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International audience; Temperate forests are under climatic and economic pressures. Public bodies, NGOs and the wood industry are looking for accurate, current and affordable data driven solutions to intensify wood production while maintaining or improving long term sustainability of the production, biodiversity, and carbon sequestration. Free tools and open access data have already been exploited to produce accurate quantitative forest parameters maps suitable for policy and operational purposes. These efforts have relied on different data sources, tools, and methods that are tailored for specific forest types and climatic conditions. We hypothesized we could build on these efforts in order to produce a generic method suitable to perform as well or better in a larger range of settings. In this study we focus on building a generic approach to create forest parameters maps and confirm its performance on a test site: a maritime pine (Pinus pinaster) forest located in south west of France. We investigated and assessed options related with the integration of multiple data sources (SAR L- and C-band, optical indexes and spatial texture indexes from Sentinel-1, Sentinel-2 and ALOS-PALSAR-2), feature extraction, feature selection and machine learning techniques. On our test case, we found that the combination of multiple open access data sources has synergistic benefits on the forest parameters estimates. The sensibility analysis shows that all the data participate to the improvements, that reach up to 13.7% when compared to single source estimates. Accuracy of the estimates is as follows: aboveground biomass (AGB) 28% relative RMSE, basal area (BA) 27%, diameter at breast height (DBH) 20%, age 17%, tree density 24%, and height 13%. Forward feature selection and SVR provided the best estimates. Future work will focus on validating this generic approach in different settings. It may prove beneficial to package the method, the tools, and the integration of open access data in order to make spatially accurate and regularly updated forest structure parameters maps effortlessly available to national bodies and forest organizations.

The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (~ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass.

International audience; Savannahs and woodlands are among the most important biomes in Africa: they cover half of sub-Saharan Africa, provide vital ecosystem services to the rural communities, and play a major part in the carbon budget. Despite their importance and their fragility, they are much less studied than other ecosystems like rainforests. In particular, the distribution and amount of the above-ground woody biomass (AGB) is largely unknown. In this paper, we produce the first continental map of the AGB of African savannahs and woodlands at a resolution of 25 m. The map is built from the 2010 L-band PALSAR mosaic produced by JAXA, along the following steps: a) stratification into wet/dry season areas in order to account for seasonal effects, b) development of a direct model relating the PALSAR backscatter to AGB, with the help of in situ and ancillary data, c) Bayesian inversion of the direct model. A value of AGB and its uncertainty has been assigned to each pixel. This approach allows estimating AGB until 85 Mg•ha − 1 approximately, while dense forests and non-vegetated areas are masked out using the ESA CCI Land Cover dataset. The resulting map is visually compared with existing AGB maps and is validated using a cross-validation approach and a comparison with AGB estimates obtained from LiDAR datasets, leading to an RMSD of 8 to 17 Mg•ha − 1. Finally, carbon stocks for savannahs in Africa and in 50 countries are estimated and compared with estimates by FAO and from AGB maps available over Africa.

International audience; Natural disturbances significantly influence forest ecosystem services and biodiversity. Accurate delineation and early detection of areas affected by wind and insect outbreaks are crucial for guiding management decisions. To this end, past studies relied mostly on passive sensors (e.g., optical), and active sensors (i.e., radar) were rarely used. This study used L-band space-borne synthetic aperture radar (SAR) within a change-detection framework to delineate forested areas affected by wind and insect disturbances. The results showed that changes in backscatter relate to damage caused by wind and insect outbreaks. Overall accuracies of 69-84% and 65-88% were obtained for delineation of areas affected by wind damage and insect outbreaks, respectively, depending on the acquisition date and environmental conditions. Areas susceptible to insect outbreaks or experiencing the initial outbreak phase (green) were detected with lower accuracies (64-74%). It is expected that L-band space-borne SAR data can be applied over larger areas and ecosystem types in the temperate and boreal regions to delineate and detect damaged areas.

