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Kankare, V., Vastaranta, M., Holopainen, M., Raty, M., Yu, X., Hyyppa, J., Hyyppa, H., Alho, P. and Viitala, R. (2013) Retrieval of Forest Aboveground Biomass and Stem Volume with Airborne Scanning LiDAR. Remote Sensing, 5, 2257-2274.
http://dx.doi.org/10.3390/rs5052257

has been cited by the following article:

• TITLE: Estimation of Tropical Forest Structural Characteristics Using ALOS-2 SAR Data

  AUTHORS: Luong Viet Nguyen, Ryutaro Tateishi, Hoan Thanh Nguyen, Ram C. Sharma, Tu Trong To, Son Mai Le

  KEYWORDS: Forest Structure, Forest Biomass, SAR, ALOS-2, Backscattering Intensity, Sensitivity Analysis

  JOURNAL NAME: Advances in Remote Sensing, Vol.5 No.2, June 27, 2016

  ABSTRACT: The potential of ALOS-2 SAR data for the estimation of tropical forest structural characteristics was assessed in Vietnam by collecting forest inventory data. The effect of polarization and seasonality of the SAR data on the estimation of forest biomass was analyzed. The combination of HH, HV, and HH/HV polarizations using multiple linear regression did not improve the estimation of biomass compared to using the HV channel independently, as the HH and HH/HV variables were not statistically significant. The dry season HV backscattering intensity was highly sensitive to the biomass compared to the rainy season backscattering intensity. The SAR data acquired in the rainy season with humid and wet canopies was not very sensitive to the biomass. The strong dependence of the biomass estimates with the season of SAR data acquisition confirmed that the choice of right season SAR data is very important for improving the satellite based estimates of the biomass. The validation results showed that the dry season HV polarization could explain 54% variation of the biomass.