Aplikasi Teknologi Drone dan Pendekatan OBIA Dalam Studi Idenifikasi Habitat Perairan Dangkal
Abstract
ABSTRAK
Habitat perairan dangkal memiliki peran penting dalam menjaga keseimbangan ekosistem laut dan mendukung keberlanjutan sumber daya perikanan. Namun, pemahaman dan pemantauan yang efektif terhadap habitat ini menjadi semakin krusial dalam menghadapi tantangan lingkungan yang semakin kompleks. Artikel ini mengungkapkan penelitian yang bertujuan untuk mengidentifikasi habitat perairan dangkal dengan memanfaatkan teknologi drone dan pendekatan Object-Based Image Analysis (OBIA). Inovasi utama dalam penelitian ini adalah penggunaan drone untuk pemetaan habitat perairan dangkal, yang menghadirkan metode yang lebih efisien dan akurat dibandingkan dengan survei konvensional. Metode OBIA digunakan dalam pengolahan data citra drone, dengan dukungan Ground Truth Habitat dan analisis algoritma SVM. Hasilnya, tingkat akurasi keseluruhan mencapai 77%, dengan tingkat akurasi tertinggi untuk Lamun sebesar 22,6% dan terendah untuk karang mati sebesar 4,1%. Penggunaan user's accuracy juga mencerminkan hasil yang bervariasi, dengan akurasi tertinggi untuk Lamun sebesar 91% dan terendah untuk karang mati sebesar 54%. Penelitian ini memberikan kontribusi penting dalam pemahaman lebih dalam tentang habitat perairan dangkal, memfasilitasi pemantauan yang lebih efektif, dan memberikan landasan untuk upaya konservasi lebih lanjut di ekosistem perairan dangkal.
Kata Kunci: Drone, OBIA, penginderaan jauh, SIG, pesisir
ABSTRACT
Shallow water habitats play a crucial role in Maintaining marine ecosystem balance and supporting sustainable fisheries resources. However, effective understanding and monitoring of these habitats have become increasingly critical in the face of complex environmental challenges. This article unveils research aimed at identifying shallow water habitats using drone technology and an Object-Based Image Analysis (OBIA) approach. The primary innovation in this study lies in the utilization of drones for shallow water habitat mapping, presenting a more efficient and accurate method compared to conventional surveys. OBIA methods were employed in processing drone image data, supported by Ground Truth Habitat and SVM algorithm analysis. The overall accuracy reached 77%, with the highest accuracy rates for Seagrass at 22.6% and the lowest for Dead Coral at 4.1%. User's accuracy usage also reflected varied results, with the highest accuracy for Seagrass at 91% and the lowest for Dead Coral at 54%. This research makes a significant contribution to a deeper understanding of shallow water habitats, facilitating more effective monitoring and providing a foundation for further conservation efforts in shallow water ecosystems.
Keywords: Drone, OBIA, remote sensing, GIS, coastal
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DOI: https://doi.org/10.21107/jk.v17i2.22313
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Published by: Department of Marine Sciences, Trunojoyo University of Madura