JOURNAL OF NATURAL RESOURCES ›› 2016, Vol. 31 ›› Issue (11): 1949-1957.doi: 10.11849/zrzyxb.20151393

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Comparison of Rocky Desertification Detection Ability of GF-1 and Landsat-OLI Based on Vegetation Index

ZHU Da-yun, XIONG Kang-ning, XIAO Hua, LAN Jia-cheng   

  1. School of Karst, Guizhou Normal University/State Key Engineering Technology Research Center for Karst Rocky Desertification Rehabilitation, Guiyang 550001, China
  • Received:2015-12-16 Revised:2016-04-23 Online:2016-11-20 Published:2016-11-20
  • Supported by:
    “13th Five-Year” National Key Research and Development Plan, No.2016YFC0502601; Science and Technology Fund of Guizhou, No.〔2016〕1101 and 〔2015〕2111; Doctor Research Fund of Guizhou Normal University in 2016

Abstract: Vegetation index is one of the major parameters in rocky desertification information extraction by using multi-source satellite images. Based on GF-1 and Landsat-OLI, this paper compared the detachability and detection ability of multiple vegetation indices with Euclidean distance between them, so as to choose an optimal parameter from satellite images and acquire the accurate rocky desertification information. It is proved that Landsat-OLI is better than GF-1 in classifying different grades of rocky desertification and separating rocky desertification region from non-desertification region, and it has 71 parameters with Euclidean distance value greater than the threshold value of 1.56. It is easy to distinguish the rocky desertification area from non-karst area through the Euclidean distance. When classifying different grades of rocky desertification, band difference and ratio are better than single spectral index. Finally, the recommended optimal vegetation index of rocky desertification information extraction from GF-1 images and Landsat-OLI images is NDVI, followed by GRNDVI.

Key words: euclidean distance, GF-1, Landsat-OLI, optimal vegetation index, rocky desertification

CLC Number: 

  • Q948