Abstract: Feature selection based on correlation clustering algorithm（FSCC） has a direct impact on the scale management of winter wheat planting areas. Taking a certain area in Chongqing City as the research object, the impact of FSCC on the accuracy of winter wheat planting area scale management zoning was analyzed. Firstly, a data sample library was established using clustering algorithms to study the spatial distribution characteristics of winter wheat planting areas, while calculating regional accuracy, average regional accuracy, standard deviation of regional accuracy, root mean square error, and deviation. Then, a subset of features was selected to achieve data partitioning calculation. The results showed that FSCC had a significant impact on the accuracy of regional scale management zoning for winter wheat cultivation. In the process of implementing zoning management, it is necessary to simultaneously consider four factors： FSCC, spatial monitoring range, crop types, and planting density of winter wheat. Through mutual adjustment, it was ensured that the zoning effect was optimal, thereby improving the planting yield of winter wheat.

Key words: feature selection based on correlation clustering algorithm（FSCC）, winter wheat, planting area, scale management, algorithms