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All Journal Journal of Tropical Soils JTSL (Jurnal Tanah dan Sumberdaya Lahan) Journal of Degraded and Mining Lands Management Agriprima : Journal of Applied Agricultural Sciences Caraka Tani: Journal of Sustainable Agriculture Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal HPT (Hama Penyakit Tumbuhan)
Istika Nita
Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Engineering Environmental Science Social Sciences Other

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New Emerging and Comprehensive Land Mapping Unit at Detailed Scale: Integrating Random Forest Analysis and Remote Sensing Techniques for Sustainable Land Management Putra, Aditya Nugraha; Ustiatik, Reni; Prasetya, Novandi Rizky; Adara, Erza Aulia; Nita, Istika; Hadi, Syamsu Ridzal Indra; Soemarno, Soemarno; Sudarto, Sudarto; Utami, Sri Rahayu; Munir, Mochammad; Rayes, Mochtar Lutfi
Caraka Tani: Journal of Sustainable Agriculture Vol 40, No 3 (2025): July
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/carakatani.v40i3.97530

Abstract

Precise and detailed land mapping is essential for sustainable land management, environmental conservation, and regional planning, especially in complex and diverse landscapes. This study aims to present an innovative framework for the development of Land Mapping Units (LMUs) at a detailed scale (1:20,000), through the integration of Random Forest (RF) analysis and high-resolution remote sensing data. This study was conducted in the South Malang Plateau, Indonesia (the area characterized by karst, tectonic, volcanic, and alluvial landforms) from June to December 2024. As part of the methodology, the study utilized a combination of geospatial data, including geological maps, DEM-derived topographical indices, and remote sensing indices (Normalized Difference Soil Index/NDSI, Soil Adjusted Vegetation Index/SAVI, Normalized Difference Water Index/NDWI, Modified Soil Adjusted Vegetation Index/MSAVI). A total of 10,903 field observation points were analyzed, with 70% used for model training and 30% for validation. The results show that RF-based LMUs achieved R2 of 0.93 and Root Mean Square Error (RMSE) of 0.645, which is reliable to use. The LMUs provide a comprehensive understanding of landform-specific characteristics, including soil fertility linked to parent material, erosion sensitivity, and slope variability. These insights support applications in precision agriculture, disaster mitigation, and environmental planning. Moreover, the result can guide informed decision-making to prioritize sustainable land management that effectively prevents land degradation in the South Malang Plateau region, as stated in the Sustainable Development Goals (SDGs). The study demonstrates the potential of combining machine learning and remote sensing to refine spatial analysis and address the limitations of manual mapping methods. The proposed framework is scalable and adaptable to other diverse landscapes, making it a valuable tool for advancing sustainable land management in a rapidly changing world.
Co-Authors Achmad Bima Fauzi Achmad Wildanul Khakim Adara, Erza Aulia Adelyanti, Martiana Aditya Nugraha Putra Aditya Nugraha Putra, Aditya Nugraha Aditya Putra Aksha Karunia Satria Albert Fernando Sitorus Alberth Fernando Sitorus Alia Fibrianingtyas Alia Fibrianingtyas Alia Fibrianingtyas Andriyanto, Chandra Anggraini Aurina Putri Anggraini Aurina Putri Awang Satya Kusuma Ayuningtyas, Priska Deffi Armita Dekan Rahmat Wahyudianto Elina Endang Listyarini Fikri Hadi Rusdianto Hadi, Syamsu Ridzal Indra Hana Kusumawati Hanifah Ainur Dienna Hayyuna Khairina Albayani Ivena Hafshah Khairunnisa Kristiawati, Wanda Kurniawan Sigit Wicaksono Kurniawan Sigit Wicaksono Kurniawan Sigit Wicaksono, Kurniawan Sigit Luqmanul Hakim Martiana Adelyanti Melati Julia Rahma Michelle Talisia Sugiarto Michelle Talisia Sugiarto Mochammad Munir Mochtar Lutfi Rayes Mochtar Lutfi Rayes Mochtar Luthfi Rayes Mualif Adi Saputra Muhamad Taufiq Hidayat Naafi Tiara Windari Novandi Rizky Prasetya Novandi Rizky Prasetya Nurhutami, Shofie Rindi Prasetya, Novandi Rizky Prasetyo Adi Nugroho Priska Ayuningtyas Qoid Luqmanul Hakim Reza Muhammadi Riza, Sativandi Rony Irawanto Rosy Lesmono Putri S Sudarto Sativandi Riza Sektiono, Antok Wahyu Sena Rizki Triyudanto Sitorus, Albert Fernando Soemarno Soemarno Sri Agustiningsih Sri Rahayu Utami Sri Rahayu Utami Sudarto Sudarto Sudarto Sudarto Sudarto Sugeng Prijono Syamsu Ridzal Indra Hadi Ustiatik, Reni Widianto Widianto Zaenal Kusuma Zaenal Kusuma Zaenal Kusuma