Modelling tree diameter from airborne laser scanning derived variables: A comparison of spatial statistical models-Reference-Cited by-同舟云学术

Modelling tree diameter from airborne laser scanning derived variables: A comparison of spatial statistical models

Published:2010-06 Issue:6 Volume:114 Page:1277-1285
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Salas Christian,Ene Liviu,Gregoire Timothy G.,Næsset Erik,Gobakken Terje

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference71 articles.

1. Information theory and an extension of the maximum likelihood principle;Akaike,1973

2. Statistical inferences in linear mixed-effects models;Bates,2006

3. spgwr: Geographically weighted regression;Bivand;R package version,2009

4. Applied spatial data analysis with R;Bivand,2008

5. A comparison of random coefficient modelling and geographically weighted regression for spatially non-stationary regression problems;Brunsdon;Geographical & Environmental Modelling,1999

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