Auteurs, date et publication :
Auteurs Wenyu Yang , Sergio Vitale , Hossein Aghababaei , Giampaolo Ferraioli , Vito Pascazzio , Gilda Schirinzi
Date : 2025
Catégorie(s)
#CIRAD #FORET ParacouRésumé
The characterization of forests is crucial for understanding the carbon cycle. P-band Synthetic Aperture Radar (SAR) is a particularly effective means of identifying key descriptors of tropical or temperate forests, thanks to its ability to penetrate dense volumetric environments and measure their biomass. In this context, ESA is launching the BIOMASS mission, which features the first P-band spaceborne SAR sensor dedicated to the study of forests. SAR tomography is a powerful tool for determining the 3D structure of forests based on their electromagnetic response. Existing techniques often separate canopy and ground reflections using SAR tomography and polarimetric diversity as well as advanced processing methods. This thesis demonstrates that comparable performance, with improved stability, can be achieved using single-polarization data and parametric tomographic focusing. This thesis proposes a simple and sufficient modeling of forests using a low-dimensional representation. The vertical reflectivity density of tropical and temperate forests is modeled at P-band, with a ground component represented by a Dirac function and volume associated with a narrow peak. The performance of this low-dimensional parametric tomographic approach is assessed using P-band data collected during the TropiSAR campaign over a tropical forest, and using the TomoSense dataset acquired over the temperate forest. Results show that this approach can accurately and reliably estimate key structural parameters of the observed tropical and temperate forests. A low resolution dataset is simulated from the TropiSAR data in order to provide a representative sample of the future BIOMASS data, yielding better performances than those from methods that will be used in its upcoming acquisition phase. The proposed approach has been extended to the dual-baseline interferometric configuration, which is the longest phase of the mission, providing adequate and well-designed estimates of the structure of the forest. The estimate accuracy from this minimal tomographic configuration has been improved using the synergy between the two modes of the BIOMASS mission through a regularization method.
Auteurs, date et publication :
Auteurs Pierre-Antoine Bou
Date : 2025
Catégorie(s)
#CIRAD #FORET ParacouRésumé
TROLL 4.0 is an individual-based forest dynamics model that jointly simulates the structure, diversity, and functioning of tropical forests, including their water balance, carbon fluxes, and leaf phenology, while accounting for intraspecific trait variation for a large number of species. In a companion paper, we describe how the model represents the physiological and demographic processes that control the tree life cycle in a 1 m resolution spatially explicit scene and uses plant functional traits measurable in the field to parameterize such processes across species and individuals (Maréchaux et al., 2025). Here we evaluate the performance of TROLL 4.0 for two Amazonian sites with contrasting soil and climate properties. We assessed the model's ability to represent forest structure, composition, and dynamics using lidar-derived spatial distribution of top canopy height and forest inventories combined with information on plant functional traits. We also evaluated the model's ability to represent carbon and water fluxes, as well as leaf area variation, at daily and fortnightly resolution over a decade, using detailed information from on-site eddy covariance towers, satellite data, and ground-based or airborne lidar data. We finally compared the responses of carbon and water fluxes to environmental drivers between simulated and observed data. Overall, TROLL 4.0 provided a realistic representation of forests at both sites. The simulated canopy height distribution showed a high correlation coefficient (CC) with observed aerial and satellite data (CC > 0.92), while the species and functional composition were well represented (CC > 0.75). TROLL 4.0 also realistically simulated the seasonal variability of carbon and water fluxes (CC > 0.46) and their responses to environmental drivers, while capturing temporal variations in leaf area (CC > 0.76) and its partitioning into leaf age cohorts. However, TROLL 4.0 overestimated annual gross primary productivity at both sites (mean RMSEP = 0.94 ± 0.67 kgC m−2 yr−1) and evapotranspiration at one site (mean RMSEP = 0.75 ± 0.63 mm d−1), likely due to an underestimation of the soil water depletion and stomatal control during the dry season. This evaluation highlights the potential of TROLL 4.0 to represent ecosystem fluxes and the structure, diversity, and dynamics of plant communities at a fine resolution, paving the way for model predictions of the effects of climate change, fragmentation, and forest management on forest structure and dynamics.
