Document Detail


Scaling up semi-arid grassland biochemical content from the leaf to the canopy level: challenges and opportunities.
MedLine Citation:
PMID:  22163513     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Remote sensing imagery is being used intensively to estimate the biochemical content of vegetation (e.g., chlorophyll, nitrogen, and lignin) at the leaf level. As a result of our need for vegetation biochemical information and our increasing ability to obtain canopy spectral data, a few techniques have been explored to scale leaf-level biochemical content to the canopy level for forests and crops. However, due to the contribution of non-green materials (i.e., standing dead litter, rock, and bare soil) from canopy spectra in semi-arid grasslands, it is difficult to obtain information about grassland biochemical content from remote sensing data at the canopy level. This paper summarizes available methods used to scale biochemical information from the leaf level to the canopy level and groups these methods into three categories: direct extrapolation, canopy-integrated approach, and inversion of physical models. As for semi-arid heterogeneous grasslands, we conclude that all methods are useful, but none are ideal. It is recommended that future research should explore a systematic upscaling framework which combines spatial pattern analysis, canopy-integrated approach, and modeling methods to retrieve vegetation biochemical content at the canopy level.
Authors:
Yuhong He; Amy Mui
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Review     Date:  2010-12-06
Journal Detail:
Title:  Sensors (Basel, Switzerland)     Volume:  10     ISSN:  1424-8220     ISO Abbreviation:  Sensors (Basel)     Publication Date:  2010  
Date Detail:
Created Date:  2012-02-07     Completed Date:  2012-07-17     Revised Date:  2013-05-29    
Medline Journal Info:
Nlm Unique ID:  101204366     Medline TA:  Sensors (Basel)     Country:  Switzerland    
Other Details:
Languages:  eng     Pagination:  11072-87     Citation Subset:  IM    
Affiliation:
Department of Geography, University of Toronto Mississauga, 3359 Mississauga Road North, Mississauga, Ontario, L5L 1C6, Canada. yuhong.he@utoronto.ca
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MeSH Terms
Descriptor/Qualifier:
Agriculture / methods,  trends*
Biochemistry
Chlorophyll / analysis
Desert Climate
Geographic Information Systems
Humans
Models, Theoretical
Nitrogen / analysis
Plant Leaves / chemistry*,  growth & development*
Remote Sensing Technology* / instrumentation,  methods
Soil / analysis,  chemistry*
Spectrum Analysis / instrumentation,  methods
Trees / chemistry*,  growth & development*,  metabolism
Chemical
Reg. No./Substance:
0/Soil; 1406-65-1/Chlorophyll; 7727-37-9/Nitrogen

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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