This paper examines the possibility of exploiting ground reflectance in the near-infrared (NIR) for monitoring grassland phytomass on a temporal basis. Three new spectral vegetation indices (Infrared Slope Index, ISI; Near Infrared Difference Index, NIDI; and Normalized Difference Structural Index, NDSI), which are based on the reflectance values in the H25 (863-881 nm) and the H18 (745-751 nm) Chris Proba (mode 5) bands, are proposed. Ground measurements of hyperspectral reflectance and phytomass were made at six grassland sites in the Italian and Austrian mountains using a hand-held spectroradiometer. At full canopy cover, strong saturation was observed for many traditional vegetation indices (Normalised Difference Vegetation Index, Modified Simple Ratio, Enhanced Vegetation Index, Enhanced Vegetation Index 2, Renormalised Difference Vegetation Index, Wide Dynamic Range Vegetation Index). Conversely, ISI and NDSI were linearly related to grassland phytomass with negligible inter-annual variability. The relationships between both ISI and NDSI, and phytomass were however site-specific. The WinSail model indicated that this was mostly due to grassland species composition and background reflectance. Further studies are needed to confirm the usefulness of these indices (e.g. using multispectral specific sensors) for monitoring vegetation structural biophysical variables in other ecosystem types and to test these relationships with aircraft and satellite sensors data. For grassland ecosystems, we conclude that ISI and NDSI hold great promise for non destructively monitoring the temporal variability of grassland phytomass

Vescovo, L.; Wohlfahrt, G.; Balzarolo, M.; Pilloni, S.; Sottocornola, M.; Rodeghiero, M.; Gianelle, D. (2012). New spectral vegetation indices based on the near-infrared shoulder wavelengths for remote detection of grassland phytomass. INTERNATIONAL JOURNAL OF REMOTE SENSING, 33 (7): 2178-2195. doi: 10.1080/01431161.2011.607195 handle: http://hdl.handle.net/10449/20966

New spectral vegetation indices based on the near-infrared shoulder wavelengths for remote detection of grassland phytomass

Vescovo, Loris;Sottocornola, Matteo;Rodeghiero, Mirco;Gianelle, Damiano
2012-01-01

Abstract

This paper examines the possibility of exploiting ground reflectance in the near-infrared (NIR) for monitoring grassland phytomass on a temporal basis. Three new spectral vegetation indices (Infrared Slope Index, ISI; Near Infrared Difference Index, NIDI; and Normalized Difference Structural Index, NDSI), which are based on the reflectance values in the H25 (863-881 nm) and the H18 (745-751 nm) Chris Proba (mode 5) bands, are proposed. Ground measurements of hyperspectral reflectance and phytomass were made at six grassland sites in the Italian and Austrian mountains using a hand-held spectroradiometer. At full canopy cover, strong saturation was observed for many traditional vegetation indices (Normalised Difference Vegetation Index, Modified Simple Ratio, Enhanced Vegetation Index, Enhanced Vegetation Index 2, Renormalised Difference Vegetation Index, Wide Dynamic Range Vegetation Index). Conversely, ISI and NDSI were linearly related to grassland phytomass with negligible inter-annual variability. The relationships between both ISI and NDSI, and phytomass were however site-specific. The WinSail model indicated that this was mostly due to grassland species composition and background reflectance. Further studies are needed to confirm the usefulness of these indices (e.g. using multispectral specific sensors) for monitoring vegetation structural biophysical variables in other ecosystem types and to test these relationships with aircraft and satellite sensors data. For grassland ecosystems, we conclude that ISI and NDSI hold great promise for non destructively monitoring the temporal variability of grassland phytomass
Near-infrared
Vegetation index
Grassland
Canopy reflectance
Settore BIO/07 - ECOLOGIA
2012
Vescovo, L.; Wohlfahrt, G.; Balzarolo, M.; Pilloni, S.; Sottocornola, M.; Rodeghiero, M.; Gianelle, D. (2012). New spectral vegetation indices based on the near-infrared shoulder wavelengths for remote detection of grassland phytomass. INTERNATIONAL JOURNAL OF REMOTE SENSING, 33 (7): 2178-2195. doi: 10.1080/01431161.2011.607195 handle: http://hdl.handle.net/10449/20966
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