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DOI | 10.1016/j.scitotenv.2019.05.332 |
High-resolution three-dimensional mapping of soil organic carbon in China: Effects of SoilGrids products on national modeling | |
Liang, Zongzheng1; Chen, Songchao2,3; Yang, Yuanyuan1; Zhou, Yue1; Shi, Zhou1,4 | |
发表日期 | 2019 |
ISSN | 0048-9697 |
EISSN | 1879-1026 |
卷号 | 685页码:480-489 |
英文摘要 | Soil organic carbon (SOC) is a key factor in soil fertility and structure and plays an important role in the global carbon cycle. However, SOC causes a large uncertainty in Earth System Models for predicting future climate change. The GlobalSoilMap (GSM) project aims to provide global digital soil maps of primary functional soil properties at six standard depth intervals (0-5, 5-15,15-30, 30-60, 60-100, and 100-200 cm) with a grid resolution of 90 x 90 m. Currently, few SOC national products that meet the GSM specifications are available. This study describes the three-dimensional spatial modeling of SOC maps according to GSM specifications. We used 5982 soil profiles collected during the Second National Soil Survey of China, along with 16 environmental covariates related to soil formation. The results were obtained by parallel computing over tiles of 100 x 100 km, and the predictions for the tiles were subsequently merged into a single SOC map for the whole of China per standard GSM depth interval. For each standard GSM depth interval, SOC contents and their uncertainties were predicted and mapped at a spatial resolution of approximately 90 m using bootstrapping. Southwestern and northeastern China had higher SOC contents than the rest of China did, whereas northwestern China had a lower SOC content. The range of the coefficient of determination for the six depth intervals ranged from 035 to 0.02, and the mean SOC content was 17.86-8.67 g kg(-1). Both these values decreased strongly with increasing soil depth. Cropland SOC content was lower than that of forest and grassland. The results of variable importance show that SoilGrids data were the best predictors for defining the soil-landscape relationship during regression modeling for SOC. These SOC maps can provide a data source for environmental modeling, a benchmark against which to evaluate and monitor SOC dynamics, and a guide for the design of future soil surveys. (C) 2019 Elsevier B.V. All rights reserved. |
WOS研究方向 | Environmental Sciences & Ecology |
来源期刊 | SCIENCE OF THE TOTAL ENVIRONMENT
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文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/102978 |
作者单位 | 1.Zhejiang Univ, Coll Environm & Resource Sci, Inst Agr Remote Sensing & Informat Technol Applic, Hangzhou 310058, Zhejiang, Peoples R China; 2.INRA, Unite InfoSol, F-45075 Orleans, France; 3.Agrocampus Ouest, INRA, UMR SAS, F-35000 Rennes, France; 4.Minist Agr, Key Lab Spect Sensing, Hangzhou 310058, Zhejiang, Peoples R China |
推荐引用方式 GB/T 7714 | Liang, Zongzheng,Chen, Songchao,Yang, Yuanyuan,et al. High-resolution three-dimensional mapping of soil organic carbon in China: Effects of SoilGrids products on national modeling[J],2019,685:480-489. |
APA | Liang, Zongzheng,Chen, Songchao,Yang, Yuanyuan,Zhou, Yue,&Shi, Zhou.(2019).High-resolution three-dimensional mapping of soil organic carbon in China: Effects of SoilGrids products on national modeling.SCIENCE OF THE TOTAL ENVIRONMENT,685,480-489. |
MLA | Liang, Zongzheng,et al."High-resolution three-dimensional mapping of soil organic carbon in China: Effects of SoilGrids products on national modeling".SCIENCE OF THE TOTAL ENVIRONMENT 685(2019):480-489. |
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