Application of satellite remote sensing for mapping wind erosion risk and dust emission-deposition in Inner Mongolia grassland, China
Article first published online: 31 JAN 2012
© 2012 The Authors. Grassland Science © 2012 Japanese Society of Grassland Science
Volume 58, Issue 1, pages 8–19, March 2012
How to Cite
Reiche, M., Funk, R., Zhang, Z., Hoffmann, C., Reiche, J., Wehrhan, M., Li, Y. and Sommer, M. (2012), Application of satellite remote sensing for mapping wind erosion risk and dust emission-deposition in Inner Mongolia grassland, China. Grassland Science, 58: 8–19. doi: 10.1111/j.1744-697X.2011.00235.x
- Issue published online: 6 MAR 2012
- Article first published online: 31 JAN 2012
- Received 9 February 2011; accepted 9 September 2011.
- Advanced Spaceborne Thermal Emission and Reflection Radiometer data;
- dust emission and deposition;
- soil-adjusted vegetation index;
- semiarid grassland;
- wind erosion
Intensive grazing leads to land degradation and desertification of grassland ecosystems followed by serious environmental and social problems. The Xilingol steppe grassland in Inner Mongolia, China, which has been a sink area for dust for centuries, is strongly affected by the negative effects of overgrazing and wind erosion. The aim of this study is the provision of a wind erosion risk map with a spatial high resolution of 25 m to identify actual source and sink areas. In an integrative approach, field measurements of vegetation features and surface roughness length z0 were combined with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image data for a land use classification. To determine the characteristics of the different land use classes, a field observation (ground truth) was performed in April 2009. The correlation of vegetation height and z0 (R2 = 0.8, n = 55) provided the basis for a separation of three main classes, “grassland”, “non-vegetation” and “other”. The integration of the soil-adjusted vegetation index (SAVI) and the spectral information from the atmospheric corrected ASTER bands 1, 2 and 3 (visible to near-infrared) led to a classification of the overall accuracy (OA) of 0.79 with a kappa () statistic of 0.74, respectively. Additionally, a digital elevation model (DEM) was used to identify topographical effects in relation to the main wind direction, which enabled a qualitative estimation of potential dust deposition areas. The generated maps result in a significantly higher description of the spatial variability in the Xilingol steppe grassland reflecting the different land use intensities on the current state of the grassland – less, moderately and highly degraded. The wind erosion risk map enables the identification of characteristic mineral dust sources, sinks and transition zones.