Spatiotemporal Variations in Grassland Desertification Based on Landsat Images and Spectral Mixture Analysis in Yanchi County of Ningxia, China

Facing the worsening degradation of grasslands, state and local governments in China have implemented a series of ecological protection projects. Ningxia Hui Autonomous Region was the first province in China to implement a region-wide grazing ban, the effect of which has become contentious at all levels of government and a topic of public concern. The change of grassland desertification is the most direct indicator of the grazing ban's effect. This paper chooses Yanchi County in Ningxia as the study area to analyze the grassland desertification situation. Based on a series of Landsat TM/ETM+ images, field observations and expert review, a Ningxia grassland desertification classification and grading system was constructed. Then, spectral mixture analysis (SMA) and a decision-tree method were used to interpret images of the study area from 4 years: 1993, 2000, 2006, and 2011. The following results were obtained: the area of desertified grassland decreased gradually from 4142 km2 in 1993 to 3695 km2 in 2011, a decrease of 10.80%. The severity of desertification also declined as the area of severely desertified grassland gradually decreased to 324 km2 in 2011 from 1093 km2 in 1993, a decrease of 70.34%. The annual reduction rate of the desertified grassland area reached its peak during the period 2000-2006. In particular, the areas of severely desertified grassland declined by 8.86% annually. In a situation of declining rainfall, human factors (such as ecological protection policy) have become a major cause of ongoing grassland desertification reversal and restoration of grassland vegetation.

[1]  Quan Sun,et al.  ractional vegetation cover estimation in arid and semi-arid environments using J-1 satellite hyperspectral data , 2012 .

[2]  Maria C. Torres-Madronero,et al.  Unmixing Analysis of a Time Series of Hyperion Images Over the Guánica Dry Forest in Puerto Rico , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Wang Tao,et al.  Spatial-temporal Changes of Sandy Desertified Land During Last 5 Decades in Northern China , 2004 .

[4]  Claudio Zucca,et al.  Towards a World Desertification Atlas. Relating and selecting indicators and data sets to represent complex issues , 2012 .

[5]  Li Run-lin Dynamic changes and driving force of grassland sandy desertification in Xilin Gol:A case study of Zhenglan Banner , 2011 .

[6]  F. van den Bergh,et al.  Limits to detectability of land degradation by trend analysis of vegetation index data , 2012 .

[7]  T. Kemper,et al.  A new tool for variable multiple endmember spectral mixture analysis (VMESMA) , 2005 .

[8]  Xi Chen,et al.  A comparison of methods for estimating fractional vegetation cover in arid regions , 2011 .

[9]  Philip C. Goodell,et al.  Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data , 2011, Int. J. Appl. Earth Obs. Geoinformation.

[10]  D. Roberts,et al.  Hierarchical Multiple Endmember Spectral Mixture Analysis (MESMA) of hyperspectral imagery for urban environments , 2009 .

[11]  Jian Yang,et al.  Landsat remote sensing approaches for monitoring long-term tree cover dynamics in semi-arid woodlands: Comparison of vegetation indices and spectral mixture analysis , 2012 .

[12]  Chenghu Zhou,et al.  A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data , 2009, Sensors.

[13]  Antonio J. Plaza,et al.  Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[14]  Ning Wang,et al.  Land surface emissivity retrieval from satellite data , 2013 .

[15]  A. Karnieli,et al.  A review of mixture modeling techniques for sub‐pixel land cover estimation , 1996 .

[16]  Yan Chang Macro-scale Survey and Dynamic Studies of Sandy Land in Ningxia by Remote Sensing , 2003 .

[17]  Emilio Chuvieco,et al.  Satellite remote sensing analysis to monitor desertification processes in the crop-rangeland boundary of Argentina , 2002 .

[18]  W. Lei Effects of grazing prohibition on grassland coverage——A case study at Yanchi County of Ningxia , 2011 .

[19]  Tao Wang,et al.  Monitoring recent trends in the area of aeolian desertified land using Landsat images in China’s Xinjiang region , 2012 .

[20]  Francesco Morari,et al.  Limits and Potentialities of Studying Dryland Vegetation Using the Optical Remote Sensing , 2008 .

[21]  Alan Grainger,et al.  Application of indicator systems for monitoring and assessment of desertification from national to global scales , 2011 .

[22]  Z. Qin,et al.  Monitoring and analysis of grassland desertification dynamics using Landsat images in Ningxia, China , 2013 .

[23]  Patrick Hostert,et al.  Differences in Landsat-based trend analyses in drylands due to the choice of vegetation estimate , 2011 .

[24]  F. Morari,et al.  Monitoring desertification in a Savannah region in Sudan using Landsat images and spectral mixture analysis , 2012 .

[25]  Gregory S. Okin,et al.  Relative spectral mixture analysis — A multitemporal index of total vegetation cover , 2005 .

[26]  D. Lobell,et al.  Quantifying vegetation change in semiarid environments: precision and accuracy of spectral mixture analysis and the normalized difference vegetation index. , 2000 .

[27]  José A. Sobrino,et al.  Satellite-derived land surface temperature: Current status and perspectives , 2013 .