期刊
REMOTE SENSING OF ENVIRONMENT
卷 115, 期 9, 页码 2184-2203出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2011.04.012
关键词
BRDF; Surface albedo; Cloud Absorption Radiometer; MODIS; CLASIC'07; ARM Climate Research Facility; US Southern Great Plains; Linear model; Inversion; A priori knowledge; 6S; AERONET; Spatial analysis; APU; Airborne measurements; Multiangle remote sensing; EOS land validation core sites
资金
- Science Mission Directorate of the National Aeronautics and Space Administration
- Earth Observing System
- Radiation Sciences Program
- Airborne Science Program
- NASA [NNX08AF89G, NNX07AT35H, NNX08AE94A]
- U.S. Department of Energy (DOE) [DOE-DE-FG02-06ER64178]
- NASA [NNX08AF89G, 101022] Funding Source: Federal RePORTER
Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities impacted by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained similar to 1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 degrees off-nadir, and at spatial resolutions ranging from 3 m to 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a land cover type-specific a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution: and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure. Published by Elsevier Inc.
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