Abstract

Yellow River is the second longest river in China, but from of old, its annual ice flood threatens people's safety and property in the Yellow River basin. Yellow River's ice flood is due to its especial geographic condition with its flowing direction from low latitude to high latitude. Every year the government spends much of manpower and material resource in Yellow River ice flood prevention. It was the first time for Yellow River Conservancy Commission (YRCC) to use Remote Sensing data in the Yellow River daily ice detection, and MODIS data as the primary data in this monitoring work. For the high temporal resolution, MODIS (the Moderate Resolution Imaging Spectroradiometer) data is useful in monitoring ice flood changing day by day. The MODIS snow and ice cover algorithm is based on the reflectance characteristic of snow. In this paper, two criteria, the Normalized Difference Snow Index (NDSI) and one test of near-infrared band's reflectance were used to identify Yellow River's ice. By comparing to the ground truth information from Yellow River hydrologic stations, the algorithm was developed, the result validated, the achievements described, and the shortage analyzed. The results show that MODIS is efficient in ice and snow detection.

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