Applicability of three remote sensing based soil moisture variables for mapping soil organic matter in areas with different vegetation densities
文献类型：期刊论文
| 作者 | Yang, Chenconghai6; Yang, Lin5,6; Zhang, Lei3,6; Shen, Feixue6; Fu, Di6; Li, Shengfeng6; Chen, Zhiqiang1,2; Zhou, Chenghu4,6 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2025-07-01 |
| 卷号 | 655页码:132980 |
| 关键词 | Soil organic matter Soil moisture NSDSIs OPTRAM OPTRAM-NSDSI Digital soil mapping |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2025.132980 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Obtaining accurate spatial information on soil organic matter (SOM) is crucial for understanding global carbon cycle. Digital soil mapping (DSM) has become an effective method for mapping SOM, in which selection of influential environmental covariates plays an important role. Soil moisture (SM) can serve as a potential covariate, especially it can be estimated at large spatial scales thanks to remote sensing. The normalized shortwave- infrared difference bare soil moisture indices (NSDSIs) based on Landsat SWIR bands generated at bare soil period has been employed in SOM mapping previously. However, soil is usually covered by vegetation, it is thus necessary to develop new SM indices applicable to areas covered with vegetation, and examine how SM indices perform in areas with different vegetation densities. In this paper, we developed a new SM index by introducing NSDSIs to the Optical TRApezoid Model (OPTRAM-NSDSI), and compared it with the original OPTRAM with the shortwave infrared transformed reflectance (OPTRAM-STR), as well as NSDSIs. SM indices were generated across two study areas, i.e. Zhuxi, Fujian (104 samples and 43.93 km2 with forestland and farmland as main land uses) and Heshan, Heilongjiang (106 samples and 60 km2 with primarily farmland) in China. The Integrated Nested Laplace Approximation with the Stochastic Partial Differential Equation approach was utilized as the SOM prediction model. The results suggest that adding SM variables into the commonly-used environmental covariates improves the prediction accuracies. The highest accuracy improvement of 26.8% in terms of Lin's concordance correlation coefficient in Zhuxi is obtained by NSDSIs, and the highest improvement of 56.7% in Heshan is obtained by OPTRAM-NSDSI. This may indicate that OPTRAM-NSDSI is more effective in areas with higher vegetation densities while NSDSIs in areas with lower densities. Furthermore, the optimal image dates for SM estimation are probably at the vegetation green-up stage. This study provides a reference for using SM information to improve SOM mapping in areas covered with vegetation. |
| URL标识 | 查看原文 |
| WOS关键词 | CONCORDANCE CORRELATION-COEFFICIENT ; OPTICAL TRAPEZOID MODEL ; AIR-TEMPERATURE ; CROPLANDS ; CAPACITY ; SPACE ; NDVI |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001437226200001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/213202]  |
| 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 | Yang, Lin |
| 作者单位 | 1.Fujian Normal Univ, Sch Geog Sci, Fuzhou 350117, Peoples R China 2.Fujian Normal Univ, Minist Educ, Key Lab Humid Subtrop Ecogeog Proc, Fuzhou 350117, Peoples R China; 3.Lawrence Berkeley Natl Lab, Climate & Ecosyst Sci Div, Berkeley, CA 94720 USA; 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; 5.Nanjing Univ, Frontiers Sci Ctr Crit Earth Mat Cycling, Nanjing 210023, Peoples R China; 6.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing 210023, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Yang, Chenconghai,Yang, Lin,Zhang, Lei,et al. Applicability of three remote sensing based soil moisture variables for mapping soil organic matter in areas with different vegetation densities[J]. JOURNAL OF HYDROLOGY,2025,655:132980. |
| APA | Yang, Chenconghai.,Yang, Lin.,Zhang, Lei.,Shen, Feixue.,Fu, Di.,...&Zhou, Chenghu.(2025).Applicability of three remote sensing based soil moisture variables for mapping soil organic matter in areas with different vegetation densities.JOURNAL OF HYDROLOGY,655,132980. |
| MLA | Yang, Chenconghai,et al."Applicability of three remote sensing based soil moisture variables for mapping soil organic matter in areas with different vegetation densities".JOURNAL OF HYDROLOGY 655(2025):132980. |
入库方式： OAI收割
来源：地理科学与资源研究所
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