JOURNAL OF NATURAL RESOURCES ›› 2012, Vol. 27 ›› Issue (8): 1340-1348.doi: 10.11849/zrzyxb.2012.08.008

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Estimating Vegetation Coverage of Typical Degraded Grassland in the Northern Tianshan Mountains

YANG Feng1,2, LI Jian-long2, QIAN Yu-rong3, YAN Qi4, JIN Guo-ping5   

  1. 1. College of Agronomy, Sichuan Agricultural University/Key Laboratory of Crop Ecophysiology and Farming System in Southwest, Ministry of Agriculture, Chengdu 611130, China;
    2. School of Life Science, Nanjing University, Nanjing 21009;
    3. College of Software, Xinjiang University, Urumqi 830046;
    4. National Environment Monitoring Center, Beijing 100012, China;
    5. Fukang Animal Husbandry Bureau, Fukang 831500, China
  • Received:2011-01-18 Revised:2012-02-09 Online:2012-08-20 Published:2012-08-20

Abstract: Grassland is one of the most widespread vegetation types worldwide, which is also an important composition of terrestrial ecosystem. Grassland degradation is a serious ecological problem in the world. Therefore, monitoring and estimating grassland degradation correctly plays an important role for managing and controlling grassland degradation and desertification. In this study, the monitoring models of grassland degradation were built for monitoring the status of grassland using remote sensing data and vegetation coverage. In addition, the relationships between five vegetation indices (Ratio Vegetation Index, RVI; Normalized Difference Vegetation Index, NDVI; Green Normalized Difference Vegetation Index, GNDVI; Soil-Adjusted Vegetation Index, SAVI; Modified Soil-Adjusted Vegetation Index, MSAVI) were discussed. The results showed that the correlations between MSAVI, GNDVI and vegetation coverage were better than other vegetation indices. Comparing the regress models between five vegetation indices and vegetation coverage, the models built by MSAVI and GNDVI appeared better effect. The optimum models for monitoring the status of grassland degradation were y=138.45xMSAVI-1.2482 (R2=0.5027, P<0.01) and y=2596.66x2GNDVI-561.54xGNDVI+38.488(R2=0.6053, P<0.01)respectively.

Key words: degraded grassland, monitoring model, vegetation coverage, vegetation index, Xinjiang grassland

CLC Number: 

  • TP79:Q948.12