Winter Wheat Mapping in Shandong Province of China with Multi-Temporal Sentinel-2 Images
Source abstract
Abstract
Wheat plays an important role in China’s and the world’s food supply, and it is closely related to economy, culture and life. The spatial distribution of wheat is of great significance to the rational planning of wheat cultivation areas and the improvement of wheat yield and quality. The current rapid development of remote sensing technology has greatly improved the efficiency of traditional agricultural surveys. The extraction of crop planting structure based on remote sensing images and technology is a popular topic in many researches. In response to the shortcomings of traditional methods, this research proposed a method based on the fusion of the pixel-based and object-oriented methods to map the spatial distribution of winter wheat. This method was experimented and achieved good results within Shandong Province. The resulting spatial distribution map of winter wheat has an overall accuracy of 92.2% with a kappa coefficient of 0.84. The comparison with the actual situation shows that the accuracy of the actual recognition of winter wheat is higher and better than the traditional pixel-based classification method. On this basis, the spatial pattern of winter wheat in Shandong was analyzed, and it was found that the topographic undulations had a great influence on the spatial distribution of wheat. This study vividly demonstrates the advantages and possibilities of combining pixel-based and object-oriented approaches through experiments, and also provides a reference for the next related research. Moreover, the winter wheat map of Shandong produced in this research is important for yield assessment, crop planting structure adjustment and the rational use of land resources.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Remote Sensing in Agriculture · Remote Sensing and Land Use · Remote Sensing and LiDAR Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Shandong Geographical Institute of Land Spatial Data and Remote Sensing Technology, Jinan 250002, China
The Fifth Prospecting Team of Shandong Coal Geology Bureau, Jinan 250100, China
Shandong Yuanhong Survey Planning and Design Co., Ltd., Jinan 250014, China
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 102206, China
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
The Key Laboratory of Digital Simulation in Spatial Design of Architecture and Urban-Rural, Shandong Provincial Education Department, Jinan 250101, China
Funding
Shandong Provincial Natural Science Foundation · Youth Innovation Team Project of Higher School in Shandong Province
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