Assessment of dual polarization in Sentinel-1 data for estimating forest aboveground biomass: case study of Barru Regency, South Sulawesi

Ananto, Wahyu Hendardi Giri; Hadi, Haeydar Anggara; Putri, Ade Febri Sandhini; Hanum, Difa Nisrina; Wiryawan, Bayu Kurnia Puji; Prabaswara, Rifqi Rizaldy; Arjasakusuma, Sanjiwana

doi:10.1117/12.2540845

Cited by 1 publication

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“…In this study, the low correlated R² value of 0.11 means that Sentinel-1 data can only affect 11% of surface carbon estimates, while other variables influence the remaining 89%. The low correlation value of radar data can be affected by saturation in the vegetation canopy, making radar wave sensitivity weak in predicting biomass (Ananto et al, 2019).…”

Section: Sentinel-1 Carbon Estimationmentioning

confidence: 99%

“…Based on the advantages and disadvantages possessed by optical and radar imagery data, this study tried to compare the multisensor imagery data of Sentinel-1 (radar) and Sentinel-2 (optics) to predict the value of mangrove surface carbon stock. Sentinel-1 and Sentinel-2 images have the potential for mangrove observations, namely with 13 multispectral channels with three red edge channels sensitive to vegetation and crosspolarization of VV VH radar data related to vegetation structure (Alan et al, 2017;Ananto et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Mapping Mangrove Surface Carbon Stocks Using Multisensor Imagery in Clungup Mangrove Conservation (Cmc) Malang Regency

Hakim

Kamal

Arjasakusuma

2022

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Mangroves can store carbon effectively with a value of about 1,023 Mg C/Ha and become one of the richest forests that store 4-20 billion tons of blue carbon globally. Remote sensing imagery can be used to map mangrove surface carbon stocks using radar and optical image sensors. Generally, forest carbon on earth is stored in two places, namely above the surface (Above Ground Carbon, AGC) and below the surface (Below Ground Carbon, BGC). This study aims to estimate the surface carbon stock of mangroves using multisensory imagery using the Random Forest method in the Clungup Mangrove Conservation (CMC) area, Malang Regency, East Java. Four vegetation indices (IRECI, NDI45, NDVI, SAVI), single band, and VV VH polarization were used as predictive variables. Estimating the carbon stock mangrove value using Sentinel-1 imagery produced 2,126 tons of C with R² 0.11. Meanwhile, Sentinel-2 produces an estimated carbon value of 2,025 tons C with an R² of 0.22. The estimation model using Sentinel-2 shows a better evaluation value with a Root Mean Squared Error (RMSE) of 0.89 and a Mean Absolute Error (MAE) of 0.75. The IRECI vegetation index is the most important variable in estimating carbon stocks. The results of the mapping accuracy of the Sentinel-1 model show a value of 34.73% and Sentinel-2 35.03%.Keywords: Mangrove, Carbon, Sentinel-1, Sentinel-2, Random Forest

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Section: Sentinel-1 Carbon Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%