期刊
REMOTE SENSING OF ENVIRONMENT
卷 152, 期 -, 页码 547-556出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2014.06.007
关键词
anisotropy; hyperspectral; multi-angular; Senegal; spectro-directional; vegetation indices
资金
- Danish Council for Independent Research (DFF) Sapere Aude program
This paper presents the Dahra field spectrometer system (DAFIS) sited in Senegal, West Africa. DAFIS is a unique system that automatically measures the spectro-directional reflectance properties of a semi-arid savanna in the spectral range of 350-1800 nm, daily from sunrise to sunset. The instrumental setup allows studying surface anisotropy for different phenological phases. First data retrieved from the Dahra field spectrometer system show distinctive patterns of spectrally dependent anisotropic behavior: during the rainy season normalized reflectance was highest around solar noon for small off-nadir observation angles but for observations of large off-nadir angles highest values were found in the morning or evening hours (both forward and backward scatter direction). Anisotropy factors corresponding to MODIS, SPOT and SEVIRI red, near-infrared (NIR) and shortwave-infrared (SWIR) sensor response functions indicated little influence of the anisotropic behavior for savanna but vegetation indices including red/NIR (NDVI) and NIR/SWIR (SIWSI) were found to be sensitive to the view angle (NDVI and SIWSI varied by 5 and 41 %, respectively). Surprisingly, the influence from differences in shading (analyzed by measurements from forward and backward scatter direction) did not have a noticeable impact on the indices (0.2% and 0.5% difference for NDVI and SIWSI in the backward and forward scatter direction, respectively). The presented data show the large potential of continuous time series collected with the DAFIS system for monitoring of plant spectro-directional behavior in semi-arid African savanna for quantitative evaluation of satellite or airborne remote sensing data or development of new Earth Observation (EO) based indices and algorithms to monitor vegetation status or stress. (C) 2014 Elsevier Inc. All rights reserved.
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