Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5754811 | Remote Sensing of Environment | 2017 | 12 Pages |
Abstract
This paper presents a new algorithm to simultaneously retrieve Aerosol Optical Depth (AOD) and land surface Bidirectional Reflectance Distribution Function (BRDF) from Advanced Along-Track Scanning Radiometer (AATSR) by adopting gradient optimization method. Different from traditional method the approach presented here can perform simultaneous retrieval from each individual AATSR swath rather than multiple days. A theoretical sensitivity study proves the proposed method is insensitive to the distortion of initial BRDF. The presented algorithm is tested on AATSR data around four different Aerosol Robotic Network (AERONET) sites representing various types of land surface. Compared with the four selected AERONET sites' AOD and BRDF-derived albedo from AERONET-based Surface Reflectance Validation Network (ASRVN) data in corresponding four AERONET sites, the presented algorithm proves considerable accuracy for various type of land surface with correlation of AOD ranging from 0.647 to 0.911 and correlation of BRDF-derived albedo ranging from 0.483 to 0.944. The intersensor comparison with Moderate Resolution Imaging Spectroradiometer (MODIS) 3Â km AOD dark target product reveals high coverage rate of the presented method especially in bright surface or nonvegetation area and the correlation between the two sensors reaches up to 0.967. The improved estimation of BRDF from AATSR retrieval in AERONET Beijing site is compared with MODIS MCD43B1 product. The relative differences in hemispherical albedo calculated from average BRDF shape function parameters between AATSR and MODIS product are 1.33%, 1.52%, 2.60% and 4.28% at 550Â nm, 670Â nm, 870Â nm and 1600Â nm respectively.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Computers in Earth Sciences
Authors
Shuaiyi Shi, Tianhai Cheng, Xingfa Gu, Hao Chen, Hong Guo, Ying Wang, Fangwen Bao, Binren Xu, Wannan Wang, Xin Zuo, Can Meng, Xiaochuan Zhang,