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International audience; The emergence of mobile laser scanning (MLS) systems that use simultaneous localization and mapping (SLAM) technology to map their environment opens up new opportunities for characterizing forest structure. The speed and accuracy of data acquisition makes them particularly adapted to operational inventories. MLS also shows great potential for estimating inventory attributes that are difficult to measure in the field, such as wood volume or crown dimensions. Hardwood species represent a significant challenge for wood volume estimation compared to softwoods because a substantial portion of the volume is included in the crown, making them more prone to allometric bias and more complex to model. This study assessed the potential of MLS data to estimate tree structural attributes in a temperate hardwood stand: height, crown dimensions, diameter at breast height (DBH), and merchantable wood volume. Merchantable wood volume estimates were evaluated to the third branching order using the quantitative structural modeling (QSM) approach. Destructive field measurements and terrestrial laser scanning (TLS) data of 26 hardwood trees were used as reference to quantify errors on wood volume and inventory attribute estimations from MLS data. Results reveal that SLAM-based MLS systems provided accurate estimates of tree height (RMSE = 0.42 m (1.78%), R2 = 0.93), crown projected area (RMSE = 3.23 m2 (5.75%), R2 = 0.99), crown volume (RMSE = 71.4 m3 (23.38%), R2 = 0.99), DBH (RMSE = 1.21 cm (3.07%), R2 = 0.99), and merchantable wood volume (RMSE = 0.39 m3 (18.57%), R2 = 0.95), when compared to TLS. They also estimated operational merchantable volume with good accuracy (RMSE = 0.42 m3 (21.82%), R2 = 0.94) compared to destructive measurements. Finally, the merchantable stem volume derived from MLS data was estimated with high accuracy compared to TLS (RMSE = 0.11 m3 (8.32%), R2 = 0.96) and regional stem taper models (RMSE = 0.16 m3 (14.7%), R2 = 0.93). We expect our results would provide a better understanding of the potential of SLAM-based MLS systems to support in-situ forest inventory

International audience; Highlighting spatiotemporal changes occurring within mangrove habitats at the finest possible scale could contribute fundamental knowledge and data for local sustainable management. This study presents the current situation of the Pichavaram mangrove area, a coastal region of Southeast India prone to both cyclones and reduced freshwater inflow. Based on the supervised classification and visual inspection of very high spatial resolution (VHSR) satellite images provided with a pixel size of 85%), which confirmed the potential of classification techniques applied to VHSR images in capturing changes in mangroves on a very fine scale. Our diagnosis reveals variable expansion rates in plantations made by the local authorities. We also report an ongoing mangrove dieback and confirm progressive shoreline erosion along the coastline. Despite a lack of field data, VHSR images allowed for the multiscale diagnosis of the ecosystem situation, thus constituting the first fine-scale assessment of the fragile Pichavaram mangrove area upon which the coastal community is dependent

International audience; Tropical cyclones (TCs) can have profound effects on the dynamics of forest vegetation that need to be better understood. Here, we analysed changes in forest vegetation induced by TCs using the normalized difference vegetation index (NDVI). We used an accurate historical database of TC tracks and intensities, together with the Willoughby cyclone model to reconstruct the 2D surface wind speed structure of TCs and analyse how TCs affect forest vegetation. We used segmented linear models to identify significant breakpoints in the relationship between the reconstructed maximum sustained wind speed (Wmax) and the observed changes in NDVI. We tested the hypothesis that the rate of change in damage caused by TCs to forest and recovery time would increase according to Wmax thresholds as defined in the widely used Saffir–Simpson hurricane wind scale (SSHWS). We showed that the most significant breakpoint was located at 50 m/s. This breakpoint corresponds to the transition between categories 2 and 3 TCs in the SSHWS. Below this breakpoint, damages caused to forest vegetation and the time needed to recover from these damages were negligable. We found a second breakpoint, with a sharp increase in damages for winds >75 m/s. This suggested that extremely intense tropical cyclones, which might be more frequent in the future, can cause extreme damages to forest vegetation. Nevertheless, we found high variation in the observed damages and time needed to recover for a given Wmax. Further studies are needed to integrate other factors that might affect the exposure and resistance to TCs as well as forests’ capacity to recover from these disturbances.