LiDAR imagery-based relief interpretation for soil organic carbon (SOC) estimation in the Quaternary Sumbing and Tertiary Kulon Progo Volcano Transition Zone, Central Java, Indonesia

Amida Mazaya Fuadah; Junun Sartohadi; Nur Ainun Harlin Jennie Pulungan

doi:10.17268/sci.agropecu.2025.046

Autores/as

Amida Mazaya Fuadah Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia. https://orcid.org/0009-0003-9058-0853
Junun Sartohadi Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia. https://orcid.org/0000-0002-0059-8335
Nur Ainun Harlin Jennie Pulungan Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia. https://orcid.org/0000-0002-9889-1600

DOI:

https://doi.org/10.17268/sci.agropecu.2025.046

Palabras clave:

Relief, LiDAR, soil organic carbon, volcanic transition zone

Resumen

Typically, the transition zone of quaternary and tertiary volcanoes is a potential area for agricultural development but is prone to landslides. Landslide occurrences and the use of former landslide zones exhibit a distinct soil organic carbon (SOC) distribution, necessitating analysis to sustain agricultural output. Laboratory SOC measurements on landscape size are not expedient, necessitating the development of an estimating method for representation. This study aims to analyze the relationship between relief and SOC using LiDAR (Light Detection and Ranging) data. LiDAR acquisition was carried out to identify relief units as units of analysis. Soil sample measurements were carried out in the laboratory with the parameters analyzed including pH, Bulk Density, Moisture Content, Organic Carbon, Organic Matter, N-total, CN Ratio and Cation Exchange Capacity. The results showed that SOC and relief had R² = 0.89 in the upper layer (0 – 20 cm) and 0.86 in the lower layer (20 - 40 cm). Relief has a high correlation with soil characteristics at the top and bottom of soil depths. It is because of relatively stable elevation and relatively dynamic land cover that SOC is spread out in a clustered way. This research can be used as a basis for agricultural land management, especially in areas prone to landslides.

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