Abstract:

To accurately obtain the planting information of winter wheat, which is the main crop in Qingdao, taking the GF-1/16 m satellite imagery as the main data source, combined with the auxiliary data source including the elevation, land utilization and field survey data, we calculated and got the results that the optimum time phase for extracting the remote sensing area of winter wheat in Qingdao was April through the spectral differences between the main development period of winter wheat and other features on the satellite imagery of GF-1/16 m. During its optimum time phase in 2017, we extracted the planting area and distribution area of winter wheat in Qingdao by the decision tree classification and districting interpretation. Besides, the 1 m satellite imagery fused GF-2, ground survey data and the data released by the statistics agency were adopted to verify the accuracy of the classification results. The results showed that: the remote sensing estimation method for winter wheat planting area on regional scale was feasible by using the advantages of GF-1/16 m satellite imagery in width, time and spatial resolution to introduce land utilization and elevation into the decision tree classification model. By verification of accuracy, the total accuracy of remote sensing interpretation for winter wheat in Qingdao in 2017 was 94.3%, and the Kappa coefficient was 0.857. The remote sensing extraction area was slightly smaller than the data released by the statistics agency, and the extraction accuracy of total area was 93.6%. This study provides reference for the extraction of crops planting area on regional scale based on high-resolution satellite imagery.

Key words: high-resolution satellite imagery, winter wheat, Qingdao, optimum time phase, decision tree classification