Validating MODIS surface reflectance based on field spectral measurements

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Abstract:

This paper presents a method of validating the MODIS (Moderate-Resolution Imaging Spectroradiometer) surface reflectance (MOD09) based on ground spectral measurements and high-resolution remote sensing images. Given that the spatial resolution of the MODIS image is too low to directly compare ground measurements with the MODIS pixels, registration is first made between MODIS and a high-resolution image. Afterwards, the same sizable sample area to one MODIS pixel is chosen in a high resolution image (a pixel in MODIS corresponds to many pixels in a high-resolution image), after which image classification is conducted in each sample area. Finally, reflectance is measured for each class in each area. Taking the ratio of every class area to each sample area as the weight, the weighted mean reflectance is then calculated for each sample area (a pixel for MODIS), which is treated as the measured reflectance of the corresponding pixel in the MODIS image. A contradistinctive analysis is carried out between measured reflectance and MODIS retrieval reflectance from the space in order to determine the accuracy of the MODIS land surface reflectance product and correct its error. The experiment indicates that a linear positive correlativity between the MODIS pixel retrieval reflectance from space and the measured (calculated) surface reflectance exists. From this, we can build an error correction model of the MODIS surface reflectance product by linear regression. The accuracy of the MODIS surface reflectance products after error correction is remarkably improved. Likewise, the relative error can be controlled by 10%, thereby satisfying the requirements of various remote sensing applications.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160903474988

Affiliations: 1: Research Center of Remote Sensing and Spatial Information Science, School of Communication and Information Engineering, Shanghai University, Shanghai, PR, China,School of Geosciences, Yangtze University, Jingzhou, Hubei, PR, China 2: Research Center of Remote Sensing and Spatial Information Science, School of Communication and Information Engineering, Shanghai University, Shanghai, PR, China 3: Calculation Center, Shanghai University of Engineering Science, Shanghai, PR, China

Publication date: February 1, 2010

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