International audience; Rice is a major staple food for nearly half of the world's population and has a considerable contribution to the global agricultural economy. While spaceborne Synthetic Aperture Radar (SAR) data have proved to have great potential to provide rice cultivation area, few studies have been performed to provide practical information that meets the user requirements. In rice growing regions where the inter-field crop calendar is not uniform such as in the Mekong Delta in Vietnam, knowledge of the start of season on a field basis, along with the planted rice varieties, is very important for correct field management (timing of irrigation, fertilization, chemical treatment, harvest), and for market assessment of the rice production. The objective of this study is to develop methods using SAR data to retrieve in addition to the rice grown area, the sowing date, and the distinction between long and short cycle varieties. This study makes use of X-band SAR data from COSMO-SkyMed acquired from 19 August to 23 November 2013 covering the Chau Thanh and Thoai Son districts in An Giang province, Viet Nam, characterized by a complex cropping pattern. The SAR data have been analyzed as a function of rice parameters, and the temporal and polarization behaviors of the radar backscatter of different rice varieties have been interpreted physically. New backscatter indicators for the detection of rice paddy area, the estimation of the sowing date, and the mapping of the short cycle and long cycle rice varieties have been developed and assessed. Good accuracy has been found with 92% in rice grown area, 96% on rice long or short cycle, and a root mean square error of 4.3 days in sowing date. The results have been discussed regarding the generality of the methods with respect to the rice cultural practices and the SAR data characteristics.

International audience; In this paper, we aim to assess the impacts of the forest definitions adopted by each African country involved in the global climate change programmes of the United Nations on national carbon emission estimations. To do so, we estimate the proportion of national carbon stocks and tree cover loss that are found in areas considered to be non-forest areas. These non-forest areas are defined with respect to a threshold on the percentage of tree cover adopted by each country. Using percent tree cover and aboveground biomass maps derived from remote sensing data, we quantitatively show that in many countries, a large proportion of carbon stocks are found in non-forest areas, where a large amount of tree cover loss can also occur. We further found that under the REDD+ framework (reduced deforestation, reduced degradation, enhancement and conservation of forest carbon stocks, sustainable management of forests), some partner countries have proposed activities related to only reducing deforestation, even when a large proportion of their carbon stocks are stored outside forests. This situation may represent a limitation of the efficiency of the REDD+ mechanism, and could be avoided if these countries choose a lower tree cover threshold for their definition of forests and/or if they were are engaged in other activities.

Il est aujourd'hui établi que la production agricole mondiale devra augmenter de façon très significative dans les trente prochaines années pour pouvoir répondre à l'accroissement démographique. Dans un contexte contraint de changement climatique, de compétition accrue pour les terres et de pressions environnementales croissantes, des informations exactes et actualisées sur les systèmes agricoles aux échelles globale et régionale sont nécessaires. Les données d'observation de la Terre donnent déjà un aperçu de l'orientation et de l'ampleur des changements en termes de superficie cultivée, d'intensification, et d'impacts sur les milieux naturels et les ressources en eau. L'arrivée des données issues des constellations Sentinel devrait permettre d'améliorer la précision des produits existants et de diversifier le catalogue sur les thèmes de la cartographie de l'occupation/utilisation agricole des sols, la caractérisation des pratiques agricoles et celle du niveau de production. Le TOSCA a soutenu et continue de soutenir des projets qui proposent des développements méthodologiques dans ce sens. • Concernant l'occupation des sols et les pratiques agricoles, les méthodes reposent pour l'essentiel sur des séries temporelles d'images optique ou radar, à résolution hecto- ou décamétrique, mais de plus en plus avec une approche multi-capteur optique-radar et/ou multi-résolution, mais aussi multi-source (données environnementales). En ce sens le CES-OSO (Occupation des Sols) est extrêmement fédérateur et permet de tester et d'adapter la chaine IOTA2 - développée sur la France entière – à différents types de systèmes agricoles (sites JECAM d'agricultures familiale et entrepreneuriale). Avec le radar on assiste au même type de développement sur le riz dans le cadre de l'initiative GEORICE. Ces projets sont accompagnés d'une réflexion sur la nomenclature des produits d'OS/US, notamment par l'introduction d'éléments liés aux pratiques (irrigation, cultures séquentielles, groupe de variétés pour le riz, etc.), sur leur précision et sur leur mise en oeuvre sur de grandes surfaces. Les résultats montrent que les méthodes et données doivent être adaptées aux agrosystèmes en place et qu'il est donc nécessaire d'effectuer des zonages. Des méthodes originales de segmentation des espaces aux échelles régionales et nationales sont développées à cette fin. • A l'échelle locale, il existe des projets montrant le rôle de la télédétection dans le suivi de l'intensification écologique des agrosystèmes, notamment par l'utilisation d'images à très haute résolution spatiale pour la détection, la cartographie et le comptage des arbres en tant que ressources pour la sécurité alimentaire des petits agriculteurs en Amazonie ou comme moyen de lutte contre les ravageurs du mil au Sénégal, ouvrant ainsi la porte à l'utilisation de données d'observation de la Terre en " agronomie des paysages ". • En termes d'estimation des rendements dans les pays du Sud où l'agriculture familiale est majoritaire, le défi est d'imaginer des approches innovantes en télédétection-modélisation des cultures, car les approches classiques -telle que l'assimilation de données- ne peuvent être mises en oeuvre à ces échelles. Un exemple de projet au Niger montre que la combinaison d'indices de végétation et d'indices de stress hydrique reproduit bien la variabilité interannuelle des rendements du mil à l'échelle régionale. Ce résultat appuie l'idée que l'analyse des variations interannuelles et des tendances à moyen terme de la production, couplée à de la modélisation, est une clé de compréhension du rôle du climat et des pratiques dans la sécurité alimentaire en Afrique de l'Ouest, sans pour autant devoir descendre à l'échelle de la parcelle cultivée. (Texte intégral)

