Estimating models of vegetation fractional coverage
based on remote sensing images at different radiometric correction
levels

doi:10.1007/s11461-009-0057-8

Front. For. China

2009, Vol. 4

Issue (4) : 402-408 https://doi.org/10.1007/s11461-009-0057-8

Research articles

Estimating models of vegetation fractional coverage based on remote sensing images at different radiometric correction levels

Zhujun GU¹,Zhiyuan ZENG²,Wei ZHENG²,Zhenlong ZHANG²,Zifu HU²,Xuezheng SHI³,Dongsheng YU⁴,

1.School of Geography Science, Nanjing Xiaozhuang University, Nanjing 211171, China；State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China；School of Geography Science, Nanjing Normal University, Nanjing 210097, China；Graduate University of Chinese Academy of Sciences, Beijing 100039, China; 2.School of Geography Science, Nanjing Normal University, Nanjing 210097, China; 3.State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China；Graduate University of Chinese Academy of Sciences, Beijing 100039, China; 4.State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China;

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Abstract The images of post atmospheric correction reflectance (PAC), top of atmosphere reflectance (TOA), and digital number (DN) of a SPOT5 HRG remote sensing image of Nanjing, China were used to derive four vegetation indices (VIs), that is, normalized difference vegetation index (NDVI), transformed vegetation index (TVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI). Based on these VIs and the vegetation fractional coverage (VFC) data obtained from field measurements, thirty-six VI-VFC relationship models were established. The results showed that cubic polynomial models based on NDVI and TVI from PAC were the best, followed by those based on SAVI and MSAVI from DN, with their accuracies being slightly higher than those of the former two models when VFC > 0.8. The accuracies of these four models were higher in medium densely vegetated areas (VFC = 0.4−0.8) than in sparsely vegetated areas (VFC = 0−0.4). All the models could be used elsewhere via the introduction of a calibration model. In VI-VFC modeling, using VIs derived from different radiometric correction levels of remote sensing images could help explore and show valuable information from remote sensing data and thus improve the accuracy of VFC estimation.

Keywords radiometric correction vegetation index vegetation fractional coverage model

Issue Date: 05 December 2009

Cite this article:

Zhujun GU,Wei ZHENG,Zifu HU, et al. Estimating models of vegetation fractional coverage based on remote sensing images at different radiometric correction levels[J]. Front. For. China, 2009, 4(4): 402-408.

URL:

https://academic.hep.com.cn/ffc/EN/10.1007/s11461-009-0057-8
https://academic.hep.com.cn/ffc/EN/Y2009/V4/I4/402

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