| As sugarcane planting in southern hills exhibits many characteristics, such as scattered, diverse shape and
so on, the extraction of sugarcane information using low and medium resolution remote sensing data is hard to satisfy the
requirements of accuracy and availability. GF -1 WFV images are used as data source in this paper, spectral
characteristics, texture features and vegetation index changes are comparatively analyzed, and then the sugarcane extraction model are established based on decision tree method using multi-temporal images. With this model, sugarcane planting information is extracted in Guangxi Jiangzhou area and fields survey data are used to check the extraction accuracy. The results show that the user accuracy is 90.13% and production accuracy is 88.78%. GF-1 WFV satellite data with its high spatial resolution and convenient obatain means can provide a potential data source for crop information identification, monitoring, extraction in complex area. |
