Above Ground Carbon Estimation Using Sentinel-1B RADAR Satellite Imagery

Abstract

Mangroves are an important forest ecosystem in Indonesia because mangroves are known to have the ability to store high carbon. The use of remote sensing technology can be used to estimate the distribution of carbon content. The advantage of using radar satellite imagery such as Sentinel-1b is its ability to penetrate clouds. Satellite images produced from radar satellites are cloud-free satellite images. The purpose of this study was to obtain information on the spatial distribution of above-ground carbon (AGC) using the Sentinel-1b radar satellite imagery in the Karang Gading dan Langkat Timur Laut Wildlife Reserve. Regression is used to estimate the distribution of AGC based on the backscattering values of VH, VV, VV/VH, VV-VH, and VV+VH. The results showed that the carbon distribution in the best model was 45.02 tons ha-1 to 222.16 tons ha-1. The quadratic regression model with VV-VH backscatter is the best model for estimating AGC with a value of R2 = 0.374, and the value of Root Mean Square Error (RMSE) value of 19.083 ha/ton.

Identification of mangrove forests using Sentinel-1 Synthetic Aperture Radar (SAR) satellite imagery in Medan Belawan District, Medan City

“…Each class's probability value is given, assuming the homogeneous object will describe a histogram with a normally distributed distribution. Pixel values are classified based on size, orientation, and shape at image distance [12].…”

“…To identify mangrove forests, Synthetic Aperture Radar (SAR) data is used in remote sensing techniques [8]. In addition, the use of SAR can also be used as a carbon estimate above to gain a better understanding [12].…”