Study of the desertification index based on the albedo-MSAVI feature space for semi-arid steppe region

  • Zhenhua Wu
  • Shaogang Lei
  • Zhengfu BianEmail author
  • Jiu Huang
  • Yong Zhang
Original Article


Desertification has been listed as the top of ten major problems affecting global environmental changes, and represents one of the important reasons of semi-arid grassland degradation. It is therefore crucial to understand ecological environment of semi-arid grasslands and temporal and spatial changes in real time for regional and local environmental protection and management. At present, remote sensing technology is being widely used in monitoring and evaluation of land desertification due to its wide observation range, large amount of information, fast data updating and high accuracy. It represents an advanced method for remote sensing monitoring of desertification by extracting various indicators and constructing feature space. Based on this, this study used Landsat images and field survey data to establish a desertification index (SASDI) model based on the albedo-MSAVI (Modified Soil Adjusted Vegetation Index) feature space and analyze the relationship between desertification and surface quantitative parameters in semi-arid grassland area. Results show that the SASDI model has a high correlation (R2 = 0.7585) with the organic matter in the soil surface and makes full use of multi-dimensional remote sensing information. The index reflects the surface cover, water, and heat combination as well as changes of the desertification land, with a clear biophysical significance. Moreover, the index is simple and easy to obtain, facilitating to quantitative analysis and continuous monitoring of desertification in semi-arid grasslands.


Albedo MSAVI Feature space Desertification index Remote sensing monitoring 



This study was supported by the Seventh Project “The National Key Research and Development Program of China 2016YFC0501107”, “National Natural Science Foundation of China U1710120” and “National key projects for basic science and technology work of China 2014FY110800”.


This research was funded by (Key Technologies of Landscape Ecological Restoration of Large-scale Coal-power Bases) Grant number (2016YFC0501107), National Natural Science Foundation of China (U1710120) and National key projects for basic science and technology work of China (2014FY110800).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zhenhua Wu
    • 1
    • 2
    • 3
  • Shaogang Lei
    • 2
    • 3
  • Zhengfu Bian
    • 2
    • 3
    Email author
  • Jiu Huang
    • 2
    • 3
  • Yong Zhang
    • 4
  1. 1.Institute of Land and ResourcesChina University of Mining and TechnologyXuzhouChina
  2. 2.Ministry of Education Engineering Research Center for Mine Ecological RestorationXuzhouChina
  3. 3.School of Environment Science and Spatial InformaticsChina University of Mining and TechnologyXuzhouChina
  4. 4.School of Finance and Public ManagementAnhui University of Finance and EconomicsBengbuChina

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