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Open AccessArticle

Tropical PeatLand Forest Biomass Estimation Using Polarimetric Parameters Extracted from RadarSAT-2 Images

1
Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi, Inage, Chiba 263-8522, Japan
2
Faculty of Mathematics and Natural Sciences, Padang State University, Jalan, Air Tawar Padang, Sumatera Barat 25111, Indonesia
*
Author to whom correspondence should be addressed.
Land 2020, 9(6), 193; https://doi.org/10.3390/land9060193
Received: 2 May 2020 / Revised: 4 June 2020 / Accepted: 7 June 2020 / Published: 10 June 2020
(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)
This paper was aimed at estimating the forest aboveground biomass (AGB) in the Central Kalimantan tropical peatland forest, Indonesia, using polarimetric parameters extracted from RadarSAT-2 images. Six consecutive acquisitions of RadarSAT-2 full polarimetric data were acquired and polarimetric parameters were extracted. The backscattering coefficient ( σ o ) for HH, HV, VH, and VV channels was computed respectively. Entropy (H) and alpha ( α ) were computed using eign decomposition. In order to understand the scattering behavior, Yamaguchi decomposition was performed to estimate surface scattering ( γ s u r f ) and volume scattering ( γ v o l ) components. Similarly following polarimetric indices were computed; Biomass Index (BMI), Canopy Structure Index (CSI), Volume Scattering Index (VSI), Radar Vegetation Index (RVI) and Pedestal Height ( p h ). The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence, and suitability for forest aboveground biomass estimation across rainy and dry conditions. Regression analysis was performed between referenced biomass measurements and polarimetric parameters; VSI, H, RVI, p h , and γ v o l were found significantly correlated with AGB. Biomass estimation was carried out using significant models. Resultant models were validated using field-based AGB measurements. Validation results show a significant correlation between measured and referenced biomass measurements with temporal consistency over the acquisition time period. View Full-Text
Keywords: forest biomass; polarimetric parameters 2; radar vegetation index (RVI); volume scattering index (VSI); canopy structure index (CSI) forest biomass; polarimetric parameters 2; radar vegetation index (RVI); volume scattering index (VSI); canopy structure index (CSI)
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Waqar, M.M.; Sukmawati, R.; Ji, Y.; Sri Sumantyo, J.T. Tropical PeatLand Forest Biomass Estimation Using Polarimetric Parameters Extracted from RadarSAT-2 Images. Land 2020, 9, 193.

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