Study On Extracting Planning Areas Of Paddy Rice By Using EOS/MODIS Data

Paddy rice is one of the main food crops in the world and also in China. Gaining the information of large-scale rice planting spatial distribution, area, and output is significant for guiding rice production, reasonable allocation of water resources, and detection of the atmospheric environment change, etc. Since the rice production features large coverage area, strong seasonality, and low economic benefit of unit area, it is technically and economically difficult to gain annual crop planting information by the ground investigation method. However, the remote sensing technology is a feasible and effective method in solving this problem. Compared with conventional statistical methods, the remote sensing method in gaining the crop planting information has its unique advantages. With the features of large coverage area, repeated observations within a short time, and relatively low cost, the remote sensing technology, combining geographic information system (GIS) and global positioning system, may extract crop planting area and realize the accurate positioning of spatial distribution.This paper takes Hunan Province as the research area. It combines the remote sensing technology and GIS technology, and selects the data within Hunan Province to realize the information extraction on late rice planting and growth in Hunan Province by the large coverage area and high time resolution of EOS/MODIS data. The research objective is to solve the problem of extensively and rapidly monitoring the late rice planting situation, and explore the solution of the mixed pixel of low resolution remote sensing image classification combining remote sensing images of middle and high spatial resolutions. The main contents in the research are:late rice identification and grid treatment based on SPOT4remote sensing image, and late rice area identification and late rice identification precision evaluation based on MODIS remote sensing data. The detail is shown as follows:First, select a SPOT4image in proper time phases to conduct geometry correction, unsupervised classification, human visual interpretation, and other treatments in order to get the late rice distribution of Hunan Province according to the late rice phenological period of Hunan Province. Meanwhile, establish a grid of500mx500m based on this image, which completely coincides with the pixel of MODIS remote sensing data to respectively calculate the percentage that late rice area occupies the whole grid area in every grid, classify them according to value differences, and then take some pixels after the classification as the training sample data and the rest as the validating data.Second, construct the vegetation index sequence data set of MODIS remote sensing data, and the vegetation index includes EVI and LSWI, and denoising treatment on the vegetation index. Then conduct principal component analysis on MOISD band images and the vegetation index of corresponding time phases and generate a new data set, and the conduct supervised classification on this data set with the training sample to get the late rice area and distribution of Hunan Province.Finally, conduct the precision validation on the late rice area and spatial distribution of Hunan Province by using the validation data and statistical data, etc. and come to the conclusion:as a whole, this method is reliable in conducting the large-scale rice monitoring precision in the rice growth stage; in the meantime, conduct beneficial exploration on solving the problem of inevitable mixed pixels in crop classification research by using the remote sensing image of low and middle spatial resolution.