<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hmimina, G</style></author><author><style face="normal" font="default" size="100%">Dufrêne, E</style></author><author><style face="normal" font="default" size="100%">Pontailler, J.-Y.</style></author><author><style face="normal" font="default" size="100%">Delpierre, N</style></author><author><style face="normal" font="default" size="100%">Aubinet, M</style></author><author><style face="normal" font="default" size="100%">Caquet, B</style></author><author><style face="normal" font="default" size="100%">de Grandcourt, A</style></author><author><style face="normal" font="default" size="100%">Burban, B</style></author><author><style face="normal" font="default" size="100%">Flechard, C</style></author><author><style face="normal" font="default" size="100%">GRANIER, a</style></author><author><style face="normal" font="default" size="100%">Gross, P</style></author><author><style face="normal" font="default" size="100%">Heinesch, B</style></author><author><style face="normal" font="default" size="100%">Longdoz, B</style></author><author><style face="normal" font="default" size="100%">Moureaux, C</style></author><author><style face="normal" font="default" size="100%">OURCIVAL, J.-M.</style></author><author><style face="normal" font="default" size="100%">Rambal, S</style></author><author><style face="normal" font="default" size="100%">Saint André, L</style></author><author><style face="normal" font="default" size="100%">Soudani, K</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing of Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Crops</style></keyword><keyword><style  face="normal" font="default" size="100%">Deciduous forests</style></keyword><keyword><style  face="normal" font="default" size="100%">evergreen forests</style></keyword><keyword><style  face="normal" font="default" size="100%">Ground-based NDVI</style></keyword><keyword><style  face="normal" font="default" size="100%">MODIS</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><volume><style face="normal" font="default" size="100%">132</style></volume><pages><style face="normal" font="default" size="100%">145-158</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Abstract Vegetation phenology is the study 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, phenological metrics are derived from time 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 from radiometric data obtained with high accuracy from ground-based measurements 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 influence 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 inflexion 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 ≤ one week). Phenological metrics identical to those provided with the MODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately two weeks 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 is more 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.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Soudani, K</style></author><author><style face="normal" font="default" size="100%">Hmimina, G</style></author><author><style face="normal" font="default" size="100%">Delpierre, N</style></author><author><style face="normal" font="default" size="100%">Pontailler, J.-Y.</style></author><author><style face="normal" font="default" size="100%">Aubinet, M</style></author><author><style face="normal" font="default" size="100%">Bonal, D</style></author><author><style face="normal" font="default" size="100%">Caquet, B</style></author><author><style face="normal" font="default" size="100%">de Grandcourt, A</style></author><author><style face="normal" font="default" size="100%">Burban, B</style></author><author><style face="normal" font="default" size="100%">Flechard, C</style></author><author><style face="normal" font="default" size="100%">Guyon, D</style></author><author><style face="normal" font="default" size="100%">GRANIER, a</style></author><author><style face="normal" font="default" size="100%">Gross, P</style></author><author><style face="normal" font="default" size="100%">Heinesh, B</style></author><author><style face="normal" font="default" size="100%">Longdoz, B</style></author><author><style face="normal" font="default" size="100%">Loustau, D</style></author><author><style face="normal" font="default" size="100%">Moureaux, C</style></author><author><style face="normal" font="default" size="100%">OURCIVAL, J.-M.</style></author><author><style face="normal" font="default" size="100%">Rambal, S</style></author><author><style face="normal" font="default" size="100%">Saint André, L</style></author><author><style face="normal" font="default" size="100%">Dufrêne, E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Ground-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing of Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Crops</style></keyword><keyword><style  face="normal" font="default" size="100%">Evergreen and deciduous forests</style></keyword><keyword><style  face="normal" font="default" size="100%">Ground-based NDVI</style></keyword><keyword><style  face="normal" font="default" size="100%">Herbaceous savanna</style></keyword><keyword><style  face="normal" font="default" size="100%">NDVI time-series</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenology</style></keyword><keyword><style  face="normal" font="default" size="100%">Tropical rain forest</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier Inc.