International audience

International audience; Interest in the world forests has grown to unprecedented heights, especially with growing awareness of their role in the global carbon cycle. Quantifying carbon in forests is therefore of crucial importance for estimating carbon fluxes at the regional and global scale. Carbon quantities are estimated by inferring wood biomass from forest biomass, and then converting it into carbon by using a value of approximately 0.5 ton of carbon for 1 ton of wood. In order to determine the bio-mass of a forest, significant relationships have therefore been established between radar mean intensity and biophysical variables. However, for mature stands (about 80 t/ha and more) increasing biomass reduces the sensitivity of the backscattering coefficient sigma/biomass relationships. Recent studies have shown that texture could be used instead of the usual intensity-age relationships, even for mature stands up to 140 t/ha, the highest biomass value observed for studied forests (monospecific, even-aged forest, subject to identical silvicultural practices and sampling covering all forest stages from sowing to harvest). The present paper aims at extending these observations to tropical forests which is a large component of the terrestrial carbon pool and the carbon sources generated by deforestation in the tropics. Radar images at P-Band were acquired during the TropiSAR experiment in 2009 over the Paracou experimental site with the SETHI ONERA airborne instrument. Paracou is located in a lowland tropical rain forest near Sinnamary, French Guiana where 15 permanent plots of 6.25 ha each were mapped and regularly measured. Three sets of treatments applied to the 15 forest stands provide biomass values from 260 to 470 T/ha. Plots were selected inside the 15th experimental stands with paying attention to the local topogra-phy. Plots with similar slopes were thus compared. Statistical features were then derived a) from gray level statistics (mean sigma, variance, skewness...) and b) the statistics of pixel pairs (energy, contrast, correlation...) for each plot on the basis of the gray level co-occurrence matrix. It is shown for radar images at P-band and polarisation HV that despite the very homogeneous shape of this regenerating forest, linear relationships between some statistical features and forest biomass can be established which does not saturate even for biomass of more than 350 t/ha. These preliminary results are encouraging and further analysis should be carried out to explore the influence of the different treatments on the retrieval performance.

The BIOMASS mission was retained in January 2009 as one of the three candidates for the next Earth Explorer Core mission to go to phase A. BIOMASS main objective is to provide information on the carbon sinks and sources in the forests globally, which will be of essential value for climate modelling and policy adaptation, e.g. REDD. Up to now, biomass retrieval algorithms have been developed and validated for the range of biomass up to 300 t/ha. The methods are based on combining SAR intensity and SAR Polarimetric interferometry (PolInSAR) which provide respectively estimates of biomass and canopy height. The remaining questions concern the overall performance of the retrieval algorithms in tropical forests characterized by high biomass density (> 300 t/ha) and complex structure. The TropiSAR experiment in French Guyana was proposed to provide feedbacks on the performances of a P-band SAR to measure biomass and canopy height of a tropical forest with higher biomass density. Characterising tropical forests is essential as it represents a large component of the terrestrial carbon pool and the carbon sources. Specifically, TropiSAR was designed to provide measurements of temporal coherence at P-band over tropical forests for time intervals compatible with space-borne missions (typically 20-30 days), to assess performances of methods transforming P-Band SAR intensity and interferometric measurements into forest biomass and forest height. The SAR system is the ONERA airborne system SETHI that flew in French Guyana in August 2009. This paper presents the first results from this analysis. The temporal coherence at P-band over tropical forests is observed to remain high even after 22 days, a time interval period compatible with typical SAR orbit cycle. The vegetation height map estimated from Polarimetric interferometry is shown to be in good agreement with Lidar measured heights and the in-situ measurements in the study area. The PolInSAR derived height captures the main structural features of the studied forests.

