Publications

Dong, YD; Jiao, ZT; Cui, L; Zhang, H; Zhang, XN; Yin, SY; Ding, AX; Chang, YX; Xie, R; Guo, J (2019). Assessment of the Hotspot Effect for the PROSAIL Model With POLDER Hotspot Observations Based on the Hotspot-Enhanced Kernel-Driven BRDF Model. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 57(10), 8048-8064.

Abstract
The hotspot effect is a typical angular reflectance signature of vegetation canopies and contains important information for the retrieval of vegetation structural parameters. To date, the hotspot effect of various analytical bidirectional reflectance distribution function (BRDF) models (e.g., the PROSAIL model) has rarely been assessed by multiangular measurements with sufficient hotspot observations due to the lack of accurate hotspot measurements (for field measurements) or appropriate methods (for airborne and spaceborne measurements). In this paper, we develop a method to further improve the hotspot effect of the kernel-driven model and design a framework to utilize the improved kernel-driven model as a bridge to assess the hotspot effect of the PROSAIL model with Polarization and Directionality of the Earth Reflectance (POLDER) hotspot observations. The results indicate that the proposed method further improves the fits between the models and the observations in the vicinity of the hotspot direction, particularly in the rare situations where the geometric-optical scattering component governs the target reflectance. In addition, the hotspot signature indicated by the PROSAIL multiangular data shows a larger variability than that of POLDER observations. C-1 and C-2 in the improved kernel-driven model can be used as benchmarked parameters to qualify the amplitude and width of the hotspot effect for the simulated multiangular data of physical BRDF models and thus present the potential for the assessment and analysis of the hotspot effect of physical models, which, in return, helps retrieve the structural parameters of vegetation canopies from hotspot signatures.

DOI:
10.1109/TGRS.2019.2917923

ISSN:
0196-2892