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The Method Study Of Cross-calibration For Moderate And Low-resolution Remote Sensing Satellites Reflectance Bands Based On Series Imagery

Posted on:2012-04-21Degree:MasterType:Thesis
Country:ChinaCandidate:H X HuangFull Text:PDF
GTID:2178330338993447Subject:Cartography and Geographic Information Engineering
Abstract/Summary:PDF Full Text Request
The premise of quantitative remote sensing lies in the absolute radiometric calibration of remote sensor, whose precision has a direct impact on the quality of various remote sensing products. In order to promote the development of quantitative remote sensing science, and timely monitoring of changes of sensor performance and improve the quality of remote sensing data It's necessary for remote sensor onboard to calibrate in a long term. Cross-calibration is an efficient, reliable calibration method, which not only calibration of historical data, but also does not require too many simultaneous ground measurements. It's greatly reducing the calibration error, which causes by the instrumental error, measurement error, etc. Thus, the cross-calibration has the advantage which vicarious calibration can not match. The keys to success of cross-calibration is the consistency of spectral response function, observed target between two sensors and the performance of ground-based observations should be stable. That is, we must considered the differences of spectral response functions and surface BRDF effects when the observed target is stable. This paper presents a new approach to NOAA17-AVHRR sensors cross-calibration in the visible to near infrared spectral domain using an a-priori, well calibrated sensor (MODIS), which includes the following aspects:(1)The stability validation of study area using Landsat TM/ETM+ data between 2000 to 2011.We found that there was little change of surface reflectace between ten years, which was obtained after atmospheric correction by dark object method. Thus, we believed that surface characteristic of the study area is stable, which can be used for cross-calibration. (2)Retrieved the surface BRDF and aerosol optical thickness (this paper refers to the aerosol optical thickness at 550nm). The central idea of this algorithm was based on the characteristic of study area was stable and assuming of dramatic changes in atmospheric conditions during the study period. We can detect the"clearest"observation during a temporal window for each pixel. If we assumed the aerosol optical depths for the"clearest"observations to be known, the aerosol optical depths of other"hazy"observations can be interpolated from the surface reflectance of the"clearest"observations.Then surface BRDF and AOD can be retrieved. We retrieved the BRDF of globle's major desert using the method.(3) The radiometric cross-calibration was performed for NOAA17-AVHRR with the method described in step (2). Apparent reflectance calculated by this method and AVHRR vicarious calibration coefficients was basically the same. So we believed that the cross-calibration method in the paper can be alternatived vicarious calibration, which can be used in the method of Moderate and Low-resolution VNIR data, cross-calibration.
Keywords/Search Tags:Cross-calibration, BRDF, Atmospheric parameters, spectral band matching factors, apparent reflectance
PDF Full Text Request
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