Abstract
Two GF-1 WFV images on August 3, 2015 and October 2, 2015 were selected to extract the cultivated area of paddy rice in Jianhu county of Jiangsu Province. Vegetation indexes were extracted from the original spectrum data in order to extract paddy rice area with Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) and Classification and Regression Trees (CART). The extraction accuracy of paddy rice was verified through on-site GPS measurement of 5 ground samples area with the scale of 1km × 1km. The results showed that the extraction accuracies of three methods were the best on October 2, 2015, and extraction accuracy of SVM was 84.89% which was the highest among three methods. It indicated that the GF-1 satellite image can be used for monitoring the cultivated area of paddy rice and it has higher accuracy and broad application prospects in the field of agriculture remote sensing monitoring.
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