Deteksi Kadar Air dan Kadar C-organik Tanah Menggunakan Wahana Tanpa Awak Multisensor

Abstract

Penentuan bahan organik dan kadar air tanah melalui analisis laboratorium perlu melalui prosedur panjang dan bersifat destruktif. Upaya estimasi kadar bahan organik dan C-organik menggunakan pendekatan penginderaan jauh perlu terus didorong agar lebih cepat, non desktruktif, dan berbasis spasial. Menduga kadar C-organik dan kadar air tanah menjadi salah satu sebagai upaya mempromosikan praktik pertanian presisi juga sebagai bahan evaluasi bagi petani. Penggunaan unmanned aerial vehicle (UAV) yang dilengkapi dengan kamera multispectral dan thermal memungkinkan pemantauan secara efisien dan near real-time dalam monitoring bahan organik dan kadar air tanah. Penelitian ini bertujuan mengidentifikasi hubungan serta mengamati korelasi antara nilai NDWI, kanal spektral serta suhu terhadap kadar C-organik dan kadar air tanah hasil pengukuran laboratorium, dan Membuat prediksi sebaran spasial kadar C-organik dan kadar air tanah dari model persamaan. Hasil penelitian menunjukkan kanal red-rdge merupakan indikator spektral paling efektif dalam menjelaskan variasi kadar C-organik tanah, sementara kanal NIR menunjukkan pengaruh paling kuat terhadap kadar air tanah. Sebaliknya, indeks NDWI memiliki hubungan yang sangat lemah terhadap C-organik dan kadar air tanah serta kurang dapat dijadikan sebagai prediktor. Suhu permukaan tanah tidak berpengaruh signifikan terhadap kadar C-organik, namun memiliki hubungan negatif yang kuat dengan kadar air tanah.

The determination of organic matter and soil moisture content through laboratory analysis requires lengthy and destructive procedures. Efforts to estimate organic matter and soil organic carbon (SOC) content using remote sensing approaches need to be continuously promoted to achieve faster, non-destructive, and spatially based methods. Estimating SOC and soil moisture content serves not only as an effort to promote precision agriculture practices but also as a valuable evaluation tool for farmers. The use of unmanned aerial vehicles (UAV) equipped with multispectral and thermal cameras enables efficient and near real-time monitoring of soil organic matter and soil moisture content. This study aims to identify relation and examine correlations between NDWI values, spectral bands, and temperature with laboratory measured SOC and soil moisture content, as well as to develop spatial distribution predictions of SOC and soil moisture content using equation models. The results indicate that the red-edge band is the most effective spectral indicator in explaining variations in soil organic carbon, while the NIR band shows the strongest influence on soil moisture content. In contrast, the NDWI index demonstrates a very weak relation with SOC and soil moisture content, making it less reliable as a predictor. Soil surface temperature does not significantly affect SOC levels but shows a strong negative relation with soil moisture content.