning
Funding: LPPM of Universitas Terbuka under contract PN2022-00003845

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Section: Original Research
Language : EN
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