Modeling uncertainties in estimation of canopy LAI from hyperspectral remote sensing data – A Bayesian approach-Reference-Cited by-同舟云学术

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Modeling uncertainties in estimation of canopy LAI from hyperspectral remote sensing data – A Bayesian approach

Published:2017-04 Issue: Volume:191 Page:19-29
ISSN:0022-4073
Container-title:Journal of Quantitative Spectroscopy and Radiative Transfer
language:en
Short-container-title:Journal of Quantitative Spectroscopy and Radiative Transfer

Author:

Varvia Petri,Rautiainen Miina,Seppänen Aku

Funder

University of Eastern Finland

Academy of Finland

Publisher

Elsevier BV

Subject

Spectroscopy,Atomic and Molecular Physics, and Optics,Radiation

Reference20 articles.

1. Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data;Gong;IEEE Trans Geosci Remote Sens,2003

2. Sensitivity of narrowband vegetation indices to boreal forest LAI, reflectance seasonality and species composition;Heiskanen;ISPRS J Photogramm Remote Sens,2013

3. Potentials and limits of vegetation indices for LAI and APAR assessment;Baret;Remote Sens Environ,1991

4. Retrieving leaf area index (LAI) using remote sensing: theories, methods and sensors;Zheng;Sensors,2009

5. Experimental evaluation of Sentinel-2 spectral response functions for NDVI time-series continuity;D'Odorico;IEEE Trans Geosci Remote Sens,2013

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