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16 p, 4.3 MB Monitoring spatial and temporal variabilities of gross primary production using MAIAC MODIS data / Fernández Martínez, Marcos (University of Antwerp. Centre of Excellence PLECO) ; Yu, Rong (University of Nebraska-Lincoln. Center for Advanced Land Management Information Technologies) ; Gamon, John (University of Alberta. Earth & Atmospheric Sciences, and Biological Sciences) ; Hmimina, Gabriel (University of Nebraska-Lincoln. Center for Advanced Land Management Information Technologies) ; Filella Cubells, Iolanda (Centre de Recerca Ecològica i d'Aplicacions Forestals) ; Balzarolo, Manuela (Centre de Recerca Ecològica i d'Aplicacions Forestals) ; Stocker, Benjamin (Centre de Recerca Ecològica i d'Aplicacions Forestals) ; Peñuelas, Josep (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Remotely sensed vegetation indices (RSVIs) can be used to efficiently estimate terrestrial primary productivity across space and time. Terrestrial productivity, however, has many facets (e. g. , spatial and temporal variability, including seasonality, interannual variability, and trends), and different vegetation indices may not be equally good at predicting them. [...]
2019 - 10.3390/rs11070874
Remote Sensing, Vol. 11, Issue 7 (April 2019) , art. 874  

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