Chinese Geographical Science ›› 2015, Vol. 25 ›› Issue (2): 213-223.doi: 10.1007/s11769-014-0693-2

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Monitoring Soil Salt Content Using HJ-1A Hyperspectral Data: A Case Study of Coastal Areas in Rudong County, Eastern China

LI Jianguo1, PU Lijie1,2, ZHU Ming1, DAI Xiaoqing1, XU Yan1, CHEN Xinjian1, ZHANG Lifang3, ZHANG Runsen1   

  1. 1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China;
    2. Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resources, Nanjing 210023, China;
    3. School of Public Administration, Nanjing University of Finance & Economics, Nanjing 210046, China)
  • Received:2013-03-04 Revised:2013-07-23 Online:2015-01-27 Published:2015-03-10
  • Contact: PU Lijie
  • Supported by:

    Under the auspices of National Natural Science Foundation of China (No. 41230751, 41101547), Scientific Research Foundation of Graduate School of Nanjing University (No. 2012CL14)


Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, HuanJing-Hyper Spectral Imager (HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm (NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index (NSSRI) was constructed from continuum-removed reflectance (CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area (NDVI705 < 0.2). The soil adjusted salinity index (SAVI) was applied to predict the soil salt content in the vegetation-covered area (NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping (R2= 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.

Key words: soil salt content, normalized differential vegetation index (NDVI), hyperspectral data, HuanJing-Hyper Spectral Imager (HJ-HSI), coastal area, eastern China