Auteurs, date et publication :
Auteurs Sylvain Schmitt , Fabian J. Fischer , James G. C. Ball , Nicolas Barbier , Marion Boisseaux , Damien Bonal , Benoit Burban , Xiuzhi Chen , Géraldine Derroire , Jeremy W. Lichstein , Daniela Nemetschek , Natalia Restrepo-Coupe , Scott Saleska , Giacomo Sellan , Philippe Verley , Grégoire Vincent , Camille Ziegler , Jérôme Chave , Isabelle Maréchaux
Publication : Geoscientific Model Development
Date : 2025
Volume : 18
Issue : 16
Pages : 5205-5243
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Exploring the biodiversity hidden in tropical rainforests canopies represents a major frontier in biodiversity research yet remains challenging. Environmental DNA (eDNA) can revolutionize this field as it did already in various ecosystems. Here, we test the hypothesis that eDNA contained in canopy throughfall could be used to monitor this elusive diversity and detect anthropogenic disturbance. Using custom-made, low-cost rain collectors, we sampled rainwash eDNA in a mature Amazonian forest and a nearby tree plantation. We successfully detected eDNA from tropical woody and epiphyte plants, vertebrates (mammals, birds, and amphibians), and insects (e.g., mosquitoes, ants, and beetles). The taxonomic composition and diversity reflected disturbance, with significantly lower diversity in the plantation. Crucially, rainwash eDNA integrated biodiversity over a 10-day period in passive collectors and provided a local signature. This approach has thus potential for establishing a cost-effective monitoring system for tropical moist forest canopies, applicable in impact assessments and sustainable management.
Auteurs, date et publication :
Auteurs Lucie Zinger , Anne-Sophie Benoiston , Yves Cuenot , Céline Leroy , Eliane Louisanna , Lucie Moreau , Frédéric Petitclerc , Finn Piatscheck , Jérôme Orivel , Cécile Richard-Hansen , Lou Hansen-Chaffard , Uxue Suescun , Valérie Troispoux , Frédéric Boyer , Jérôme Chave , Thibaud Decaëns , Antoine Fouquet , Johan Pansu , Jérémy Raynaud , Rodolphe Rougerie
Publication : Science Advances
Date : 2025
Volume : 11
Issue : 33
Pages : eadx4909
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Forest measurement plays a vital role in monitoring climate change and quantifying the global carbon cycle. Synthetic Aperture Radar Tomography (TomoSAR) has long been an effective technique for reconstructing three-dimensional (3D) forest structures. With recent advancements in Artificial Intelligence (AI), methods based on Machine Learning (ML) and Deep Learning (DL) have been proposed for estimating parameters in forested areas. Both approaches address the height retrieval problem as a classification task. In this paper, two methodologies—ML-based CatBoost and DL-based TomoSAR Neural Network (TSNN)—are introduced and compared in terms of accuracy and computational load, demonstrating that they can effectively replace traditional model-based TomoSAR methods.
Auteurs, date et publication :
Auteurs Francesca Razzano , Wenyu Yang , Sergio Vitale , Giampaolo Ferraioli , Vito Pascazio , Silvia Liberata Ullo , Gilda Schirinzi
Date : 2025
Pages : 512-516
Catégorie(s)
#CIRAD #FORET ParacouRésumé
High intraspecific variability and uneven interspecies spectral distances weaken the link between spectral variance and taxonomic diversity. Simulations of artificial tree communities in a tropical f...
Auteurs, date et publication :
Auteurs Colette Badourdine , Jean-Baptiste Féret , Raphaël Pélissier , Grégoire Vincent
Publication : Applied Vegetation Science
Date : 2025
Volume : 28
Issue : 4
Pages : e70050
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Light drones provide a cheap and effective tool to monitor forest canopy, especially in tropical and equatorial contexts, where infrastructure and resources are limiting. In these regions, good quality optical satellite images are rare, yet the stakes are maximal to characterize forest function, dynamics, diversity, and phenology, and more generally the vegetation-climate interplay.
Auteurs, date et publication :
Auteurs Nicolas Barbier , Pierre Ploton , Hadrien Tulet , Gaëlle Viennois , Hugo Leblanc , Benoît Burban , Maxime Réjou-Méchain , Philippe Verley , James Ball , Denis Feurer , Grégoire Vincent
Publication : ISPRS Open Journal of Photogrammetry and Remote Sensing
Date : 2026
Volume : 19
Pages : 100114
Catégorie(s)
#CIRAD #FORET ParacouRésumé
The ForestScan project was conceived to evaluate new technologies for characterising forest structure and biomass at Forest Biomass Reference Measurement Sites (FBRMS). It is closely aligned with other international initiatives, particularly the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) aboveground biomass (AGB) cal/val protocols, and is part of GEO-TREES, an international consortium dedicated to establishing a global network of Forest Biomass Reference Measurement Sites (FBRMS) to support EO and encourage investment in relevant field-based observations and science. ForestScan is the first demonstration of what can be achieved more broadly under GEO-TREES, which would significantly expand and enhance the use of EO-derived AGB estimates.
We present data from the ForestScan project, a unique multiscale dataset of tropical forest three-dimensional (3D) structural measurements, including terrestrial laser scanning (TLS), unpiloted aerial vehicle laser scanning (UAV-LS), airborne laser scanning (ALS), and in-situ tree census and ancillary data. These data are critical for the calibration and validation of EO estimates of forest biomass, as well as providing broader insights into tropical forest structure.
