Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation.

By Anatoly A. Gitelson. Journal of plant physiology, 2004

1,161 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/17bbaf2bc96f8bcf75144485ff49b6a8c7c440ae

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Citations in the corpus

The multispectral separability of Costa Rican rainforest types with support vector machines and Random Forest decision trees (2010, methodology): “Indices ND53, WDRVI and NDVI showed similar average M values and number of well-separated forest types, though EVI performed poorly (figures 3(a) and 3(b)).”
Comparison of different vegetation indices for the remote assessment of green leaf area index of crops (2011, methodology): “…al., 1996, 1997), the Green Atmospherically Resistant Vegetation Index, GARI (Gitelson et al., 1996), theWide Dynamic Range Vegetation Index, WDRVI (Gitelson, 2004), the green and red-edge chlorophyll indices, CIGreen and CIRed-edge, respectively (Gitelson et al., 2003a, 2003c; Gitelson et al.,…”
Performance evaluation of spectral vegetation indices using a statistical sensitivity function (2007, background): “The sensitivity of WDRVI is relatively consistent over the entire range of LAI, but it is inferior to NDVI (when LAIb2.”
Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications (2017, methodology): “Hence, NDVI reaches saturation in this way more easily. us, Gitelson [64] proposed theWide Dynamic Range Vegetation Index (WDRVI), which can be expressed as follows: WDRVI = ( nir − red)( nir + red) .”
LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands (2011, methodology): “Furthermore, dynamic range of an index is computed as the difference between the maximum and the minimum values of it, the wider the dynamic range, for the same bands, the more robust the index is (Gitelson, 2004).”
Monitoring Maize (Zea mays L.) Phenology with Remote Sensing (2004, background): “1139 Viña, Gitelson, Rundquist, Keydan, Leavitt & Schepers in Agronomy Journal (2004) 96.”
Water and Nitrogen Effects on Active Canopy Sensor Vegetation Indices (2011, background): “So, the expected saturation of the NDVI (Gitelson, 2004) also occurred in this experiment at these growth stages (Fig.”
Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat (2012, background): “Yet, NDVI is easily saturated with dense canopy, reducing the sensitivity of NDVI to high physiological and biochemical content of plants (Thenkabail et al., 2000; Gitelson, 2004).”
Estimating winter wheat (Triticum aestivum) LAI and leaf chlorophyll content from canopy reflectance data by integrating agronomic prior knowledge with the PROSAIL model (2015, methodology): “…http://dx.doi.org/10.1080/01431161.2015.1041176 © 2015 Taylor & Francis The empirical regression approach is based on statistical regression between target variables and spectral reflectance or vegetation indices (VIs) (Darvishzadeh et al. 2008; Gitelson 2004; Ustin et al. 2009; Viña et al. 2011).”