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- Title
Extraction of Planting Information of Winter Wheat in a Province Based on GF-1/WFV Images.
- Authors
Li Feng; Qin Quart; Wang Hao; Hu Xianfeng; Zhao Hong
- Abstract
In order to explore the adaptability of domestic high-resolution GF-1 satellite images in the extraction of planting information of crops especially in a province, based on the 16-meter remote sensing images of a multi-spectral wide-spectrum camera (WFV) carried by the GF-1 satellite as well as land use type and field survey data of Shandong Province, the planting area and distribution regions of winter wheat in Shandong Province (the main producing area of winter wheat in China) in 2016 were extracted by decision tree classification method and supervised classification-maximum likelihood classification method, and the accuracy of the classification results was verified based on ground survey data and data published by the statistics bureau. The results showed that the method of taking the GF-1/WFV images as the main source of data, introducing multi-source information into the decision tree and supervised classification models, and then calculating the planting area of winter wheat in the province was feasible. The total accuracy of remote sensing interpretation of winter wheat in Shandong Province in 2016 reached 92.1%, and Kappa coefficient was 0.806. The planting area of winter wheat extracted based on the remote sensing images in the province was slightly smaller than the area provided by the statistics department, and the extraction accuracy of the area was 93.0%. Research indicates that GF-1/WFV images have great potential for development and application in remote sensing monitoring of planting information of crops in a province.
- Subjects
WINTER wheat; REMOTE-sensing images; PLANTING; DECISION trees; MAXIMUM likelihood statistics
- Publication
Meteorological & Environmental Research, 2018, Vol 9, Issue 4, p100
- ISSN
2152-3940
- Publication type
Article
- DOI
10.19547/j.issn2152-3940.2018.04.023