High-resolution mapping of saturated soil hydraulic conductivity across China's drylands
文献类型：期刊论文
| 作者 | Yang, Ting2,6; Jia, Xiaoxu1,6; Niu, Liantao1,5; Huang, Laiming1,6; Zhao, Chunlei1,6; Li, Xiangdong4; Ren, Xiang3,7; Wang, Ruofan5; Shao, Mingan1,6 |
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 出版日期 | 2026-04-01 |
| 卷号 | 148页码:105176 |
| 关键词 | Saturated soil hydraulic conductivity Remote sensing Machine learning Sentinel-1/2 Environmental covariates |
| ISSN号 | 1569-8432 |
| DOI | 10.1016/j.jag.2026.105176 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | The accurate high-resolution mapping of saturated soil hydraulic conductivity (Ks) is crucial for the advancement of hydrological modeling and soil-water management practices. Traditional approaches, including pedo-transfer functions (PTFs) and coarse-resolution digital soil mapping, encounter constraints in delineating fine-scale spatial heterogeneity. This is attributed to their dependence on sparse soil properties or low-resolution environmental covariates. This study proposes a novel approach that integrates multi-sensor Sentinel-1 and Sentinel2 (S1/S2) remote sensing data with environmental covariates (including climate, vegetation, topography, and soil properties). This integration is achieved via a random forest regression model on the Google Earth Engine (GEE) platform, thereby facilitating the generation of 90-meter resolution Ks maps in China's drylands. More than 5,000 lab-based Ks samples were employed to assess the contributions of synthetic aperture radar (SAR), optical, and environmental variables. The results demonstrated that high-resolution remote sensing data significantly improve the accuracy of Ks prediction at both surface (0-10 cm) and subsurface (10-30 cm) layers. Specifically, the root mean square error (RMSE) of ln(Ks/(cm min-1)) ranged from 1.24 to 1.61, and the coefficient of determination (R2) from 0.61 to 0.79. The generated 90-m Ks map outperformed the existing global and regional datasets in terms of both spatial detail and statistical accuracy. Validation using Taylor diagrams and probability density functions confirmed a closer match with the field data distributions, with the standard deviation reduced by 13.61%-22.81% compared to benchmarks. In particular, our findings elucidated the finescale heterogeneity influenced by soil texture and topography-such as the high-Ks zones in the Loess Plateau and Taklamakan Desert, which were not clearly visible in coarser products, were successfully resolved. This approach bridges the gap between coarse-scale PTFs and the requirement for high-resolution hydrological inputs. Additionally, it provides a scalable solution for arid and semi-arid regions worldwide. |
| URL标识 | 查看原文 |
| WOS关键词 | PARTICLE-SIZE DISTRIBUTION ; PEDOTRANSFER FUNCTIONS ; LAND ; WATER ; MODIS |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001709309700001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221285]  |
| 专题 | 黄河三角洲现代农业工程实验室_外文论文 |
| 通讯作者 | Jia, Xiaoxu |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China; 2.Shandong Dongying Inst Geog Sci, Dongying 257000, Peoples R China; 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 4.Yanan Univ, Coll Life Sci, Yanan 716000, Peoples R China; 5.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China; 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Modern Agr Engn Lab, Beijing 100101, Peoples R China; 7.Civil Aviation Adm China, Key Lab Low Altitude Geog Informat & Air Route, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Ting,Jia, Xiaoxu,Niu, Liantao,et al. High-resolution mapping of saturated soil hydraulic conductivity across China's drylands[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2026,148:105176. |
| APA | Yang, Ting.,Jia, Xiaoxu.,Niu, Liantao.,Huang, Laiming.,Zhao, Chunlei.,...&Shao, Mingan.(2026).High-resolution mapping of saturated soil hydraulic conductivity across China's drylands.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,148,105176. |
| MLA | Yang, Ting,et al."High-resolution mapping of saturated soil hydraulic conductivity across China's drylands".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 148(2026):105176. |
入库方式： OAI收割
来源：地理科学与资源研究所
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