Mapping crop distribution in China between 2000 and 2015 by fusing remote-sensing derived cropping seasons and knowledge-based crop phenology

Crop mapping is necessary for a variety of application in food security and agricultural monitoring. An innovative phenology-based crop mapping method was developed to map 14 crops between 2000 and 2015. Unlike traditional mapping methods mainly based on remote-sensing data and statistic data, our method takes crop phenology as the input. Phenological metrics represent crop characteristics related to crop calendar and progress such as the timing of emergence, maturity, harvest, etc. Phenological characteristics of each crop are relatively consistent for a long period of time. Combing crop phenology, we allocated the statistical harvest areas on cropland through matching different crops to different cropping seasons in each agroecological regions, which were extracted from 16-day composite MODIS EVI (MOD13Q1) time series data in 250m spatial resolution. Here we obtained the distribution of 14 crops at the spatial resolution of 1km by 1km in 2000, 2010 and 2015, which had higher spatial resolution and higher accuracy when compared with other products. By comparing the data recorded crop types in each meteorological station, we found our method achieved higher accuracies than other methods at the same resolution. As for winter crops, the relevance between total statistical crop area and the area of different cropping seasons that extracted by remote sensing in each agroecological region was higher than 70%. Obviously, the use of crop phenology as the mapping method input improve the accuracy of crop mapping, which are convenient for analyzing the spatial and temporal change of our crops. We found that the center of gravity migration of all crops fell into three directions when analyzing the center of gravity distribution change. In addition, declining Shannon diversity index reflected that the crop richness of the same plot was decreasing.