TY - GEN
T1 - Comparison of the use of Sentinel-1 SAR and ALOS-2 PALSAR-2 in mangrove aboveground biomass estimation in San Juan, Batangas, Philippines
AU - Bilolo, J.J.
AU - Dida, J.V.
AU - Araza, A.
PY - 2024/4/24
Y1 - 2024/4/24
N2 - This study compares the potential of Sentinel-1 and ALOS-2 PALSAR-2 in estimating mangrove aboveground biomass (AGB) in San Juan, Batangas, Philippines. Mangrove forests are essential coastal ecosystems that are facing growing threats. One way of conserving them is by creating policies that can protect them. To do this effectively, information like AGB can be used as a guide. However, conventional AGB estimations are labor-intensive and ecologically disruptive. Conversely, remote sensing technologies, such as synthetic aperture radar (SAR), offer a more efficient alternative. Sentinel-1, operating in C-band, and ALOS-2 PALSAR-2, operating in L-band, are two prominent SAR platforms with global coverage, offering data for land cover classification, forest monitoring, and forest biomass estimation. This research used the backscatter values of Sentinel-1 and ALOS-2 PALSAR-2 as predictor variables in estimating mangrove AGB by correlating them to the observed AGB from a mangrove survey. The models developed using these platforms yielded limited accuracy, with low coefficient of determination (R2) (Sentinel-1 = 0.13; ALOS-2 PALSAR-2 = 0.12) and RMSE (Sentinel-1 = 8.72 Mg ha-1; ALOS-2 PALSAR-2 = 8.78 Mg ha-1). Potential sources of errors were identified, including small sample size and data noise. On the results, Sentinel-1 demonstrates a slightly better performance in terms of the R2 and RMSE in the modeling while ALOS-2 PALSAR-2 performed better in the validation, however, both still yielded suboptimal AGB estimates compared to other studies. Refining the models by incorporating additional parameters, exploring machine learning, and considering other data sources are recommended to enhance AGB estimation.
AB - This study compares the potential of Sentinel-1 and ALOS-2 PALSAR-2 in estimating mangrove aboveground biomass (AGB) in San Juan, Batangas, Philippines. Mangrove forests are essential coastal ecosystems that are facing growing threats. One way of conserving them is by creating policies that can protect them. To do this effectively, information like AGB can be used as a guide. However, conventional AGB estimations are labor-intensive and ecologically disruptive. Conversely, remote sensing technologies, such as synthetic aperture radar (SAR), offer a more efficient alternative. Sentinel-1, operating in C-band, and ALOS-2 PALSAR-2, operating in L-band, are two prominent SAR platforms with global coverage, offering data for land cover classification, forest monitoring, and forest biomass estimation. This research used the backscatter values of Sentinel-1 and ALOS-2 PALSAR-2 as predictor variables in estimating mangrove AGB by correlating them to the observed AGB from a mangrove survey. The models developed using these platforms yielded limited accuracy, with low coefficient of determination (R2) (Sentinel-1 = 0.13; ALOS-2 PALSAR-2 = 0.12) and RMSE (Sentinel-1 = 8.72 Mg ha-1; ALOS-2 PALSAR-2 = 8.78 Mg ha-1). Potential sources of errors were identified, including small sample size and data noise. On the results, Sentinel-1 demonstrates a slightly better performance in terms of the R2 and RMSE in the modeling while ALOS-2 PALSAR-2 performed better in the validation, however, both still yielded suboptimal AGB estimates compared to other studies. Refining the models by incorporating additional parameters, exploring machine learning, and considering other data sources are recommended to enhance AGB estimation.
KW - Aboveground Biomass Estimation
KW - ALOS-2 PALSAR-2
KW - Mangroves
KW - Remote Sensing
KW - Sentinel-1
U2 - 10.5194/isprs-archives-XLVIII-4-W8-2023-53-2024
DO - 10.5194/isprs-archives-XLVIII-4-W8-2023-53-2024
M3 - Conference paper
AN - SCOPUS:85198635514
T3 - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SP - 53
EP - 60
BT - Philippine Geomatics Symposium (PhilGEOS) 2023
A2 - Principe, J.A.
A2 - Tamondong, A.M.
A2 - Ang, M.R.C.O.
PB - ISPRS
T2 - 2023 Philippine Geomatics Symposium, PhilGEOS 2023
Y2 - 6 December 2023 through 7 December 2023
ER -