Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite

Beijing, China

Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite

Beijing, China
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Liu R.,CAS Institute of Physics | Liu R.,National Satellite Meteorological Center | Chen H.,CAS Institute of Physics | Shi C.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite | Liu J.,China Meteorological Press
2011 International Conference on Information Science and Technology, ICIST 2011 | Year: 2011

A new method for spatial matching of data with different resolution was proposed by introducing the concept of standing and contour pixels in histo-variogram theory, and was examined in quality validation of the sea surface temperature data obtained by FY2-C satellite. For comparing satellite data with grid data, this method can reduce the spurious error resulted from changed pixel characteristics during downscaling or upscaling. For comparing satellite data with station data, this method can give relatively accurate results while requiring less precise spatial matching. © 2011 IEEE.


Yang L.,National Satellite Meteorological Center | Yang L.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite | Feng X.,National Satellite Meteorological Center | Feng X.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite | And 3 more authors.
Chinese Journal of Electronics | Year: 2014

To analysis and improve China Fengyun-2 (FY-2, spin-stabilized geosynchronous meteorological satellite) on-orbit Image navigation (IN) performance, an automated landmark matching algorithm (FY-2 automated landmark matching, FALM) for the Visible and infrared spin scan radiometer (VISSR) visible channel has been developed at China National satellite meteorological center (NSMC). FALM is based on a correlation algorithm used to match the observed landmark to the corresponding landmark extracted from the template. FALM can overcome the previous methods' shortcomings, such as the dependency on ten-year long satellite data and US Defense Mapping Agency data. Each step of FALM, generation of the landmark templates, binarization processing for observed images, image matching between observed images and landmark templates are described. Exclusion of false matching is done by several strict quality measures including cloud contamination detection, prior knowledge check, neighborhood filter and Hypothesis test. 400 days of FY-2 data have been processed by FALM and the results have showed that mainly five factors which can influence the FY-2 on-orbit IN performance: orbit control, the integrity of the known IN parameters, the satellite viewing zone adjustment, beta angle computation and the moment of sunshine pressure. Because of FALM's high processing speed and accuracy, it is ready to put into operation for the FY-2 IN improvement, as well as for operational monitoring purposes, and will be further developed for FY-4.


Guo Q.,National Satellite Meteorological Center | Guo Q.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite | Yang C.,National Satellite Meteorological Center | Yang C.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite | And 2 more authors.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2010

Spatial characteristics of thermal infrared (TIR) images are generally described by image-derived point spread function (IDPSF) for sampled imaging system. Most investigators working on IDPSF on-orbit evaluation focus on visible and near-infrared images and pay little attention on TIR ones, the reason of which lies on the fact that the assumption of an observed target with an ideal step profile is not suitable for TIR band. A new approach for TIR images is proposed here based on a more common slope-profile model, where the transition features, i.e., the sample number (Nslope) and the beginning position of slope interval, are extracted from the observed signals. Simulation results show that the estimation performance will be increased, with lower noise level as well as higher system modulation transfer function value at half of normalized spatial frequency (MTF 0.5) or smaller Nslope. For a good performance system with noise squared-root variance (SRV) nomore than 1.0 count and MTF 0.5 between 0.3 and 0.4, the relative error between simulated and estimated MTF 0.5's is less than 20%. The IDPSF of FY-2C satellite TIR band is estimated, and the derived MTF 0.5 is properly close to on-ground testing results. The image quality of FY-2C TIR band has been improved by using Wiener filtering and the estimated IDPSF, which eventually benefits the cloud detection product with more detectable low fractus and increased detection accuracy by about 1% in winter. Considering a step-profile target as a special case of this model, the proposed approach is also suitable for visible and near-infrared images. © 2009 IEEE.

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