[1]WEI Feng-liang,LIU Ting-xi,ZHANG Sheng-wei,et al.Research for Vegetation Cover Change of Horqin Sandy Land and its Relationship with the Climate Factors[J].Research of Soil and Water Conservation,2012,19(03):254-258.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
19
Number of periods:
2012 03
Page number:
254-258
Column:
Public date:
2012-06-20
- Title:
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Research for Vegetation Cover Change of Horqin Sandy Land and its Relationship with the Climate Factors
- Author(s):
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WEI Feng-liang1, LIU Ting-xi1, ZHANG Sheng-wei1, DING Lei1, CUI De-xin2, ZHAO Ze-feng2
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1. Inner Mongolia Agricultural University, Hohhot 010018, China;
2. Irrigation and Drainage Water Development Center of Inner Mongolia Autonomous Region, Hohhot 010018, China
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- Keywords:
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Horqin sandy land; SAVI; climate factors; information entropy; spatial-temporal variability
- CLC:
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Q948.112
- DOI:
-
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- Abstract:
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The ecological system of drought and semi-arid region area is vulnerable, and the variation of vegetation cover is obious, it is particularly important to provide a theoretical basis for combating desertification through explicating the vegetation cover pattern of desertification area and determining its variability of spatial-temporal and the relationship with climate factors. In this study, Horqin sandy land of the typical desertification in the north China was taken as study area, and soil regulate vegetation index (SAVI) was extract by using the resolution imaging spectrum radiometer (Moderate Resolution Imaging Spectroradiometer, MODIS) surface reflectivity product data, the variability of spatial-temporal of SAVI in the study area was analyzed through the information entropy theory. The relationship between the change of the vegetation cover and the climate factors was further clear by performing the correlation analysis. As a whole, growth situation of vegetation in the east of the study area was better than that in the western region, and growth situation of vegetation in the south was better than that north. The spatial-temporal variability of vegetation pattern was the largest in 2000 and was the least in 2005; and it was the largest in southwest instead of southeast on the spacial scale. Precipitation and temperatures were positively correlated with SAVI, and precipitation had the larger effect on SAVI.