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How to solve small sample size problems in time-series soil organic carbon mapping: New insights from the Third Law of Geography

文献类型：期刊论文

作者Wang, Jingzhe3,10; Zhang, Zipeng2,6; Wang, Yankun1; Qin, Cheng-Zhi10; Chen, Xiangyue9; Zhang, Yinghui4,5,7,8; Hu, Zhongwen4,5,7,8
刊名GEODERMA
出版日期2025-08-01
卷号460页码:117402
关键词Soil organic carbon density (SOCD) Digital soil mapping (DSM) Third Law of Geography Geo-environmental similarity Small sample size
ISSN号0016-7061
DOI10.1016/j.geoderma.2025.117402
产权排序5
文献子类Article
英文摘要Accurate and up-to-date mapping of soil organic carbon density (SOCD) spatial distribution and temporal dynamics is essential for understanding terrestrial ecosystem carbon fluxes and monitoring global climate change. However, the available historical soil sample data remained insufficient to meet the high-precision spatiotemporal mapping requirements of SOCD across large regions. Therefore, we attempted to apply the Third Law of Geography (also known as the Law of Geographic Similarity) to address the issue of small sample size in modelling. In this study, we proposed a weighted multivariate similarity index and a similarity threshold index, along with the identification of optimal thresholds for measuring geographic similarity, to effectively increase the soil sample size. Based on the different input samples, we designed various modeling schemes for SOCD mapping. Our results suggest that the geographic similarity threshold-driven framework successfully reconciles the trade-off between sample quantity and quality, increasing sample sizes by up to three times while enhancing spatial representativeness and reducing prediction uncertainty. Accuracy evaluation and uncertainty analysis consistently demonstrated that models incorporating similarity-based input samples outperformed those relying solely on limited local samples. In comparison to the model utilizing only a limited data sample, the S1-1980 s model, achieved a coefficient of determination (R2) of 0.04 and a root mean square error (RMSE) of 2.47 Kg C m- 2. Conversely, the S3-1980 s model, based on similarity-expanded samples, demonstrated a significant improvement, achieving an R2 of 0.64 and a RMSE of 1.36 Kg C m- 2. Consequently, the prediction using the improved model achieved accurate detection of regional spatiotemporal patterns of SOCD. This study provides a reference for addressing small sample size issues in time-series soil organic carbon mapping.
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WOS关键词DATASET ; CHINA ; INFORMATION
WOS研究方向Agriculture
语种英语
WOS记录号WOS:001519912200001
出版者ELSEVIER
源URL[http://ir.igsnrr.ac.cn/handle/311030/215377]  
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Wang, Jingzhe
作者单位1.Shenzhen Polytech Univ, Internet Things Res Inst, Shenzhen 518055, Peoples R China;
2.Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi 830017, Peoples R China;
3.Shenzhen Polytech Univ, Sch Artificial Intelligence, Shenzhen 518055, Peoples R China;
4.Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China
5.Shenzhen Univ, Guangdong Hong Kong Macau Joint Lab Smart Cities, Shenzhen 518060, Peoples R China;
6.Xinjiang Univ, Xinjiang Key Lab Oasis Ecol, Urumqi 830017, Peoples R China;
7.Shenzhen Univ, Guangdong Key Lab Urban Informat, Hong Kong 518060, Peoples R China;
8.Shenzhen Univ, MNR Key Lab Geoenvironm Monitoring Great Bay Area, Hong Kong 518060, Peoples R China;
9.Hunan Univ Sci & Technol, Sch Earth Sci & Spatial Informat Engn, Xiangtan 411201, Peoples R China;
10.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;
推荐引用方式
GB/T 7714		 Wang, Jingzhe,Zhang, Zipeng,Wang, Yankun,et al. How to solve small sample size problems in time-series soil organic carbon mapping: New insights from the Third Law of Geography[J]. GEODERMA,2025,460:117402.
APA Wang, Jingzhe.,Zhang, Zipeng.,Wang, Yankun.,Qin, Cheng-Zhi.,Chen, Xiangyue.,...&Hu, Zhongwen.(2025).How to solve small sample size problems in time-series soil organic carbon mapping: New insights from the Third Law of Geography.GEODERMA,460,117402.
MLA Wang, Jingzhe,et al."How to solve small sample size problems in time-series soil organic carbon mapping: New insights from the Third Law of Geography".GEODERMA 460(2025):117402.

入库方式： OAI收割

来源：地理科学与资源研究所

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