Andrew Skidmore

Prof. Andrew Skidmore

Faculty for Geo-Information Science and Earth Observation (ITC), University of Twente, 7500AA Enschede, The Netherlands
orcid

Research Focus & Metrics

Academic Career Length

40Years (1987-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 May 2012 in Ecography
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CDCarsten F. Dormann
Carsten F. Dormann
JEJane Elith
Jane Elith
SBSven Bacher
Sven Bacher
CBCarsten M Buchmann
Carsten M Buchmann
GCGudrun Carl
Gudrun Carl
Sven LautenbachSven Lautenbach
Sven Lautenbach

4 September 2013 in Ecography
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BNBabak Naimi
Babak Naimi
NHNicholas Hamm
Nicholas Hamm
TGThomas Groen
Thomas Groen
ASAndrew Skidmore
Andrew Skidmore
ATAlbertus G. Toxopeus
Albertus G. Toxopeus

1 February 2006 in Remote Sensing of Environment
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Journal Article
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PBPieter S. A. Beck
Pieter S. A. Beck
Clement ATZBERGERClement ATZBERGER
Clement ATZBERGER
KHKjell Arild Høgda
Kjell Arild Høgda
BJBernt Johansen
Bernt Johansen
ASAndrew Skidmore
Andrew Skidmore

1 October 2004 in International Journal of Remote Sensing
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Journal Article
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Onisimo MutangaOnisimo Mutanga
Onisimo Mutanga
ASAndrew Skidmore
Andrew Skidmore
Remotely sensed vegetation indices such as NDVI, computed using the red and near infrared bands have been used to estimate pasture biomass. These indices are of limited value since they saturate in dense vegetation. In this study, we evaluated the potential of narrow band vegetation indices for characterizing the biomass of Cenchrus ciliaris grass measured at high canopy density. Three indices were tested: Modified Normalized Difference Vegetation Index (MNDVI), Simple Ratio (SR) and Transformed Vegetation Index (TVI) involving all possible two band combinations between 350 nm and 2500 nm. In addition, we evaluated the potential of the red edge position in estimating biomass at full canopy cover. Results indicated that the standard NDVI involving a strong chlorophyll absorption band in the red region and a near infrared band performed poorly in estimating biomass (R 2=0.26). The MNDVIs involving a combination of narrow bands in the shorter wavelengths of the red edge (700–750 nm) and longer wavelengths of the red edge (750–780 nm), yielded higher correlations with biomass (mean R 2=0.77 for the highest 20 narrow band NDVIs). When the three vegetation indices were compared, SR yielded the highest correlation coefficients with biomass as compared to narrow band NDVI and TVI (average R 2=0.80, 0.77 and 0.77 for the first 20 ranked SR, NDVI and TVI respectively). The red edge position yielded comparable results to the narrow band vegetation indices involving the red edge bands. These results indicate that at high canopy density, pasture biomass may be more accurately estimated by vegetation indices based on wavelengths located in the red edge than the standard NDVI.

1 February 2003 in Ecology
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FLFrank Van Langevelde
Frank Van Langevelde
CVClaudius A. D. M. Van De Vijver
Claudius A. D. M. Van De Vijver
LKLalit Kumar
Lalit Kumar
JKJohan Van De Koppel
Johan Van De Koppel
NRNico De Ridder
Nico De Ridder
MRMax Rietkerk
Max Rietkerk

1 March 2009 in Forest Ecology and Management
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Journal Article
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TBT.M. Basuki
T.M. Basuki
PLP.E. van Laake
P.E. van Laake
ASAndrew Skidmore
Andrew Skidmore
YHY.A. Hussin
Y.A. Hussin