A framework for soil texture prediction based on remote sensing information from different climate patterns and crop growth periods
文献类型：期刊论文
| 作者 | Li, Xiangrui2,3; Zhang, Yuhong3; Liu, Huanjun2; Xu, Xinliang1; Zhang, Wenqi4; Luo, Chong2 |
| 刊名 | INTERNATIONAL JOURNAL OF DIGITAL EARTH
 |
| 出版日期 | 2026-07-01 |
| 卷号 | 19期号:1页码:2639816 |
| 关键词 | Soil texture random forest recursive feature elimination climate patterns digital soil mapping |
| ISSN号 | 1753-8947 |
| DOI | 10.1080/17538947.2026.2639816 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Soil texture is an important parameter representing the physical properties of soil, so accurate mapping of it is crucial for revealing the intrinsic soil properties. Using Sentinel-2 images from Youyi Farm, which is located in the third major black soil region of Northeast China, bare soil information, and crop growth information, the relationship between them and soil texture mapping accuracy under different annual climate patterns (2019-flooded, 2020-normal, and 2021-drought) was explored. The results indicated that (1) the highest mapping accuracy was obtained for sand, silt, and clay after the recursive feature elimination, with R & sup2; and RMSE values reaching 0.732/8.544%, 0.762/6.725%, and 0.612/1.925%, respectively. (2) In the flooded year, crop-growth information (NDVI, EVI) added in different months had a small effect on the mapping accuracy of clay, while sand and silt showed large fluctuations. (3) The results show that all bands of remote sensing imagery have major influences on all soil texture predictions and that crop growth information contributes relatively little to sand and silt but significantly influences clay predictions. This study offers new perspectives and methods for high-resolution mapping of soil texture and related soil property studies. |
| URL标识 | 查看原文 |
| WOS关键词 | ORGANIC-CARBON ; FEATURE-SELECTION ; PERFORMANCE ; VALIDATION ; MOISTURE ; LAND |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001708050700001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221169]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Zhang, Yuhong; Luo, Chong |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China; 2.Chinese Acad Sci, Northeast Inst Geog & Agroecol, State Key Lab Black Soils Conservat & Utilizat, Changchun 130102, Peoples R China; 3.Harbin Normal Univ, Heilongjiang Prov Key Lab Geog Environm Monitoring, Harbin 150025, Peoples R China; 4.Jilin Agr Univ, Sch Econ & Management, Changchun, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Xiangrui,Zhang, Yuhong,Liu, Huanjun,et al. A framework for soil texture prediction based on remote sensing information from different climate patterns and crop growth periods[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH,2026,19(1):2639816. |
| APA | Li, Xiangrui,Zhang, Yuhong,Liu, Huanjun,Xu, Xinliang,Zhang, Wenqi,&Luo, Chong.(2026).A framework for soil texture prediction based on remote sensing information from different climate patterns and crop growth periods.INTERNATIONAL JOURNAL OF DIGITAL EARTH,19(1),2639816. |
| MLA | Li, Xiangrui,et al."A framework for soil texture prediction based on remote sensing information from different climate patterns and crop growth periods".INTERNATIONAL JOURNAL OF DIGITAL EARTH 19.1(2026):2639816. |
入库方式： OAI收割
来源：地理科学与资源研究所
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