干旱区生态环境知识资源中心(Arid): High Spatial Resolution Topsoil Organic Matter Content Mapping Across Desertified Land in Northern China

Arid

DOI	10.3389/fenvs.2021.668912
	High Spatial Resolution Topsoil Organic Matter Content Mapping Across Desertified Land in Northern China
	Yang Junting; Li Xiaosong; Wu Bo; Wu Junjun; Sun Bin; Yan Changzhen; Gao Zhihai
通讯作者	Li, XS (corresponding author), Int Res Ctr Big Data Sustainable Dev Goals, Beijing, Peoples R China. ; Li, XS (corresponding author), Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China.
来源期刊	FRONTIERS IN ENVIRONMENTAL SCIENCE
EISSN	2296-665X
出版年	2021
卷号	9
英文摘要	Soil organic matter (SOM) content is an effective indicator of desertification; thus, monitoring its spatial-temporal changes on a large scale is important for combating desertification. However, mapping SOM content in desertified land is challenging owing to the heterogeneous landscape, relatively low SOM content and vegetation coverage. Here, we modeled the SOM content in topsoil (0-20 cm) of desertified land in northern China by employing a high spatial resolution dataset and machine learning methods, with an emphasis on quarterly green and non-photosynthetic vegetation information, based on the Google Earth Engine (GEE). The results show: 1) the machine learning model performed better than the traditional multiple linear regression model (MLR) for SOM content estimation, and the Random Forest (RF) model was more accurate than the Support Vector Machine (SVM) model; 2) the quarterly information regarding green vegetation and non-photosynthetic were identified as key covariates for estimating the SOM content in desertified land, and an obvious improvement could be observed after simultaneously combining the Dead Fuel Index (DFI) and Normalized Difference Vegetation Index (NDVI) of the four quarters (R-2 increased by 0.06, the root mean square error decreased by 0.05, the ratio of prediction deviation increased by 0.2, and the ratio of performance to interquartile distance increased by 0.5). In particular, the effects of the DFI in Q1 (the first quarter) and Q2 (the second quarter) on estimating low SOM content (<1%) were identified; finally, a timely (2019) and high spatial resolution (30 m) SOM content map for the desertified land in northern China was drawn which shows obvious advantages over existing SOM products, thus providing key data support for monitoring and combating desertification.
英文关键词	desertified land soil organic matter content Sentinel-2 machine learning Google Earth Engine
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000697952100001
WOS关键词	SOIL TOTAL NITROGEN ; SEMIARID REGION ; CARBON STOCKS ; RANDOM FOREST ; PREDICTION ; VEGETATION ; REGRESSION ; SUPPORT ; GRASSLAND ; PATTERN
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/363307
作者单位	[Yang Junting; Li Xiaosong] Int Res Ctr Big Data Sustainable Dev Goals, Beijing, Peoples R China; [Yang Junting; Li Xiaosong; Wu Junjun] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China; [Yang Junting] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China; [Wu Bo] Chinese Acad Forestry, Inst Desertificat Studies, Beijing, Peoples R China; [Sun Bin; Gao Zhihai] Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing, Peoples R China; [Yan Changzhen] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Desert & Desertificat, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Yang Junting,Li Xiaosong,Wu Bo,et al. High Spatial Resolution Topsoil Organic Matter Content Mapping Across Desertified Land in Northern China[J],2021,9.
APA	Yang Junting.,Li Xiaosong.,Wu Bo.,Wu Junjun.,Sun Bin.,...&Gao Zhihai.(2021).High Spatial Resolution Topsoil Organic Matter Content Mapping Across Desertified Land in Northern China.FRONTIERS IN ENVIRONMENTAL SCIENCE,9.
MLA	Yang Junting,et al."High Spatial Resolution Topsoil Organic Matter Content Mapping Across Desertified Land in Northern China".FRONTIERS IN ENVIRONMENTAL SCIENCE 9(2021).