Mapping cropping intensity in Huaihe basin using phenology algorithm, all Sentinel-2 and Landsat images in Google Earth Engine

Abstract

With the decline of cultivated land quality and area in recent decades, the intensification of land use plays an important role in meeting the growing demand for food. Cropping intensity refers to the number of crop planting cycles in one year, which is important for improving food production and safety at the local, regional and national scales. Therefore, it is necessary to develop an accurate high spatial resolution dataset of cropping intensity. The existing datasets of cropping intensity were generally developed based on MODIS or Landsat images, both of which have defects in spatial and temporal resolutions. In this paper, we improved the quality of the dataset on the Google Earth Engine (GEE) platform, and developed a new algorithm incorporating crop phenology. The algorithm was based on the Landsat 7/8 and Sentine-2A/B time series imageries to map the 30 m cropping intensity in the Huaihe basin in 2018 by extracting complete growth cycle. Results show that single cropping, double cropping and triple cropping in the Huaihe basin accounted for 41.6%, 57.7% and 0.7% of the total cultivated area in 2018, respectively, and the proportion of multiple cropping reached 58.4%. The accuracy of single cropping, double cropping and triple cropping are 92.93%, 91.39%, and 72.78% respectively. The overall accuracy is 91.38% and the kappa coefficient is 0.84. This algorithm accurately captures the seasonal dynamics of planting patterns in arable land, which can be used to produce cropping intensity products with high-resolution and provide a reference for large-scale regional vegetation monitoring.