A GIS-Based Assessment of Vulnerability to Aeolian Desertification in the Source Areas of the Yangtze and Yellow Rivers

Aeolian desertification is a kind of land degradation that is characterized by aeolian activity, resulting from the responses of land ecosystems to climate change and anthropogenic disturbances. The source areas of the Yangtze and Yellow Rivers are typical regions of China’s Tibetan Plateau affected by aeolian desertification. We assessed the vulnerability of these areas to aeolian desertification by combining remote sensing with geographical information system technologies. We developed an assessment model with eight indicators, whose weights were determined by the analytical hierarchy process. Employing this model, we analyzed the spatial distribution of vulnerability to aeolian desertification and its changes from 2000 to 2010, and discuss the implications. Overall, low-vulnerability land was the most widespread, accounting for 64%, 62%, and 71% of the total study area in 2000, 2005, and 2010, respectively. The degree of vulnerability showed regional differences. In the source areas of the Yangtze River, land with high or very high vulnerability accounted for 17.4% of this sub-region in 2010, versus 2.6% in the source areas of the Yellow River. In the Zoige Basin, almost all of the land had very low to low vulnerability. To understand the change in vulnerability to aeolian desertification, we calculated an integrated vulnerability index (IVI). This analysis indicated that the vulnerability to aeolian desertification increased from 2000 to 2005 (IVI increased from 2.1709 to 2.2463), and decreased from 2005 to 2010 (IVI decreased from 2.2463 to 2.0057). Increasing regional temperatures appear to be primarily responsible for the change in vulnerability to aeolian desertification throughout the region. The effects of other factors (climatic variation and human activities) differed among the various sub-regions. The implementation of the ecological restoration project has achieved a noticeable effect since 2005. Our results provide empirical support for effort to protect the ecology of this ecologically fragile region.

[1]  Jun Ye Multicriteria fuzzy decision-making method using entropy weights-based correlation coefficients of interval-valued intuitionistic fuzzy sets , 2010 .

[2]  Lindsay C. Stringer,et al.  Mapping the vulnerability of crop production to drought in Ghana using rainfall, yield and socioeconomic data , 2012 .

[3]  C. Yan,et al.  Driving forces of aeolian desertification in the source region of the Yellow River: 1975–2005 , 2013, Environmental Earth Sciences.

[4]  T. L. Saaty A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[5]  J. A. Mabbutt,et al.  Desertification indicators , 1986 .

[6]  Zhaoyin Wang,et al.  An environmental gradient of vegetative controls upon channel planform in the source region of the Yangtze and Yellow Rivers , 2014 .

[7]  Mladen Todorovic,et al.  A GIS-based approach for desertification risk assessment in Apulia region, SE Italy , 2012 .

[8]  Tarmo K. Remmel,et al.  Tracking Desertification in California Using Remote Sensing: A Sand Dune Encroachment Approach , 2010, Remote. Sens..

[9]  L. Salvati,et al.  Performance evaluation and cost assessment of a key indicator system to monitor desertification vulnerability , 2012 .

[10]  Zhang Dong-hai,et al.  The spatial-temporal changes of vegetation coverage in the Three-River Headwater Region in recent 12 years , 2013 .

[11]  Guangyin Hu,et al.  Driving forces responsible for aeolian desertification in the source region of the Yangtze River from 1975 to 2005 , 2012, Environmental Earth Sciences.

[12]  Dzung L. Pham,et al.  Spatial Models for Fuzzy Clustering , 2001, Comput. Vis. Image Underst..

[13]  Murray Turoff,et al.  The Delphi Method: Techniques and Applications , 1976 .

[14]  S. Stefanidis,et al.  Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP) , 2013, Natural Hazards.

[15]  Shuangshuang Li,et al.  NDVI-Based Analysis on the Influence of Climate Change and Human Activities on Vegetation Restoration in the Shaanxi-Gansu-Ningxia Region, Central China , 2015, Remote. Sens..

[16]  Mingyuan Du,et al.  Mutual influence between human activities and climate change in the Tibetan Plateau during recent years , 2004 .

[17]  E. Chuvieco,et al.  Integration of ecological and socio-economic factors to assess global vulnerability to wildfire , 2014 .

[18]  Shuangshuang Li,et al.  Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001-2012 , 2015, Remote. Sens..

[19]  Ting Hua,et al.  Controls on desertification during the early twenty-first century in the Water Tower region of China , 2014, Regional Environmental Change.

[20]  D. Weindorf,et al.  Multi-temporal assessment of land sensitivity to desertification in a fragile agro-ecosystem: Environmental indicators , 2012 .

[21]  M. Macchiato,et al.  Integrated Indicators for the Estimation of Vulnerability to Land Degradation , 2013 .

[22]  Sofia Bajocco,et al.  Land sensitivity to desertification across Italy: Past, present, and future , 2011 .

[23]  Shao Quanqin,et al.  The Spatial and Temporal Characteristics of Grassland Degradation in the Three-River Headwaters Region in Qinghai Province , 2008 .

[24]  Sergio M. Vicente-Serrano,et al.  Drought Variability and Land Degradation in Semiarid Regions: Assessment Using Remote Sensing Data and Drought Indices (1982-2011) , 2015, Remote. Sens..

[25]  C. E,et al.  Warming and drying trends on the Tibetan Plateau (1971–2005) , 2010 .

[26]  L. Yong Assessment on Driving Force of Climate Change & Livestock Grazing Capacity to Grassland Sanding in Ruoergai , 2007 .

[27]  R Ramanathan,et al.  A note on the use of the analytic hierarchy process for environmental impact assessment. , 2001, Journal of environmental management.

[28]  Guangyin Hu,et al.  The developmental trend and influencing factors of aeolian desertification in the Zoige Basin, eastern Qinghai-Tibet Plateau , 2015 .

[29]  Guangyin Hu,et al.  Aeolian desertification and its causes in the Zoige Plateau of China’s Qinghai–Tibetan Plateau , 2010 .

[30]  Q. Shao,et al.  Integrated assessment on the effectiveness of ecological conservation in Sanjiangyuan National Nature Reserve , 2013 .

[31]  Ainong Li,et al.  Eco-environmental vulnerability evaluation in mountainous region using remote sensing and GIS—A case study in the upper reaches of Minjiang River, China , 2006 .

[32]  Ian D. Bishop,et al.  Linking objective and subjective modelling for landuse decision-making , 1998 .

[33]  Stephen J. Carver,et al.  Integrating multi-criteria evaluation with geographical information systems , 1991, Int. J. Geogr. Inf. Sci..

[34]  S. Mantel,et al.  The role of GIS and remote sensing in land degradation assessment and conservation mapping: some user experiences and expectations , 2001 .

[35]  Yanglin Wang,et al.  Analyzing nonlinear variations in terrestrial vegetation in China during 1982–2012 , 2015, Environmental Monitoring and Assessment.