Improving the performance of remote sensing models for capturing intra- and inter-annual variations in daily GPP: An analysis using global FLUXNET tower data

Agricultural and Forest Meteorology

Volumn 214-215, Issue , 2015, Pages 416-429

  Verma, M ^a,b   Friedl, M A ^a   Law, B E ^c   Bonal, D ^d   Kiely, G ^e   Black, T A ^f   Wohlfahrt, G ^g,h   Moors, E J ⁱ   Montagnani, L ^j,k   Marcolla, B ^l   Toscano, P ^m   Varlagin, A ⁿ   Roupsard, O ^o,p   Cescatti, A ^q   Arain, M A ^r   D'Odorico, P ^s  

^a BOSTON UNIVERSITY   (United States)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^c OREGON STATE UNIVERSITY   (United States)

^d UNIVERSITÉ DE LORRAINE   (France)

^e UNIVERSITY COLLEGE CORK   (Ireland)

^f UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^g UNIVERSITY OF INNSBRUCK   (Austria)

^h INSTITUTE FOR RENEWABLE ENERGY   (Italy)

ⁱ WAGENINGEN UNIVERSITY   (Netherlands)

^j FREE UNIVERSITY OF BOZEN BOLZANO   (Italy)

^k Autonomous Province of Bolzano   (Italy)

^l RESEARCH AND INNOVATION CENTRE   (Italy)

^m INSTITUTE OF BIOMETEOROLOGY   (Italy)

ⁿ SEVERTSOV INSTITUTE OF ECOLOGY AND EVOLUTION   (Russian Federation)

^o UMR ECO SOLS   (France)

^p CATIE   (Costa Rica)

^q JOINT RESEARCH CENTRE   (Italy)

^r MCMASTER UNIVERSITY   (Canada)

^s ETH ZURICH   (Switzerland)

more..

Author keywords

FLUXNET; Gross primary productivity; Lagged effects; Modeling; Remote sensing; Seasonal

Indexed keywords

ABIOTIC FACTOR; ANNUAL VARIATION; BIOME; CARBON CYCLE; EFFICIENCY MEASUREMENT; GLOBAL CHANGE; GROSS DOMESTIC PRODUCT; LEAF; PERFORMANCE ASSESSMENT; PRIMARY PRODUCTION; REMOTE SENSING; SOIL MOISTURE; SPATIOTEMPORAL ANALYSIS;

EID: 84942627290     PISSN: 01681923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agrformet.2015.09.005     Document Type: Article

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