• Journal of Infrared and Millimeter Waves
  • Vol. 36, Issue 2, 225 (2017)
GAO Yong-Gang1、2、3、4、* and XU Han-Qiu1、2、3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    DOI: 10.11972/j.issn.1001-9014.2017.02.017 Cite this Article
    GAO Yong-Gang, XU Han-Qiu. Estimation of multi-scale urban vegetation coverage based on multi-source remote sensing images[J]. Journal of Infrared and Millimeter Waves, 2017, 36(2): 225 Copy Citation Text show less

    Abstract

    The vegetation coverage from multi-source at multi-scale and multi-source at the same scale in urban area was studied. The Landsat 7 ETM+, SPOT 5 and IKONOS remote sensing image data were taken as the data source. The vegetation coverage with different spatial resolutions derived from a 1∶500 topographic map as the reference map by grid method was taken as reference. The accuracies of fraction vegetation coverage extracted from the images, wich were radiometrically corrected using different models, were compared. An optimal radiometric correction model for the extraction of fraction vegetation coverage in urban areas was proposed. The results show that ICM model is the best radiometric correction model for estimating fraction vegetation coverage in urban area. NDVI is the best vegetation index for fraction vegetation coverage estimation for high resolution remote sensing images, while the best vegetation indices for estimating fraction vegetation coverage from moderate spatial resolution images are the RVI and MSAVI. For the studies area, the GI model is more accurate than the CR model in estimating the vegetation coverage.
    GAO Yong-Gang, XU Han-Qiu. Estimation of multi-scale urban vegetation coverage based on multi-source remote sensing images[J]. Journal of Infrared and Millimeter Waves, 2017, 36(2): 225
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