From cropland to cropped field: A robust algorithm for national-scale mapping by fusing time series of Sentinel-1 and Sentinel-2

Authors

Bingwen Qiu, Fuzhou UniversityFollow
Duoduo Lin, Fuzhou University
Chongcheng Chen, Fuzhou University
Peng Yang, Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs, Beijing, China
Zhenghong Tang, University of Nebraska - LincolnFollow
Zhenong Jin, University of Minnesota
Zhiyan Ye, Fuzhou University
Xiao Zhu, The Hong Kong Polytechnic University
Mingjie Duan, The Hong Kong Polytechnic University
Hangyu Huang, Fuzhou University
Zhiyuan Zhao, Fuzhou University
Weiming Xu, Fuzhou University
Zuoqi Chen, Fuzhou University

Date of this Version

2022

Citation

International Journal of Applied Earth Observations and Geoinformation 113 (2022) 103006

doi:10.1016/j.jag.2022.103006

Comments

This is an open access article under the CC BY-NC-ND license

Abstract

Detailed and updated maps of actively cropped fields on a national scale are vital for global food security. Unfortunately, this information is not provided in existing land cover datasets, especially lacking in smallholder farmer systems. Mapping national-scale cropped fields remains challenging due to the spectral confusion with abandoned vegetated land, and their high heterogeneity over large areas. This study proposed a large-area mapping framework for automatically identifying actively cropped fields by fusing Vegetation-Soil-Pigment indices and Synthetic-aperture radar (SAR) time-series images (VSPS). Three temporal indicators were proposed and highlighted cropped fields by consistently higher values due to cropping activities. The proposed VSPS algorithm was exploited for national-scale mapping in China without regional adjustments using Sentinel-2 and Sentinel-1 images. Agriculture in China illustrated great heterogeneity and has experienced tremendous changes such as non-grain orientation and cropland abandonment. Yet, little is known about the locations and extents of cropped fields cultivated with field crops on a national scale. Here, we produced the first national-scale 20 m updated map of cropped and fallow/abandoned land in China and found that 77 % of national cropland (151.23 million hectares) was actively cropped in 2020. We found that fallow/abandoned cropland in mountainous and hilly regions were far more than we expected, which was significantly underestimated by the commonly applied VImax-based approach based on the MODIS images. The VSPS method illustrates robust generalization capabilities, which obtained an overall accuracy of 94 % based on 4,934 widely spread reference sites. The proposed mapping framework is capable of detecting cropped fields with a full consideration of a high diversity of cropping systems and complexity of fallow/abandoned cropland. The processing codes on Google Earth Engine were provided and hoped to stimulate operational agricultural mapping on cropped fields with finer resolution from the national to the global scale.