An Atmospheric Correction Method over Bright and Stable Surfaces for Moderate to High Spatial-Resolution Optical Remotely Sensed Imagery

Remote Sensing

Xueshuang Gong¹  Haibo Wang¹  Kai Ao²  Jinhua Wu³  Bo Zhong⁴  Junjun Wu⁴  Qinhuo Liu⁴  Shanlong Wu⁴  Aixia Yang⁴ 

[1] China Centre for Resources Satellite Data and Application, Beijing 100094, China;College of Computer Science and Technology, University of Posts and Telecommunications, Chongqing 400065, China;School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China;State Key Laboratory of Remote Sensing Science, Aerospace information Research Institute, Chinese Academy of Sciences, Beijing 100101, China;

关键词: aod;    moderate to high spatial resolution;    atmospheric correction;    aeronet;    automatic;    validation;   

DOI  :  10.3390/rs12040733

来源: DOAJ

【 摘 要 】

Although many attempts have been made, it has remained a challenge to retrieve the aerosol optical depth (AOD) at 550 nm from moderate to high spatial-resolution (MHSR) optical remotely sensed imagery in arid areas with bright surfaces, such as deserts and bare ground. Atmospheric correction for remote-sensing images in these areas has not been good. In this paper, we proposed a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from moderate to high spatial-resolution imagery in arid areas with bright surfaces. Land surface in arid areas is usually bright and stable and the variation of atmosphere in these areas is also very small; consequently, the land-surface characteristics, specifically the bidirectional reflectance distribution factor (BRDF), can be retrieved easily and accurately using time series of satellite images with relatively lower spatial resolution like the Moderate-resolution Imaging Spectroradiometer (MODIS) with 500 m resolution and the retrieved BRDF is then used to retrieve the AOD from MHSR images. This algorithm has three advantages: (i) it is well suited to arid areas with bright surfaces; (ii) it is very efficient because of employed lower resolution BRDF; and (iii) it is completely automatic. The derived AODs from the Multispectral Instrument (MSI) on board Sentinel-2, Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Gao Fen 1 Wide Field Viewer (GF-1/WFV), Gao Fen 6 Wide Field Viewer (GF-6/WFV), and Huan Jing 1 CCD (HJ-1/CCD) data are validated using ground measurements from 4 stations of the AErosol Robotic NETwork (AERONET) around the world.

【 授权许可】

Unknown