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International audienceAim: The size structure of a forest canopy is an important descriptor of the forest environment that may yield information on forest biomass and ecology. However, its variability at regional scales is poorly described or understood because of the still prohibitive cost of very high-resolution imagery as well as the lack of an appropriate methodology. We here employ a novel approach to describe and map the canopy structure of tropical forests. Location Amazonia. Methods: We apply Fourier transform textural ordination (FOTO) techniques to subsamples of very high-resolution satellite imagery freely available through virtual globe software (e.g. Google Earth®) to determine two key structural variables: apparent mean crown size and heterogeneity in crown size. A similar approach is used with artificial forest canopy images generated by the light interaction model (discrete anisotropic radiative transfer, DART) using three-dimensional stand models. The effects of sun and viewing angles are explored on both model and real data. Results: It is shown that in the case of canopies dominated by a modal size class our approach can predict mean canopy size to an accuracy of 5%. In Amazonia, we could evidence a clear macrostructure, despite considerable local variability. Apparent crown size indeed consistently increases from about 14 m in wet north-west Amazonia to more than 17 m for areas of intermediate dry season length (1–3 months) in south and east Amazonia, before decreasing again towards the ecotone with the Cerrado savanna biome. This general trend reflects the known variation of other forest physiognomic properties (height) reported for South America and Africa. Some regions show significantly greater canopy heterogeneity, a feature that may be related to substratum, perturbation rate and/or forest turnover rate. Main conclusions: Our results demonstrate the feasibility and interest of large-scale assessment of rain forest canopy structur

International audienceAlthough rising global sea levels will affect the shape of coastlines over the coming decades(1,2), the most severe and catastrophic shoreline changes occur as a consequence of local and regional-scale processes. Changes in sediment supply(3) and deltaic subsidence(4,5), both natural or anthropogenic, and the occurrences of tropical cyclones(4,5) and tsunamis(6) have been shown to be the leading controls on coastal erosion. Here, we use satellite images of South American mangrove-colonized mud banks collected over the past twenty years to reconstruct changes in the extent of the shoreline between the Amazon and Orinoco rivers. The observed timing of the redistribution of sediment and migration of the mud banks along the 1,500km muddy coast suggests the dominant control of ocean forcing by the 18.6 year nodal tidal cycle(7). Other factors affecting sea level such as global warming or El Nino and La Nina events show only secondary influences on the recorded changes. In the coming decade, the 18.6 year cycle will result in an increase of mean high water levels of 6 cm along the coast of French Guiana, which will lead to a 90 m shoreline retreat

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Lucas, R. M., Mitchell, A. L., Rosenqvist, A., Christophe, P., Melius, A., Ticehurst, C. (2007). The potential of L-band SAR for quantifying mangrove characteristics and change: case studies from the tropics. Aquatic Conservation-Marine and Freshwater Ecosystems, 17, 245-264. Sponsorship: Environmental Research Institute of the Supervising Scientist (ERISS)1. The Japan Aerospace Exploration Agency's (JAXA) Advanced Land Observing Satellite (ALOS) L-band Phased Array Synthetic Aperture Radar (PALSAR), launched successfully in January 2006, will provide new data sets for coastal ecosystems mapping and change monitoring at local to global scales. 2. To evaluate L-band capability for mangrove applications, data acquired by the NASA airborne SAR (AIRSAR) and Japanese Earth Resources Satellite (JERS-1 SAR) over sites in Australia, French Guiana and Malaysia were used to demonstrate benefits for mapping extent and zones, retrieving biomass and structural attributes (e.g. height), and detecting change. 3. The research indicates that mapping is most effective where mangroves border non-forested areas and where differences in structure, as a function of species, growth stage and biomass distributions, occur between zones. 4. Using L-band SAR, biomass can be retrieved up to ?100?140 Mg ha?1, although retrieval is complicated by a noticeable decrease in L-band backscattering coefficient within higher (?>200 Mg ha?1) biomass stands, particularly those with extensive prop root systems. 5. Change detection through multi-temporal comparison of data proved useful for mapping deforestation/regeneration and mangrove dynamics associated with changing patterns of sedimentation. 6. The research highlights the likely benefits and limitations of using ALOS PALSAR data and supports JAXA's Kyoto & Carbon (K&C) Initiative in promoting the use of these data for regional mangrove assessment.Peer reviewe

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