A dataset of the planting areas of three staple crops with a spatial resolution of 1 km in China during 2009–2015

Abstract

The planting area of three staple crops (rice, maize and wheat) in China ranks among the highest in the world. Developing the planting area maps of three staple crops consistent with the county-level statistical data for agricultural policy formulation and disaster risk prevention. However, there is a scarcity of available planting area datasets of for these three crops in China, and the existing public datasets limited data for only a few years, often exhibit significant disparities from the statistical data. This dataset was established using a crop mapping method based on multi-source data. Firstly, we determined the rough spatial distribution of crops by extracting key phenology of these three crops based on GLASS leaf area index (LAI) products. Then, we filtered the crop pixels gradually by the optimization rules referring to county-level statistical data. Finally, we obtained a dataset of the planting areas of three staple crops with a spatial resolution of 1 km in China during 2009–2015 (ChinaCropArea1kmV2). The R2 (consistency with county-level statistical data) values of maize, rice and wheat products are 0.98, 0.89 and 0.82 respectively, and the accuracies of mapping based on point verification reached 0.85, 0.86 and 0.93 respectively. The consistency between the second generation products and statistical data is higher than the accuracy of existing products. The presented method for the production of this dataset can rapidly enables rapid and accurate crop mapping over large areas while maintaining a high level of consistency with county-level statistical yearbooks. The production of this dataset is helpful to provide a key data base for agricultural production research and scientific decision making.