[A quickly atmospheric correction method for HJ-1 CCD with deep blue algorithm].

In the present, for the characteristic of HJ-1 CCD camera, after receiving aerosol optical depth (AOD) from deep blue algorithm which was developed by Hsu et al. assisted by MODerate-resolution imaging spectroradiometer (MODIS) surface reflectance database, bidirectional reflectance distribution function (BRDF) correction with Kernel-Driven Model, and the calculation of viewing geometry with auxiliary data, a new atmospheric correction method of HJ-1 CCD was developed which can be used over vegetation, soil and so on. And, when the CCD data is processed to correct atmospheric influence, with look up table (LUT) and bilinear interpolation, atmospheric correction of HJ-1 CCD is completed quickly by grid calculation of atmospheric parameters and matrix operations of interface define language (IDL). The experiment over China North Plain on July 3rd, 2012 shows that by our method, the atmospheric influence was corrected well and quickly (one CCD image of 1 GB can be corrected in eight minutes), and the reflectance after correction over vegetation and soil was close to the spectrum of vegetation and soil. The comparison with MODIS reflectance product shows that for the advantage of high resolution, the corrected reflectance image of HJ-1 is finer than that of MODIS, and the correlation coefficient of the reflectance over typical surface is greater than 0.9. Error analysis shows that the recognition error of aerosol type leads to 0. 05 absolute error of surface reflectance in near infrared band, which is larger than that in visual bands, and the 0. 02 error of reflectance database leads to 0.01 absolute error of surface reflectance of atmospheric correction in green and red bands.

[Application of hyper-spectral remote sensing technology in environmental protection].

Hyper-spectral remote sensing (RS) technology has been widely used in environmental protection. The present work introduces its recent application in the RS monitoring of pollution gas, green-house gas, algal bloom, water quality of catch water environment, safety of drinking water sources, biodiversity, vegetation classification, soil pollution, and so on. Finally, issues such as scarce hyper-spectral satellites, the limits of data processing and information extract are related. Some proposals are also presented, including developing subsequent satellites of HJ-1 satellite with differential optical absorption spectroscopy, greenhouse gas spectroscopy and hyper-spectral imager, strengthening the study of hyper-spectral data processing and information extraction, and promoting the construction of environmental application system.

[The monitoring of haze from HJ-1].

With the urbanizing in China, haze days occur frequently, which have largely impacted air quality. In the present paper, based on haze physical properties, haze optical properties were calculated by Mie theory and apparent reflectance of haze in Environment Satellite 1 (HJ-1) channels was simulated by Radiative Transfer (RT) 3. Simulated results show that it is reasonable to extract the haze from apparent reflectance in the first and second channels. By Deep Blue algorithm, Haze Optical Depth (HOD) was retrieved from HJ-1 data supported by reflectance database from MODIS product. From HJ-1 data in 2009 over Beijing area, the haze days were monitored and validated by AERONET/PHOTONS Beijing site. The validation shows that the correlation coefficient of HOD is greater than 0.9, but HOD from HJ-1 is greater than that from ground-based measurements. The discussions show that the error from reflectance database is less than 0.1 and radiance resolution of HJ-1 needs to advance for haze monitoring.

[Retrieval and validation of the surface reflectance using HJ-1-CCD data].

The potentiality of the retrieval of surface reflectance using CCD camera aboard HJ-1A/B satellite was studied. It is very difficult to use dark targets in atmospheric correction due to the lack of near infrared band. The alternative normalized difference vegetation index (NDVI) and the red/blue reflectance ratio are detected from the spectral experiment in Beijing and the Pearl River Delta. Ground-based spectral data including grass, dense vegetation, water body, soil, residential roof and bright building etc. were used to validate the surface reflectance in Beijing, and the relative error in red, blue band is under 38.7% and 37.2% respectively. Uncertainties of the surface reflectance retrievals were analyzed. The comparison of MODIS surface reflectance product showed that there is a good agreement in the dense targets, and the correlation coefficient (R2) in red, blue band is as high as 0.809 4 and 0.723 9 respectively. HJ-1-CCD data can effectively reduce pixel-mixed impact on the cement roof and bright buildings, and the inversion accuracy is higher than MODIS products.

[The retrieval of fine and coarse aerosol from MODIS].

Generally, aerosols over land are composed of fine and coarse aerosols, which have different optical properties. How to derive the fine mode and coarse mode aerosols from satellite observations is an important issue in the aerosol retrieving. In the present paper, information of aerosol models (including refractive index and size distribution function) was retrieved from the ground-based measurement of the AERONET/PHOTONS site in Beijing. The retrievals indicate that, aerosols over Beijing have a bi-model distribution, and the optical properties of fine and coarse aerosols are distinct. Based on the dark dense vegetation (DDV) method, optical depth of the fine, coarse and total aerosols were derived from MODIS data over Beijing area in 2007. The validation of these satellite retrievals shows that from MODIS data, the optical depth of fine and total aerosols can be retrieved well (with correlation coefficients greater than 0.8), and so can the Angstrom exponent (having a correlation coefficient of 0.517). However, relatively poor results were obtained when retrieving the optical depth of coarse aerosols.