Broadband vegetation index performance evaluated for a low-cover environment

• Published in: International journal of remote sensing Vol. 27; no. 21; pp. 4715 - 4730
• Main Authors: Baugh, W. M., Groeneveld, D. P.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.11.2006; Taylor and Francis
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Teledetection and vegetation maps; United States; San Luis Valley; Colorado; High performance; Introduced species; Vegetation index; Linear regression; Space remote sensing; Landsat; water table; arid environment; North America; Standards; Landsat satellite; precipitation; aquifers; Arid region; standard samples; Environment; Multidate observation; Antecedent; Pixel
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431160600758543

Fourteen vegetation indices (VIs) were quantitatively evaluated using a Landsat TM dataset spanning 17 years over the San Luis Valley, Colorado, USA to find the best VI for use in sparsely vegetated arid regions. The VIs were compared to the known linear promotional effect of antecedent precipitation in an area of stable water tables. The r 2 value of the linear regression for these indices was used to determine performance. The following published VIs were evaluated: ARVI, DVI, EVI, IPVI, MSAVI, MSAVI 2 , NDVI, NDVI*, PVI, RVI, SAVI, TSAVI, WDVI, and a new index introduced in this paper, NDVI offset . NDVI* and NDVI offset performed best of all the tested VIs, both with r 2  = 0.77. Standard NDVI was a relatively poor performer (r 2  = 0.37). The high performance of NDVI offset is promising for use in regions or multi-temporal sequences that lack saturated NDVI pixels.