Can Polarimetric Radarsat-2 Images Provide a Solution to Quantify Non-Photosynthetic Vegetation Biomass in Semiarid Mixed Grassland?. Issue 6 (2nd November 2017)

• Record Type: Journal Article
• Authors: Li, Zhaoqin; Guo, Xulin
• Is Part Of: Canadian journal of remote sensing. Volume 43:Issue 6(2017)
• Page Start: 593
• Page End: 607
• Publication Date: 2017-11-02
• Subjects: Remote sensing -- Periodicals; 621.367805
• DOI: 10.1080/07038992.2017.1394181
• Languages: English
• ISSNs: 0703-8992

Abstract

ABSTRACT: Quantifying non-photosynthetic vegetation (NPV) biomass using optical remote sensing in semiarid mixed grassland is challenging. This is due to the combined effects of photosynthetic vegetation, biological soil crust, and bare soil on the canopy spectra. Radarsat-2 provides a new way to quantify NPV biomass. This study investigated the potential of fine quad-pol Radarsat-2 images for quantifying NPV biomass and total aboveground biomass in semiarid mixed grasslands. The parameters used were Radar Vegetation Index, co-polarization ratio (HH/VV), cross-polarization ratios (VH/HH and VH/VV), de-polarization ratio, the Cloude and Pottier decomposition component (Entropy and Alpha angle) and the Freeman-Durden decomposition components (volume, surface, and multiple scattering). The best NPV and total aboveground biomass estimations are achieved with an r 2 of 0.70 and 0.51 and relative root mean square error (rRMSE) of 9% and 8.4%, respectively, using the VH/VV cross-polarization ratio of the FQ23 (41.9°–43.3°) image in the middle growing season. The r 2 values are 0.65 and 0.70 and the rRMSE are 12.6% and 8.4%, respectively, for NPV and total biomass estimation using the depolarization ratio of the FQ3 (20.9°–22.9°) image in the peak growing season.