Web of Science: 10 cites, Scopus: 10 cites, Google Scholar: cites
Influence of landscape heterogeneity and spatial resolution in multi-temporal in situ and MODIS NDVI data proxies for seasonal GPP dynamics
Balzarolo, Manuela (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Peñuelas, Josep (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Veroustraete, Frank (University of Antwerp. Department of Bioscience Engineering)

Data: 2019
Resum: The objective of this paper was to evaluate the use of in situ normalized difference vegetation index (NDVI) and Moderate Resolution Imaging Spectroradiometer NDVI (NDVI) time series data as proxies for ecosystem gross primary productivity (GPP) to improve GPP upscaling. We used GPP flux data from 21 global FLUXNET sites across main global biomes (forest, grassland, and cropland) and derived MODIS NDVI at contrasting spatial resolutions (between 0. 5 × 0. 5 km and 3. 5 × 3. 5 km) centered at flux tower location. The goodness of the relationship between NDVI and NDVI varied across biomes, sites, and MODIS spatial resolutions. We found a strong relationship with a low variability across sites and within year variability in deciduous broadleaf forests and a poor correlation in evergreen forests. Best performances were obtained for the highest spatial resolution at 0. 5 × 0. 5 km). Both NDVI and NDVI elicited roughly three weeks later the starting of the growing season compared to GPP data. Our results confirm that to improve the accuracy of upscaling in situ data of site GPP seasonal responses, in situ radiation measurement biomes should use larger field of view to sense an area, or more sensors should be placed in the flux footprint area to allow optimal match with satellite sensor pixel size.
Ajuts: European Commission 702717
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Publicat a: Remote sensing (Basel), Vol. 11, issue 14 (July 2019) , art. 1656, ISSN 2072-4292

DOI: 10.3390/rs11141656

16 p, 2.4 MB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Articles > Articles de recerca
Articles > Articles publicats

 Registre creat el 2020-01-10, darrera modificació el 2021-08-07

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