TY - JOUR
T1 - Matching the phenology of Net Ecosystem Exchange and vegetation indices estimated with MODIS and FLUXNET in-situ observations
AU - Balzarolo, M.
AU - Vicca, S.
AU - Nguy-Robertson, A. L.
AU - Bonal, D.
AU - Elbers, J. A.
AU - Fu, Y. H.
AU - Grünwald, T.
AU - Horemans, J. A.
AU - Papale, D.
AU - Peñuelas, J.
AU - Suyker, A.
AU - Veroustraete, F.
N1 - Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - Shifts in ecosystem phenology play an important role in the definition of inter-annual variability of net ecosystem carbon uptake. A good estimate at the global scale of ecosystem phenology, mainly that of photosynthesis or gross primary productivity (GPP), may be provided by vegetation indices derived from MODIS satellite image data.However, the relationship between the start date of a growing (or greening) season (SGS) when derived from different vegetation indices (VI's), and the starting day of carbon uptake is not well elucidated. Additionally, the validation of existing phenology data with in-situ measurements is largely missing. We have investigated the possibility to use different VI's to predict the starting day of the growing season for 28 FLUXNET sites as well as MODIS data. This analysis included main plant functional types (PFT's).Of all VI's taken into account in this paper, the NDVI (Normalized Difference Vegetation Index) shows the highest correlation coefficient for the relationship between the starting day of the growing season as observed with MODIS and in-situ observations. However, MODIS observations elicit a 20-21 days earlier SGS date compared to in-situ observations. The prediction for the NEE start of the growing season diverges when using different VI's, and seems to depend on the amplitude for carbon and VI and on PFT. The optimal VI for estimation of a SGS date was PFT-specific - for example the WRDVI for cropland, but the MODIS NDVI performed best when applied as an estimator for Net Ecosystem Exchange and when considering all PFT's pooled.
AB - Shifts in ecosystem phenology play an important role in the definition of inter-annual variability of net ecosystem carbon uptake. A good estimate at the global scale of ecosystem phenology, mainly that of photosynthesis or gross primary productivity (GPP), may be provided by vegetation indices derived from MODIS satellite image data.However, the relationship between the start date of a growing (or greening) season (SGS) when derived from different vegetation indices (VI's), and the starting day of carbon uptake is not well elucidated. Additionally, the validation of existing phenology data with in-situ measurements is largely missing. We have investigated the possibility to use different VI's to predict the starting day of the growing season for 28 FLUXNET sites as well as MODIS data. This analysis included main plant functional types (PFT's).Of all VI's taken into account in this paper, the NDVI (Normalized Difference Vegetation Index) shows the highest correlation coefficient for the relationship between the starting day of the growing season as observed with MODIS and in-situ observations. However, MODIS observations elicit a 20-21 days earlier SGS date compared to in-situ observations. The prediction for the NEE start of the growing season diverges when using different VI's, and seems to depend on the amplitude for carbon and VI and on PFT. The optimal VI for estimation of a SGS date was PFT-specific - for example the WRDVI for cropland, but the MODIS NDVI performed best when applied as an estimator for Net Ecosystem Exchange and when considering all PFT's pooled.
KW - Net Ecosystem Exchange (NEE)
KW - Phenology
KW - Plant functional types (PFT's)
KW - Start of growing season (SGS)
KW - Start of net carbon uptake (SGS)
KW - Vegetation indices (VI's)
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U2 - 10.1016/j.rse.2015.12.017
DO - 10.1016/j.rse.2015.12.017
M3 - Article
AN - SCOPUS:84952042862
SN - 0034-4257
VL - 174
SP - 290
EP - 300
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
ER -