关键词: GF-1, 面向对象, 水稻, 种植信息提取

Abstract: Rice planting information extraction by remote sensing is an important part of agricultural remote sensing. GF-1 satellite WFV data provides a new way for agricultural information extraction, object-oriented classification method is an important method of remote sensing interpretation. This research takes Yangzhou as the research area, based on the GF-1 image data, uses the object-oriented classification method, extracts the rice planting information, and carries on the field investigation verification test result. The feasibility of GF-1 data oriented object classification in extracting rice planting information and the factors affecting extraction precision are discussed. The results showed that GF-1 data can be used to extract rice planting information in Yangzhou by object-oriented classification method. Rice planting area was 214 524 hm2 in Yangzhou City, the overall accuracy of rice was 98.5%, Kappa coefficient was 0.95, area accuracy was 97.5%. Field investigation can improve the extraction accuracy. The degree of terrain fragmentation affects the extraction accuracy, with the decrease of terrain fragmentation, the extraction accuracy is increased.

Key words: GF-1, object-oriented classification, rice, planting information extraction