UTILIZING REMOTE SENSING AND MACHINE LEARNING FOR ECOSYSTEM SERVICES MAPPING AT GUNUNG MAS TEA PLANTATION

Authors

  • Annisa Fitria Department of Geography, Faculty of Mathmatics and Natural Sciences, University of Indonesia
  • Masita Dwi Mandini Manessa Department of Geography, Faculty of Mathmatics and Natural Sciences, University of Indonesia
  • Rudy Parluhutan Tambunan Department of Geography, Faculty of Mathmatics and Natural Sciences, University of Indonesia

DOI:

https://doi.org/10.30536/j.ijreses.2023.v20.a3880

Keywords:

AHP, Ecosystem Services, Land Use and Land Cover, Supervised classification, Tea

Abstract

Land use and land cover changes are one of the main factors affecting ecosystems and the services they provide. Conversion from natural vegetation to agricultural and urban land can lead to the degradation of ecosystem services and loss of biodiversity. Puncak area, Bogor, which is a highland area, has become an area that is synonymous with tea plantations because it has an ecosystem that is suitable for being a tea plantation area. Gunung Mas tea plantation managed by PTPN VIII is one of the largest tea plantations and a contributor to foreign exchange in Indonesia. The tourism potential in the plantation and agricultural business sectors has a high selling value as a tourist object and attraction. The purpose of this study is to find out the distribution of ecosystem services for climate regulation, water flow and flood regulation, and ecotourism and cultural recreation services at Gunung Mas tea plantation which is displayed in the form of an Ecosystem Service Map. The land cover classification was extracted from the Sentinel 2A image, which was then scored based on expert judgment. The scoring results are then processed using the AHP Pairwise Comparison method. The results of the study show that the research area has very high climate regulation ecosystem services, very high water flow and flood regulation, and high cultural recreation and ecotourism ecosystem services.

 

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Published

2025-11-25

Issue

Vol. 20 No. 2 (2023)

Section

Articles

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Copyright (c) 2023 Author (S)

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