Abstract

Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are multi-spectral sensors embarked on the EOS AM-1 (TERRA) satellite platform. Both sensors opperate in different spectral bands, but also with different pixel resolutions. The overall goal of this paper is to classify MODIS data to get an estimation of water surface area, very useful in the post-crisis periods for the decision makers at all levels. To develop the classification technique, the strategy was to obtain MODIS and ASTER data acquired at the same time over the same location, and use the ASTER data as "ground truth". Two lakes in the Bihor County of Romania were chosen and satellite data from October 31, 2002 were utilized. From the ASTER data we created a detailed water mask to be used as ground truth for the MODIS water classification. The percent water image derived from ASTER was superimposed on the MODIS image. A supervised classification for water was performed on the 3-band MODIS image using the feature space algorithm. The water surface area as measured from the MODIS classification was about 16% more than the ASTER ground truth-value. Due to the constraint that high spatial resolution satellite images are low temporal resolution, there exists a need for a reliable method to obtain accurate information from medium resolution data. This approach provided useful information concerning the water classification from different resolution data that could help in the estimation of water surface area from MODIS imagery.

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