Chinese Geographical Science

, Volume 25, Issue 3, pp 283–294 | Cite as

Mapping soil salinity using a similarity-based prediction approach: A case study in Huanghe River Delta, China

  • Lin Yang
  • Chong Huang
  • Gaohuan Liu
  • Jing Liu
  • A-Xing Zhu
Article

Abstract

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.

Keywords

soil salinization similarity-based prediction approach digital soil mapping Huanghe (Yellow) River Delta environmental factor 

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Copyright information

© Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Lin Yang
    • 1
  • Chong Huang
    • 1
  • Gaohuan Liu
    • 1
  • Jing Liu
    • 2
  • A-Xing Zhu
    • 1
    • 2
    • 3
  1. 1.State Key Laboratory of Resources and Environment Information System, Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.Department of GeographyUniversity of Wisconsin-MadisonMadisonUSA
  3. 3.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application and School of GeographyNanjing Normal UniversityNanjingChina

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