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[EN] Land surface phenology from time series of satellite data are expected to contribute to improve the represen-tation of vegetation phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from GEOCLIM-LAI, a global climatology of leaf area index (LAI) derived from 1-km SPOT VEGETATION time series for 1999-2010. The calibration with ground measurements showed that the start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The satellite-derived phenology was spatially consistent with the global distributions of climatic drivers and biome land cover. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests in Europe, cherry in Asia and lilac shrubs in North America showed an overall root mean square error lower than 19 days for the start, end and length of season, and good agreement between the latitudinal gradients of VEGETATION LAI phenology and ground data, [ES] La teledetección debe contribuir a mejorar la representación de la fenología en los modelos climáticos. En este estudio se ha caracterizado la fenología típica de la vegetación a escala global mediante GEOCLIM-LAI, una climatología del índice de área foliar (LAI) calculada a partir de series temporales en el periodo 1999-2010 de datos SPOT VEGETATION a 1-km de resolución espacial. A partir de la calibración con observaciones in situ, el inicio y fin de la estación de crecimiento se han definido como la fecha para la cual el LAI alcanza, respectivamente, el 30% y 40% de la amplitud de su ciclo anual. Los patrones espaciales de la fenología de satélite muestran una gran consistencia con la distribución espacial de cubiertas vegetales y factores climáticos. La comparación con medidas in situ para las fe-nofases correspondientes al inicio, fin y duración de la estación de crecimiento de abedul común en Europa, cerezo en Asia y lilo en Norte América muestra errores medios menores de 19 días, y un gran acuerdo en el gradiente latitudinal de la fenología observada in situ y estimada a partir de series temporales LAI VEGETATION., Este trabajo ha sido financiado en parte por el programa Europeo de observación Copernicus Global Land, y los proyectos FP7 geoland2 (218795), GIOBIO (32-566), LONGLOVE (32-594), CGL2013-48074-P, SGR 2014-274 y IMBALANCE-P (ERC-2013-SyG-610028). A. Verger fue beneficiario de un contrato Juan de la Cierva del Ministerio de Ciencia e Innovación, Gobierno de España.

This contribution aims at analysing the distribution of biophysical variables and sun-induced chlorophyll fluorescence (F) retrieved from high-resolution hyperspectral images acquired over a mixed forest ecosystem. The airborne data were acquired on June 16th, 2013 over the Hardt forest, a mid-latitude plain forest located in Alsace (France), using the imaging spectrometer HyPlant, developed by Forschungszentrum Jülich in collaboration with SPECIM Spectral Imaging Ltd. HyPlant is composed of a hyperspectral sensor covering the visible, near-infrared and shortwave infrared part of the spectrum, and of a narrowband sensor specifically designed for F retrieval, that covers the 670-780 nm spectral region with a sub-nanometer resolution. The images were elaborated in order to obtain three products: (i) a thematic map of the distribution of the main species over the study area (i.e., hornbeam (Carpinus betulus L.), oak (Quercus robur L., Quercus petraea (Matt.) Liebl.), maple (Acer campestre L.), linden (Tilia L.), pine (Pinus L.) and larch (Larix decidua Mill.)), through a machine-learning classification method; (ii) maps of biophysical variables (e.g., chlorophyll, LAI maps) through inversion of radiative transfer models; (iii) a map of F at the oxygen absorption bands through the innovative Spectral Fitting Method (SFM). A field campaign was conducted concurrently with the overflight to collect ground measurements to validate all the products: (i) forest species composition and crown condition were assessed by forest experts in 22 sampling units of 20_20 m; (ii) pigment concentration and LAI were determined in the same sites by means of laboratory extraction and hemispherical photography acquisition; (iii) top-of-canopy red and far-red F was measured over the main forest species using high-resolution spectroradiometers manually operated from a mobile hydraulic platform. The validated products obtained from HyPlant airborne data were used to compare and analyse the spatial variability of F and biophysical variables in relation to species composition and forest structure. Results showed that different species (mapped with an overall accuracy of 75%) are characterised by different F values: pine and linden are characterised by the lowest fluorescence emission, while the other broadleaves show higher values. The F emission intensity analysed in relation to pigment content and biomass pointed out that these relationships are not unique. In highly dense and green canopies, where the biophysical variables tend to saturate, F shows an inter-species variability, highlighting the potential of using F maps in combination with reflectance-derived biophysical products in order to improve our understanding of complex ecosystem's dynamics Hyperspectral; Sun-induced fluorescence; Plant traits; Classification; Tree species

Initiated in 1984, the Committee Earth Observing Satellites' Working Group on Calibration and Validation (CEOS WGCV) pursues activities to coordinate, standardize and advance calibration and validation of civilian satellites and then- data. One subgroup of CEOS WGCV, Land Product Validation (LPV), was established in 2000 to define standard validation guidelines and protocols and to foster data and information exchange relevant to the validation of land products. Since then, a number of leaf area index (LAI) products have become available to the science com munity at both global and regional extents. Having multiple global LAI products and multiple, disparate validation activities related to these products presents the opportunity to realize efficiency through international collaboration. So the LPV subgroup established an international LAI Intel-comparison validation activity. This paper describes the main components of this international validation effort. The paper documents the current participants, then- ground LAI measurements and scaling techniques, and the metadata and infrastructure established to share data. The paper concludes by describing plans for sharing both field data and high-resolution LAI products from each site. Many considerations of this global LAI intercomparison can apply to other products, and this paper presents a framework for such collaboration. © 2006 IEEE.

The value of satellite derived land products for science applications and research is dependent upon the known accuracy of the data. CEOS (Committee on Earth Observation Satellites), the space arm of the Group on Earth Observations (GEO), plays a key role in coordinating the land product validation process. The Land Product Validation (LPV) sub-group of the CEOS Working Group on Calibration and Validation (WGCV) aims to address the challenges associated with the validation of global land products. This paper provides an overview of LPV sub-group focus area activities, which cover seven terrestrial Essential Climate Variables (ECVs). The contribution will enhance coordination of the scientific needs of the Earth system communities with global LPV activities.

International audience

Many vegetation properties are related to features of reflectance spectra in the region 400 nm - 2500 nm. and to emittance in region 8 mm - 14 mm Detailed observations of spectral reflectance reveal subtle features related to biochemical components of leaves such as chlorophyll and water. Exchange of energy between the biosphere and the atmosphere is an important mechanism determining the response of vegetation to climate variability. This requires measurements of the component temperature of foliage and soil. The latter are closely related to the angular variation in thermal infrared emittance. The architecture of vegetation canopies determines complex changes of observed reflectance and emittance spectra with view and illumination angle. Quantitative analysis of reflectance and emittance spectra requires, therefore, an accurate characterization of the anisotropy of radiance. This can be achieved with nearly - simultaneous observations at different view angles. The Surface Processes and Ecosystem Changes Through Response Analysis (SPECTRA) Mission has been conceived to perform these observations at high spatial resolution by taking advantage of the spacecraft agility. Scientific preparations are pursued along two avenues: a) the nature of the expected data and candidate algorithms are evaluated by generating and using synthetic hyper - spectral multi - angular/radiometric data; b) algorithms are evaluated with actual hyper - spectral data collected with a variety of airborne systems and concurrent ground measurements; Campaigns have been performed using radiometric observations provided by ATSR, AATSR, AirMISR, CHRIS - PROBA and a variety of airborne hyperspectral systems. The paper will cover highlights of these studies.