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ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021

文献类型：期刊论文

作者Mei, Qinghang4,5,6; Zhang, Zhao5,6; Han, Jichong3,5,6; Song, Jie3,5,6; Dong, Jinwei1,2; Wu, Huaqing5,6; Xu, Jialu5,6; Tao, Fulu1,2
刊名EARTH SYSTEM SCIENCE DATA
出版日期2024-07-10
卷号16期号:7页码:3213-3231
ISSN号1866-3508
DOI10.5194/essd-16-3213-2024
英文摘要Soybean, an essential food crop, has witnessed a steady rise in demand in recent years. There is a lack of high-resolution annual maps depicting soybean-planting areas in China, despite China being the world's largest consumer and fourth-largest producer of soybean. To address this gap, we developed the novel Regional Adaptation Spectra-Phenology Integration method (RASP) based on Sentinel-2 remote sensing images from the Google Earth Engine (GEE) platform. We utilized various auxiliary data (e.g., cropland layer, detailed phenology observations) to select the specific spectra and indices that differentiate soybeans most effectively from other crops across various regions. These features were then input for an unsupervised classifier (K-means), and the most likely type was determined by a cluster assignment method based on dynamic time warping (DTW). For the first time, we generated a dataset of soybean-planting areas across China, with a high spatial resolution of 10 m, spanning from 2017 to 2021 (ChinaSoyArea10m). The R2 values between the mapping results and the census data at both the county and prefecture levels were consistently around 0.85 in 2017-2020. Moreover, the overall accuracy of the mapping results at the field level in 2017, 2018, and 2019 was 77.08 %, 85.16 %, and 86.77 %, respectively. Consistency with census data was improved at the county level (R2 increased from 0.53 to 0.84) compared to the existing 10 m crop-type maps in Northeast China (Crop Data Layer, CDL) based on field samples and supervised classification methods. ChinaSoyArea10m is very spatially consistent with the two existing datasets (CDL and GLAD (Global Land Analysis and Discovery) maize-soybean map). ChinaSoyArea10m provides important information for sustainable soybean production and management as well as agricultural system modeling and optimization. ChinaSoyArea10m can be downloaded from an open-data repository (DOI: https://doi.org/10.5281/zenodo.10071427, Mei et al., 2023).
WOS关键词WATER-STRESS ; MODIS ; LANDSAT ; RICE ; MAPS ; CORN
资助项目National Key Research and Development Program of China[2020YFA0608201] ; National Natural Science Foundation of China[42061144003] ; National Natural Science Foundation of China[41977405]
WOS研究方向Geology ; Meteorology & Atmospheric Sciences
语种英语
WOS记录号WOS:001268927800001
出版者COPERNICUS GESELLSCHAFT MBH
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/207369]  
专题陆地表层格局与模拟院重点实验室_外文论文
通讯作者Zhang, Zhao
作者单位1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
3.Beijing Normal Univ, Sch Syst Sci, Beijing 100875, Peoples R China
4.Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China
5.Beijing Normal Univ, Sch Natl Safety & Emergency Management, Zhuhai 519087, Peoples R China
6.Beijing Normal Univ, Joint Int Res Lab Catastrophe Simulat & Syst Risk, Zhuhai 519087, Peoples R China
推荐引用方式
GB/T 7714		 Mei, Qinghang,Zhang, Zhao,Han, Jichong,et al. ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021[J]. EARTH SYSTEM SCIENCE DATA,2024,16(7):3213-3231.
APA Mei, Qinghang.,Zhang, Zhao.,Han, Jichong.,Song, Jie.,Dong, Jinwei.,...&Tao, Fulu.(2024).ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021.EARTH SYSTEM SCIENCE DATA,16(7),3213-3231.
MLA Mei, Qinghang,et al."ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021".EARTH SYSTEM SCIENCE DATA 16.7(2024):3213-3231.

入库方式： OAI收割

来源：地理科学与资源研究所

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