MODIS data has a high temporal and spectral resolution, and it can provide vegetation indices of high quality. By using
MODIS NDVI time series with 250 m spatial resolution which were composite of 16 days in 2005, this work chose
annual modulus of vector, maximum and minimum NDVI three indices to do classification. Training and validation
samples were selected based on TM images and the 1:1,000,000 vegetation atlas of China. Then the land coverage map
was generated using maximum likelihood classification (MLC) method. After post-classification process of the original
classification result, the final land classification map of Keerqin sandy land was got in the end. The classification
accuracy was assessed using validation samples and the result indicates that 250 m MODIS NDVI time series has
advantage and potential in regional land coverage mapping. Also the classification method used in the paper could not
only reduce the data amount and quicken the speed of classification, but also could reduce the disturbance of other
invalidation information to classification and get better classification accuracy.
By means of GIS method, the digital elevation model (DEM) of Binjiang Basin was established, and the boundary of the basin was drawn. Based on SCS model, the Grid SCS model was established; with witch the flood volumes were computed. This research indicates that the Grid SCS model can calculate the spatial distribution of the runoff and the calculation precision of runoff yield is improved.
Weather Satellite data has great potential for Precipitation forecast which plays an important role in flood disaster monitoring. In this paper, the GMS-5 infrared cloud imagery combined with surface temperature data for two years in Binjiang reaches of Guangdong province in China is used to study the relationship between infrared cloud imagery and surface rainfall rates. First, parameterization estimate of infrared cloud imagery is made one the base of atmospheric probing principle, then some parameterization estimate result have been obtained under different analysis field from 3×3 to 15×15 pixels. The result shows:1 there exist obvious correlation between the probability of rain and parameterization estimate such as average brightness temperature(Tb), brightness temperature variance(fc), equivalent cloudage(CN),brightness temperature area index(A1--the first A5--the fifth grade, A6-the sixth grade );2 The rainfall intensity increase with Tb and f and CN, and that it decrease with Tb and A1.Finally,the prediction empirical formula of rainfall intensity has been established by means of optimized subclass regression under different analysis field. The following formula is made under analysis field of 11×11 pixels. The statistical result shows that the average precision of rainfall intensity is about 80% using infrared cloud imagery parameters and the size of analysis field has slight effect on it. If the rainfall intensity reached the storm standard, the flood alarm would be sent out.