iForest - Biogeosciences and Forestry


Remote sensing-supported vegetation parameters for regional climate models: a brief review

H Latifi (1)   , B Galos (2)

iForest - Biogeosciences and Forestry, Volume 3, Issue 4, Pages 98-101 (2010)
doi: https://doi.org/10.3832/ifor0543-003
Published: Jul 15, 2010 - Copyright © 2010 SISEF

Review Papers

Collection/Special Issue: NFZ Summer School 2009 - Birmensdorf (Switzerland)
Long-term ecosystem research: understanding the present to shape the future
Guest Editors: Marcus Schaub (WSL, Switzerland)

Land surface plays a key role in a climate system. Thus, the land surface description will become increasingly important for climate modelling by its feedbacks on the climate. Various forms of active/passive remotely sensed data are nowadays being used to provide continuous and up-to-date information on the earth’s surface on both global and regional scales. This information is useful to be included in climate models. This review summarizes how LAI and albedo, two of the most important land surface parameters, could be derived from remote sensing. Whereas the high acquisition frequency, accessibility, and spatial continuality are referred to potential advantages, the scaling is still a drawback which may cause further problems such as incompatibility of different remote sensing data sources for a specific climate model. Moreover, issues like shadow and atmospheric effects are often problematic, especially when optical remote sensing is applied. Here, suggestions for improvement are made and open questions are pointed out.


Regional climate models, Forest and vegetation parameters, Active and passive remote sensing

Authors’ address

H Latifi
Dept. of Remote Sensing and Landscape Information Systems, University of Freiburg, Tennenbacher straße 4, D-79106 Freiburg (Germany)
B Galos
Institute of Environment and Earth Sciences, Faculty of Forestry, University of West Hungary, 9400 Sopron (Hungary)

Corresponding author


Latifi H, Galos B (2010). Remote sensing-supported vegetation parameters for regional climate models: a brief review. iForest 3: 98-101. - doi: 10.3832/ifor0543-003

Academic Editor

Marcus Schaub

Paper history

Received: May 25, 2010
Accepted: May 31, 2010

First online: Jul 15, 2010
Publication Date: Jul 15, 2010
Publication Time: 1.50 months

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