Share Email Print
cover

Proceedings Paper

Retrieval of aerosol optical depth over the Yangtze River Delta with HJ-1 data
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Aerosol optical depth (AOD) is a key indicator of atmospheric environment. Aerosol remote sensing is the most efficient way to obtain the temporal and spatial distributions of AOD. In this paper, the data from Environment Satellite (HJ-1) CCD camera were employed to retrieve AOD by using deep blue algorithm over the Yangtze River Delta. The third band (in blue) was firstly extracted from the MODIS land surface reflectance product (MOD09) and then converted to the first band of CCD/HJ-1. According to the characteristics of the study area and CCD data, a multi-dimension look up table was then built by the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). AOD over the Yangtze River Delta were finally retrieved from the radiance of the first band of CCD/HJ-1. After the retrieved AOD were validated by the MODIS AOD product (MOD04), the correlation coefficient (R) is 0.64 by regression of all cloud screened pixels (1147). The retrieved AOD has a higher spatial resolution than the MODIS AOD and thus can provide more detailed information. Compared with the AERONET ground observation data, the retrieved AOD is closer to the ground-based data than the MODIS AOD.

Paper Details

Date Published: 8 October 2014
PDF: 10 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 92210Y (8 October 2014); doi: 10.1117/12.2061169
Show Author Affiliations
Lu Zhang, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Runhe Shi, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Yongming Xu, Nanjing Univ. of Information Science and Technology (China)
Long Li, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Wei Gao, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

© SPIE. Terms of Use
Back to Top