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All Journal Jurnal Ilmu Dasar
Darmawan, Sukma Adi
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Control & Systems Engineering Mathematics

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Crops Classification in Fragmented Agricultural Land Using Integrated Radar and Optical Remote Sensing Satellite Data Darmawan, Sukma Adi; Cahyono, Bowo Eko; Suprianto, Agus; Umniyah, Inas Alfiyatul
Jurnal ILMU DASAR Vol. 26 No. 2 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v26i2.53691

Abstract

This study aims to classify crops on fragmented agricultural land by integrating radar (Sentinel-1) and optical (Sentinel-2) satellite remote sensing data. The research responds to the pressing issue of decreasing agricultural land in Jember Regency due to land conversion, which threatens food security. Feature-level fusion is applied to combine spectral indices (NDVI, NDWI, NDBI) from Sentinel-2 and radar backscatter characteristics (VV, VH) from Sentinel-1. Classification was performed using the Random Forest algorithm in the Google Earth Engine (GEE) platform. The results showed that the combination of both datasets provided high overall accuracy (81.58%) in classifying eight land cover types including agricultural crops such as paddy, corn, sugarcane, and citrus. This integration enables better monitoring of complex agricultural landscapes, offering a practical tool for sustainable land management.
Co-Authors Cahyono, Bowo Eko Suprianto Suprianto Umniyah, Inas Alfiyatul