Data are presented for three FBRMS: FBRMS-01: Paracou, French Guiana; FBRMS-02: Lopé, Gabon; and FBRMS-03: Kabili-Sepilok, Malaysia. Field data for each site include new 3D LiDAR measurements combined with plot tree census and ancillary data, at a multi-hectare scale. Not all data types were collected at all sites, reflecting the practical challenges of field data collection. We also provide detailed data collection protocols and recommendations for TLS, UAV-LS, ALS and plot census measurements for each site, along with requirements for ancillary data to enable integration with ALS data (where possible) and upscaling to EO estimates. We outline the requirements and challenges for field data collection for each data type and discuss the practical considerations for establishing new FBRMS or upgrading existing sites to FBRMS standard, including insights into the associated costs and benefits. All datasets described in this study are openly available. The TLS, UAV-LS and ALS datasets are provided through the ForestScan Project Data Collection in the CEDA archive (https://doi.org/10.5285/88a8620229014e0ebacf0606b302112d, Chavana-Bryant et al., 2025l). Tree census and plot description data for FBRMS-01 (Paracou, French Guiana) are hosted in the CIRAD Dataverse (https://doi.org/10.18167/DVN1/94XHID, Derroire et al., 2025b). Tree census and ancillary data for FBRMS-02 (Lopé, Gabon) and FBRMS-03 (Kabili-Sepilok, Malaysia) are available via a ForestPlots.net data package (https://doi.org/10.5521/forestplots.net/2025_2, Chavana-Bryant et al., 2025k). Together, these repositories provide access to the complete set of datasets released as part of the ForestScan project.
Auteurs, date et publication :
Auteurs Cecilia Chavana-Bryant , Phil Wilkes , Wanxin Yang , Andrew Burt , Peter Vines , Amy C. Bennett , Georgia C. Pickavance , Declan L. M. Cooper , Simon L. Lewis , Oliver L. Phillips , Benjamin Brede , Alvaro Lau , Martin Herold , Iain M. McNicol , Edward T. A. Mitchard , David A. Coomes , Toby D. Jackson , Löic Makaga , Heddy O. Milamizokou Napo , Alfred Ngomanda
Publication : Earth System Science Data
Date : 2026
Volume : 18
Issue : 2
Pages : 1243-1274
Catégorie(s)
#CIRAD #FORET ParacouRésumé
The aim of this study, which was conducted in French Guiana, was to characterize the karyotypes of nine ant species belonging to the genera Anochetus, Apterostigma, Cyphomyrmex, Camponotus, Gigantiops, Myrmicocrypta, Odontomachus and Pseudomyrmex, and to compare them with published data. We present the first descriptions of the karyotypes of Gigantiops destructor (Fabricius), an endemic Formicinae of the Amazonian region, which is the only living species in the tribe Gigantiopini, and of a species from the poorly-known cryptic genus Myrmicocrypta, which belongs to the Myrmicinae tribe Attini.
Auteurs, date et publication :
Auteurs Cléa S.F. Mariano , Igor da Silva Santos , Sarah Groc , Céline Leroy , Pierre Jean Malé , Mario X. Ruiz-González , Philippe Cerdan , Alain Dejean , Jacques H.C. Delabie
Publication : Annales de la Societe Entomologique de France
Date : 2025
Volume : 47
Issue : 1-2
Pages : 140–146
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Quantifying and monitoring the structure and degradation of tropical forests over regional to global scales is gaining increasing scientific and societal importance. Reliable automated methods are only beginning to appear; for instance, through the recent development of textural approaches applied to high resolution optical imagery. In particular, the Fourier Transform Textural Ordination (FOTO) method shows some potential to provide non-saturating estimates of tropical forest structure, including for large scale applications. However, we need to understand more precisely how canopy structure interacts with physical signals (light) to produce a given texture, notably to assess the method's sensitivity to varying sun-view acquisition conditions. In this study, we take advantage of the detailed description of canopy topography provided by airborne small footprint LiDAR data acquired over the Paracou forest experimental station in French Guiana. Using hillshade models and a range of sun-view angles identical to the actual parameter distributions found for Quickbird™ images over the Amazon, we study noise and bias in texture estimation induced by the changing configurations. We introduce the bidirectional texture function, which summarizes these effects, and in particular the existence of a textural ‘hot spot', similar to a well-known feature of bidirectional reflectance studies. For texture, this effect implies that coarseness decreases in configurations for which shadows are concealed to the observer. We also propose a method, termed partitioned standardization, that allows mitigating acquisition effects and discuss the potential for an operational use of VHR optical imagery and the FOTO method in the current context of international decisions to reduce CO2 emissions due to deforestation and forest degradation.
Auteurs, date et publication :
Auteurs Nicolas Barbier , Christophe Proisy , Cédric Véga , Daniel Sabatier , Pierre Couteron
Publication : Remote Sensing of Environment
Date : 2011
Volume : 115
Issue : 1
Pages : 167–179