</style></publisher><volume><style face="normal" font="default" size="100%">123</style></volume><pages><style face="normal" font="default" size="100%">234-245</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Plant phenology characterises the seasonal cyclicity of biological events such as budburst, ﬂowering, fructiﬁ- cation, leaf senescence and leaf fall. These biological events are genetically pre-determined but also strongly modulated by climatic conditions, particularly temperature, daylength and water availability. Therefore, the timing of these events is considered as a good indicator of climate change impacts and as a key parameter for understanding and modelling vegetation–climate interactions. In situ observations, empirical or bioclimatic models and remotely sensed time-series data constitute the three possible ways for monitoring the timing of plant phenological events. Remote sensing has the advantage of being the only way of surface sampling at high temporal frequency and, in the case of satellite-based remote sensing, over large regions. Nevertheless, exogenous factors, particularly atmospheric conditions, lead to some uncertainties on the seasonal course of surface reﬂectance and cause bias in the identiﬁcation of vegetation phenological events. Since 2005, a network of forest and herbaceous sites has been equipped with laboratory made NDVI sensors to monitor the temporal dynamics of canopy structure and phenology at an intra-daily time step. In this study, we present recent results obtained in several contrasting biomes in France, French Guiana, Belgium and Congo. These sites represent a gradient of vegetation ecosystems: the main evergreen and deciduous forest ecosystems in temperate climate region, an evergreen tropical rain forest in French Guiana, an herbaceous savanna ecosystem in Congo, and a succession of three annual crops in Belgium. In this paper, (1) we provide an accurate description of the seasonal dynamics of vegetation cover in these different ecosystems (2) we identify the most relevant remotely sensed markers from NDVI time-series for determining the dates of the main phenological events that characterize these ecosystems and (3) we discuss the relationships between temporal canopy dynamics and climate factors. In addition to its importance for phenological studies, this ground-based Network of NDVI measurement provides data needed for the calibration and direct validation of satellite observations and products.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roupsard, O</style></author><author><style face="normal" font="default" size="100%">Gross, P</style></author><author><style face="normal" font="default" size="100%">Dreyer, E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Limitation of photosynthetic activity by CO2 availability in the chloroplasts of oak leaves from different species and during drought</style></title><secondary-title><style face="normal" font="default" size="100%">Ann. For. Sci.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">chlorophyll fluorescence</style></keyword><keyword><style  face="normal" font="default" size="100%">chloroplasts</style></keyword><keyword><style  face="normal" font="default" size="100%">CO2 diffusion</style></keyword><keyword><style  face="normal" font="default" size="100%">Drought</style></keyword><keyword><style  face="normal" font="default" size="100%">mesophyll conductance</style></keyword><keyword><style  face="normal" font="default" size="100%">oaks</style></keyword><keyword><style  face="normal" font="default" size="100%">Stomatal conductance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><volume><style face="normal" font="default" size="100%">53</style></volume><pages><style face="normal" font="default" size="100%">243-254</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">It has recently been suggested that the low photosynthesis rates in tree species as compared to highly productive crops is at least partly due to resistances opposing the CO 2 fluxes in the mesophyll of tree leaves. To validate this assertion, values of CO2 mole fractions in the chloroplasts of leaves from Quercus petraea, Q robur, Q ilex and Populus sp were estimated on the basis of the analysis of the partitioning of light driven electron flow between fractions used for the carboxylation or the oxygenation of RuBP by Rubisco. The procedure used included: i) a measure of total light driven electron flows derived from the chlorophyll a fluorescence ratio ΔF/Fm', which is proportional to the photochemical efficiency of PS II, multiplied by incident irradiance and a calibration coefficient; ii) an estimation of the electron flux devoted to carboxylation obtained from net CO2 assimilation and respiration rate measurement, and using the known electron requirements (four electrons for CO2 or O2 fixation); iii) the derivation of the CO2 mole fraction in the chloroplasts from the specificity factor of Rubisco, and the ratio of carboxylation/oxygenation of RuBP. Results showed that in the absence of drought stress, the mole fraction of CO2 in the chloroplasts (35-45% of the atmospheric one) was much lower than the calculated substomatal one (60-70% of the atmospheric) in all species. Moreover, lowest values were recorded in the species with lowest assimilation rates, suggesting that the differences in the net CO 2 assimilation rate between species are linked to the CO2 availability in the chloroplasts. Finally, the CO2 availability decreased with increasing drought in the soil, stressing the importance of reduced influx of CO2 as an important factor for drought-induced declines of photosynthesis. These results are discussed with respect to the occurrence of significant resistances in the leaf mesophyll, in addition to the stomatal resistances.</style></abstract></record></records></xml>