Estimasi Simpanan Karbon Tegakan Menggunakan Citra Sentinel-2A Pada Kawasan Mangrove Labuan Tereng Kabupaten Lombok Barat

Abstract

The primary worry in addressing climate change problems is the elevation in global temperatures resulting from the growing levels of CO2 emissions in the atmosphere. Mangrove ecosystems contribute to the "blue carbon" plan which is capable of storing carbon well, this research was conducted to assess carbon storage within the mangrove forest ecosystem by combining Sentinel-2A satellite imagery with on-site field measurements. The data analysis findings indicate the presence of six distinct mangrove varieties, namely R. mucronata, A. marina, R. apiculata, S. alba, E. agallocha, and C. decandra. The R. mucronata type is the type that dominates the mangrove area with an average carbon amount of 122.1 tonnes/ha. Correlation analysis shows a strong relationship between IKVm and mangrove forest carbon stocks, with a correlation coefficient value of 80%. In the regression model, the power model provides the best equation for estimating carbon stocks with a coefficient of determination value of 64.4% giving a model equation of y = 109.51x1.2381. Analysis of image carbon reserves obtained the lowest value, namely 0.02-10.46 tonnes/ha which was in the very rare vegetation density type and the highest carbon reserve value was 58.30-59.02 tonnes/ha in the very high density class.

Analisis Komparatif Tutupan Mangrove Menggunakan Citra Landsat 9 dan Sentinel 2A di Desa Labuan Tereng Kabupaten Lombok Barat

“…indeks vegetasi yang digunakan memiliki nilai piksel yang menjelaskan terkait kondisi vegetasi mangrove. Semakin tinggi nilai indeks vegetasi maka menandakan vegetasi dengan tingkat kerapatan yang tinggi (Hambali et al 2023). Gambar hasil pengolahan citra Landsat 9 dan Sentinel 2A untuk setiap transformasi indeks vegetasi mangrove dapat dilihat sebagai berikut: Dari hasil pengolahan citra Landsat 9 dan Sentinel 2A yang telah dilakukan dalam menganalisis beberapa model indeks vegetasi mangrove yaitu NDVI, SAVI, dan ARVI, didapatkan perbedaan yang secara signifikan baik secara visual peta ataupun nilai indeks vegetasi.…”