References of "Pontailler, J.-Y"
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See detailEvaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements
Hmimina, G.; Dufrêne, Eric; Pontailler, J.-Y. et al

in Remote Sensing of Environment (2013), (132), 145-158

Vegetation phenology is the st udy of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote ... [more ▼]

Vegetation phenology is the st udy of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote sensing of vegetation phenology, phenologicalmetrics are derived fromtime series of optical data. For that purpose, considerable effort has been specifically focused on developing noise reduction and cloud-contaminated data removal techniques to improve the quality of remotely-sensed time series. Comparative studies between time series composed of satellite data acquired under clear and cloudy conditions and fromradiometric data obtainedwith high accuracy fromground-basedmeasurements constitute a direct and effective way to assess the operational use and limitations of remote sensing for predicting the main plant phenological events. In the present paper, we sought to explicitly evaluate the potential use of MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing data for monitoring the seasonal dynamics of different types of vegetation cover that are representative of the major terrestrial biomes, including temperate deciduous forests, evergreen forests, African savannah, and crops. After cloud screening and filtering, we compared the temporal patterns and phenological metrics derived from in situ NDVI time series and from MODIS daily and 16-composite products. We also evaluated the effects of residual noise and the in uence of data gaps in MODIS NDVI time series on the identification of the most relevant metrics for vegetation phenology monitoring. The results show that the in exion points of a model fitted to a MODIS NDVI time series allow accurate estimates of the onset of greenness in the spring and the onset of yellowing in the autumn in deciduous forests (RMSE<oneweek). Phenologicalmetrics identical to those providedwith theMODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately twoweeks or more during the autumn phenological transitions. In the evergreen forests, in situ NDVI time series describe the phenology with high fidelity despite small temporal changes in the canopy foliage. However, MODIS is unable to provide consistent phenological patterns. In crops and savannah, MODIS NDVI time series reproduce the general temporal patterns of phenology, but significant discrepancies appear between MODIS and ground-based NDVI time series during very localized periods of time depending on the weather conditions and spatial heterogeneity within the MODIS pixel. In the rainforest, the temporal pattern exhibited by a MODIS 16-day composite NDVI time series ismore likely due to a pattern of noise in the NDVI data structure according to both rainy and dry seasons rather than to phenological changes. More investigations are needed, but in all cases, this result leads us to conclude that MODIS time series in tropical rainforests should be interpreted with great caution. [less ▲]

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See detailGround-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes
Soudani, K.; Hmimina, K.; Delpierre, N. et al

in Remote Sensing of Environment (2012), 123

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See detailExceptional Carbon Uptake In European Forests During The Warm Spring Of 2007: A Data-Model Analysis
Delpierre, N.; Soudani, K.; Kostner, B. et al

in Global Change Biology (2009), 15(6), 1455-1474

Temperate and boreal forests undergo drastic functional changes in the springtime, shifting within a few weeks from net carbon (C) sources to net C sinks. Most of these changes are mediated by temperature ... [more ▼]

Temperate and boreal forests undergo drastic functional changes in the springtime, shifting within a few weeks from net carbon (C) sources to net C sinks. Most of these changes are mediated by temperature. The autumn 2006-winter 2007 record warm period was followed by an exceptionally warm spring in Europe, making spring 2007 a good candidate for advances in the onset of the photosynthetically active period. An analysis of a decade of eddy covariance data from six European forests stands, which encompass a wide range of functional types (broadleaf evergreen, broadleaf deciduous, needleleaf evergreen) and a wide latitudinal band (from 44 degrees to 62 degrees N), revealed exceptional fluxes during spring 2007. Gross primary productivity (GPP) of spring 2007 was the maximum recorded in the decade examined for all sites but a Mediterranean evergreen forest (with a +40 to +130 gC m(-2) anomaly compared with the decadal mean over the January-May period). Total ecosystem respiration (TER) was also promoted during spring 2007, though less anomalous than GPP (with a +17 to +93 gC m(-2) anomaly over 5 months), leading to higher net uptake than the long-term mean at all sites (+12 to +79 gC m(-2) anomaly over 5 months). A correlative analysis relating springtime C fluxes to simple phenological indices suggested spring C uptake and temperatures to be related. The CASTANEA process-based model was used to disentangle the seasonality of climatic drivers (incoming radiation, air and soil temperatures) and biological drivers (canopy dynamics, thermal acclimation of photosynthesis to low temperatures) on spring C fluxes along the latitudinal gradient. A sensitivity analysis of model simulations evidenced the roles of (i) an exceptional early budburst combined with elevated air temperature in deciduous sites, and (ii) an early relief of winter thermal acclimation in coniferous sites for the promotion of 2007 spring assimilation. [less ▲]

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