Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

This study systematically evaluated linear predictive models between vegetation indices (VI) derived from radiometrically corrected airborne imaging spectrometer (HyMap) data and field measurements of biophysical forest stand variables ( n=40). Ratio-based and soil-line-related broadband VI were cal...

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Vydané v:	Remote sensing of environment Ročník 95; číslo 2; s. 177 - 194
Hlavní autori:	Schlerf, Martin, Atzberger, Clement, Hill, Joachim
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY Elsevier Inc 30.03.2005 Elsevier Science
Predmet:	Animal, plant and microbial ecology Applied geophysics Biological and medical sciences Biophysical forest variables Earth sciences Earth, ocean, space Exact sciences and technology Fundamental and applied biological sciences. Psychology General aspects. Techniques Hyperspectral Imaging spectrometry Internal geophysics LAI Multispectral Teledetection and vegetation maps Vegetation indices Imaging spectrometry Multispectral LAI Biophysical forest variables Hyperspectral Vegetation indices Vegetation index vegetation Cross validation Forecast model imagery Procedure soils Forest stand Space remote sensing Landsat Prediction Biophysics Spectrometer forests interpolation channels Regression model techniques Reflectance Leaf area index
ISSN:	0034-4257, 1879-0704
On-line prístup:	Získať plný text
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