We analyse the evolution of the fraction of water surface (FWS), derived by SSM/I between 1988 and 2002 over the Western Siberia Lowland. This whole region exhibits an increase in the amount of FWS that is in agreement with the observed trends of the Ob river discharge and precipitation. However, a similar increasing trend is not found over the most important wetland area of Sibirskie Uvaly Hills located in a region of sporadic permafrost. These observations support the hypothesis that climate warming in discontinuous permafrost environments may lead to a reduction of small lakes and wetland areas. Citation: Grippa, M., N. M. Mognard, T. Le Toan, and S. Biancamaria (2007), Observations of changes in surface water over the western Siberia lowland

International audience; Radiative transfer models have been widely usedto interpret the radar backscatter from forested areas. Most of these models are based on an iterative solution of the radiativetransfer equation, usually solved up to first or second order, thustaking into account single and double scattering. Although thismethod leadsto results agreeing well with copolarized backscattermeasurements, it produces less accurate estimates for hori-zontal–vertical (HV) polarization. This paper presents a radiativetransfer backscatter model that accounts for multiple scatteringby using the discrete ordinate and eigenvalue method applied to alayered medium. Using parameters derived from an architecturaltree model, calculations at C- and L-band are compared withHV data acquired for a maritime pine forest in the southwest of France during the Spaceborne Imaging Radar-C missions. Goodagreement is found at C-band for all values of forest biomass,and reasonable agreement at L-band for high biomass, when thesoil backscatter plays a minor role. For low biomass, the L-bandmodeling is inadequatebecauseof difficultiesin estimatingthe soilbackscatter. Comparison with calculations from a first-order ra-diativetransfermodelshowsthatmultiplescatteringissignificant,especially at C-band.

International audience; The objective of this paper is to investigate the relationships between VHF data and forest biomass using data acquired by the Airborne Imaging Radar CARABAS over two different pine plantation forests in southern France. Data are analyzed using detailed ground truth measurements available on both sites. The backscattering coefficient is strongly correlated to characteristics of the tree trunk. Signal saturation is not observed up to goo m(3)/ha. However, the sensitivity to the volume is high in the range of 0-500 m(3)/ha (e.g., 1 to 1.5 dB for 50 m(3)/ha), whereas it is reduced beyond 500 m(3)/ba (< 0.5 dB for 50 m(3)/ha). The experimental analysis is supported by theoretical modeling using a coherent backscatter model based on the distorted Born approximation coupled with a tree growth model giving a fine and precise description of the trees at both sites. The modeling results show that the trunk is the main scatterer, but that, when the branch dimensions are not insignificant compared to trunk dimension, branch scattering needs to be accounted for. However, since the two species under study are both coniferous, branch dimensions are relatively small compared to trunk dimension. This explains no significant differences observed in the backscatter behavior between both sites, except for mature stands with low stem density. Finally, the effect of topography is investigated both experimentally, using a digital elevation model (DEM), and theoretically with the coherent model. The loss of sensitivity to stem volume due to slope is clearly demonstrated and explained by the decrease of the dihedral trunk-ground interaction as the slope increases.

Methodologies were developed for the provision of standardized geo-referenced information and statistical information to describe the forests and other wooded land in Europe using optical and microwave space borne remotely sensed data. Two forest maps from large areas in Europe were provided using a reflectance mosaic of IRS-WiFS data.

International audience; This paper presents the results of analysis and modeling of the airborne ranging Helsinki University of Technology Scatterometer (HUTSCAT) data obtained over an Austrian pine forest in southern France. The objective is to use high vertical resolution backscatter profiles to validate a model that is subsequently used to determine the scattering sources within a canopy and to understand the wave/tree interaction mechanisms. The backscatter coefficients derived from HUTSCAT measurements at X-band at near-normal incidence and polarizations HH, VV, and VH are analyzed. The tree crown backscatter separated from the ground backscattering shows a sensitivity of about 3 dB between 0 and 200 m3/ha. The estimation of tree height using HUTSCAT profiles gives very good results, with a mean precision of 1 m. The vertical backscatter profiles are compared with the output from the MIT/CESBIO radiative transfer (RT) model coupled with a tree growth architectiral model, AMAP, which recreates tree architecture using botanical bases. An a posteriori modification to the RT model is introduced, taking into account the vertical and horizontal variability of the scattering area in order to correctly estimate the backscatter attenuation. The results show good agreement between both simulated and HUTSCAT-derived vertical backscatter distribution within the canopy. The penetration dept at near normal incidence is studied. Both simulated and experimental penetration depht are compared and appear to be of several meters, varying with the stand's age.