Literature DB >> 21105420

[Study on the relation between fraction cover and mixed spectra in karst environment].

Bo Liu1, Yue-min Yue, Ru Li, Ke-lin Wang, Bing Zhang, Qing-xi Tong.   

Abstract

Karst rocky desertification is one of the most serious eco-environmental problems of land degradation in karst regions, southwest China. The fractional cover of vegetation and exposed bedrock are the main land surface symptoms and essential assessing indicators of karst rocky desertification. To assess the extent of rocky desertification in complex karst environments, the information of multiple land cover types fraction is needed. Based on in situ spectral reflectance data, this study proposed several spectral indices and explored the relationship between spectral features of main land cover types and their responding fractional cover. The results showed that spectral indices have much higher correlation coefficients with fractional cover than does spectral reflectance. Vegetation indices have good linear relation with fractional cover of photosynthetic vegetation (PV). The proposed spectral indices have high correlation coefficients with fractional cover of non-photosynthetic vegetation (NPV) and bare soil, with R2 0.70 and 0.73, respectively. Lower correlation coefficients (R2 = 0.55) with the factional cover of exposed bedrock, were observed. The absorption depth of four forms of the proposed indices has the highest correlation coefficient with the fractional cover of NPV, bare soil, and exposed rock. This study indicates that hyperspectral remote sensing has the potential for the extraction of karst rocky desertification information.

Entities:  

Year:  2010        PMID: 21105420

Source DB:  PubMed          Journal:  Guang Pu Xue Yu Guang Pu Fen Xi        ISSN: 1000-0593            Impact factor:   0.589


  1 in total

1.  Using principal component analysis and annual seasonal trend analysis to assess karst rocky desertification in southwestern China.

Authors:  Zhiming Zhang; Zhiyun Ouyang; Yi Xiao; Yang Xiao; Weihua Xu
Journal:  Environ Monit Assess       Date:  2017-05-16       Impact factor: 2.513

  1 in total

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