Pendugaan Cadangan Karbon Biomassa Atas Padang Lamun di Tiga Pulau Kepulauan Liukang Tangaya Menggunakan Citra Satelit Sentinel-2A

Abstract

Padang lamun memiliki peran krusial sebagai penyerap karbon biru (blue carbon) untuk mitigasi perubahan iklim, namun rentan terhadap degradasi sehingga memerlukan pemetaan dan pedugaan cadangan karbon yang akurat. Penelitian ini bertujuan memetakan luasan habitat dan menduga total cadangan karbon biomassa atas (above-ground biomass) padang lamun di Area 3 KKP Liukang Tangaya menggunakan citra satelit Sentinel-2A. Pengolahan citra dilakukan melalui metode Object Based Image Analysis (OBIA) dengan algoritma Support Vector Machine (SVM) untuk klasifikasi habitat bentik. Transformasi Normalized Difference Vegetation Index (NDVI) diaplikasikan untuk memetakan kelas kerapatan lamun. Pendugaan karbon spasial diperoleh dengan mengalikan luas kelas kerapatan dengan rata-rata cadangan karbon hasil pengukuran lapang. Hasil pemetaan menunjukkan dominasi mutlak padang lamun oleh spesies Enhalus acoroides dan Thalassia hemprichii. Luasan padang lamun terpetakan mencapai 184.73 Ha di Pulau Satanger, 647.63 Ha di Pulau Aloang, dan 247.44 Ha di Gosong Pasir Satunggul, dengan nilai Overall Accuracy sebesar 67.50%. Secara akumulatif, Pendugaan total cadangan karbon biomassa atas tertinggi ditemukan di Pulau Aloang sebesar 17.19 tonC, diikuti oleh Gosong Pasir Satunggul sebesar 9.82 tonC, dan Pulau Satanger sebesar 5.51 tonC. Pemodelan spasial berbasis citra Sentinel 2A secara konsisten mampu merepresentasikan distribusi luasan dan menduga kapasitas simpanan karbon dari padang lamun di wilayah perairan dangkal.

Seagrass meadows play a crucial role as blue carbon sinks for climate change mitigation, yet they are vulnerable to degradation, thus requiring accurate mapping and carbon stock estimation. This study aims to map the habitat extent and estimate the total above-ground biomass carbon stock of seagrass in Area 3 of the Liukang Tangaya Marine Protected Area using Sentinel-2A satellite imagery. Image processing was conducted using the Object Based Image Analysis (OBIA) method with the Support Vector Machine (SVM) algorithm for benthic habitat classification. Furthermore, the Normalized Difference Vegetation Index (NDVI) transformation was applied to map seagrass density classes. Spatial carbon estimation was obtained by multiplying the area of density classes with the average carbon content from field measurements. The mapping results showed the absolute dominance of seagrass meadows by Enhalus acoroides and Thalassia hemprichii species. The mapped seagrass extent reached 184.73 Ha in Satanger Island, 647.63 Ha in Aloang Island, and 247.44 Ha in Satunggul Sandbank, with an Overall Accuracy of 67.50%. Cumulatively, the highest estimated total above-ground carbon stock was found in Aloang Island at 17.19 tonC, followed by Satunggul Sandbank at 9.82 tonC, and Satanger Island at 5.51 tonC. Spatial modeling based on Sentinel-2A imagery consistently represents the extent distribution and estimates the carbon storage capacity of seagrass meadows in shallow waters.