Mapping soil salinity using a similarity-based prediction approach: A case study in Huanghe River Delta, China
文献类型：SCI/SSCI论文
| 作者 | Yang L.; Huang, C.; Liu, G. H.; Liu, J.; Zhu, A. X. |
| 发表日期 | 2015 |
| 关键词 | soil salinization similarity-based prediction approach digital soil mapping Huanghe (Yellow) River Delta environmental factor salt-affected soils spatial-distribution land-use classification coefficient region model iran |
| 英文摘要 | Spatial distribution of soil salinity can be estimated based on its environmental factors because soil salinity is strongly affected and indicated by environmental factors. Different with other properties such as soil texture, soil salinity varies with short-term time. Thus, how to choose powerful environmental predictors is especially important for soil salinity. This paper presents a similarity-based prediction approach to map soil salinity and detects powerful environmental predictors for the Huanghe (Yellow) River Delta area in China. The similarity-based approach predicts the soil salinities of unsampled locations based on the environmental similarity between unsampled and sampled locations. A dataset of 92 points with salt data at depth of 30-40 cm was divided into two subsets for prediction and validation. Topographical parameters, soil textures, distances to irrigation channels and to the coastline, land surface temperature from Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Indices (NDVIs) and land surface reflectance data from Landsat Thematic Mapper (TM) imagery were generated. The similarity-based prediction approach was applied on several combinations of different environmental factors. Based on three evaluation indices including the correlation coefficient (CC) between observed and predicted values, the mean absolute error and the root mean squared error we found that elevation, distance to irrigation channels, soil texture, night land surface temperature, NDVI, and land surface reflectance Band 5 are the optimal combination for mapping soil salinity at the 30-40 cm depth in the study area (with a CC value of 0.69 and a root mean squared error value of 0.38). Our results indicated that the similarity-based prediction approach could be a vital alternative to other methods for mapping soil salinity, especially for area with limited observation data and could be used to monitor soil salinity distributions in the future. |
| 出处 | Chinese Geographical Science |
| 卷 | 25 |
| 期 | 3 |
| 页 | 283-294 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1002-0063 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/38982]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Yang L.,Huang, C.,Liu, G. H.,et al. Mapping soil salinity using a similarity-based prediction approach: A case study in Huanghe River Delta, China. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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