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遥感学报 2007
Consistency Study between MODIS and TM on Winter Wheat Plant Area Monitoring——A Case in Small Area
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Abstract:
Accurate and timely updated-information for plant area of wheat is essential to yield estimation,agricultural management,optimizing the spatial pattern of winter wheat and food security.On account of the mutual restricting problems among the acquisition ability of RS images,spatial resolution and accuracy in the measurement of wheat plant area in large scale,this paper introduced the technology of support vector machine(SVM),and developed the model of consistency check used in operational measurement and accuracy verification by integrating the multi-temporal full-covered data(MODIS) and medium resolution sample data(TM).The paper chose the middle part of Henan province in China as a typical experimental region,where winter wheat is the main crop.By pixel accuracy and regional accuracy,the paper analyzed the consistency of measuring results of winter wheat between MODIS and TM with different sample amount.By consistency check between different proportion of TM sample and measuring result,the study draws the conclusions that when the sample proportion reaches 5 percent of whole samples,the pixel accuracy is higher than 82 percent,and the region accuracy is about 90 percent.Moreover,when sample proportion reaches 40 percent,region accuracy in non-sample region stabilizes over 97 percent.The study result shows that the model in the paper can be regarded as the theoretical and experimental groundwork of the operational measurement of wheat plant area by remote sensing.In practical application,if high or moderate resolution image covering 40% of whole investigating region can be obtained,the accuracy can reach the criterion of operational crop area measurement using the method brought forward in this paper.