Auteurs, date et publication :
Auteurs A. Hamadi , L. Villard , P. Borderies , C. Albinet , T. Koleck , T. Le Toan
Publication : IEEE Geoscience and Remote Sensing Letters
Date : 2017
Volume : 14
Issue : 11
Pages : 1918–1922
Catégorie(s)
#CIRAD #FORET ParacouRésumé
The objective of this study is to assess and compare different above-ground biomass (AGB) estimation models for tropical forest using P-band SAR tomography. In this paper, we investigate (1) comparative performance of back-projection and Capon beamforming tomographic estimators to analyze the vertical structure of tropical forest 2) impact of terrain slope correction on tomogram reflectivity and AGB estimates 3) correlation of tomogram reflectivity at 30m to forest AGB using different models 4) possibility of using tomographic retrieved height to improve the AGB estimation. The performance of these models is evaluated using dataset acquired during TropiSAR 2009 by ONERA over the Paracou site.
Auteurs, date et publication :
Auteurs N. Ramachandran , S. Tebaldini , M. M. d'Alessandro , S. Saatchi , O. Dikshit
Date : 2019
Pages : 1-5
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Two-level data sets consist of higher level (say population) traits computed from lower level (say individual) observations. Cluster analysis for two-level data sets aims at classifying populations using individual observations. Most existing techniques to classify populations in two-level data sets actually operate on population traits (e.g. the k-means algorithm), thus disregarding the within-population individual variability. In this study, the k-means algorithm was compared with a recently developed classification method that accounts for within-population variability. Populations were tree species in a tropical rain forest in French Guiana, and individual observations were tree diameters and diameter growth rates. Tree species were classified according to either their diameter and growth rate, or to their asymptotic diameter distribution as predicted by an Usher matrix population model. In both cases, the k-means algorithm and the two-level classification method defined species clusters that were significantly related according to the Rand index. Nevertheless, clusters showed increasing differences between the two methods as the within-population individual variability increased. Whereas the k-means algorithm produced equally-sized spherical clusters, the two-level classification method adapted the size and shape of clusters to the individual within-population variability. Taking account of individual variability to classify populations in ecology may thus be important, albeit rarely done.
Auteurs, date et publication :
Auteurs Nicolas Picard , Avner Bar-Hen
Publication : Ecological Informatics
Date : 2013
Volume : 15
Pages : 1–7
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Establishing a direct link between climate change and fluctuations in animal populations through long-term monitoring is difficult given the paucity of baseline data. We hypothesized that social wasps are sensitive to climatic variations, and thus studied the impact of ENSO events on social wasp populations in French Guiana. We noted that during the 2000 La Niña year there was a 77.1% decrease in their nest abundance along ca. 5 km of forest edges, and that 70.5% of the species were no longer present. Two simultaneous 13-year surveys (1997–2009) confirmed the decrease in social wasps during La Niña years (2000 and 2006), while an increase occurred during the 2009 El Niño year. A 30-year weather survey showed that these phenomena corresponded to particularly high levels of rainfall, and that temperature, humidity and global solar radiation were correlated with rainfall. Using the Self-Organizing Map algorithm, we show that heavy rainfall during an entire rainy season has a negative impact on social wasps. Strong contrasts in rainfall between the dry season and the short rainy season exacerbate this effect. Social wasp populations never recovered to their pre-2000 levels. This is probably because these conditions occurred over four years; heavy rainfall during the major rainy seasons during four other years also had a detrimental effect. On the contrary, low levels of rainfall during the major rainy season in 2009 spurred an increase in social wasp populations. We conclude that recent climatic changes have likely resulted in fewer social wasp colonies because they have lowered the wasps' resistance to parasitoids and pathogens. These results imply that Neotropical social wasps can be regarded as bio-indicators because they highlight the impact of climatic changes not yet perceptible in plants and other animals.
Auteurs, date et publication :
Auteurs Alain Dejean , Régis Céréghino , James M. Carpenter , Bruno Corbara , Bruno Hérault , Vivien Rossi , Maurice Leponce , Jérome Orivel , Damien Bonal , Nicolas Salamin
Publication : Plos One
Date : 2011
Volume : 6
Issue : 11
Pages : e27004
Catégorie(s)
#CIRAD #FORET ParacouRésumé
textlessptextgreaterThe seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and 35 litter productivity measurements), their associated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonality in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rainfall is textless 2000 mm yrtextlesssuptextgreater−1textless/suptextgreater (water-limited forests) and to radiation otherwise (light-limited forests). On the other hand, independent of climate limitations, wood productivity and litterfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosynthetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest productivity in a drier climate in water-limited forest, and in current light-limited forest with future rainfall textless 2000 mm yrtextlesssuptextgreater−1textless/suptextgreater.textless/ptextgreater
Auteurs, date et publication :
Auteurs Fabien H. Wagner , Bruno Hérault , Damien Bonal , Clément Stahl , Liana O. Anderson , Timothy R. Baker , Gabriel Sebastian Becker , Hans Beeckman , Danilo Boanerges Souza , Paulo Cesar Botosso , David M. J. S. Bowman , Achim Bräuning , Benjamin Brede , Foster Irving Brown , Jesus Julio Camarero , Plínio Barbosa Camargo , Fernanda C. G. Cardoso , Fabrício Alvim Carvalho , Wendeson Castro , Rubens Koloski Chagas
Publication : Biogeosciences
Date : 2016
Volume : 13
Issue : 8
Pages : 2537–2562
Catégorie(s)
#CIRAD #FORET ParacouRésumé
We generalize Ripley's K function to get a new function, M, to characterize the spatial structure of a point pattern relatively to another one. We show that this new approach is pertinent in ecology when space is not homogenous and the size of objects matters. We present how to use the function and test the data against the null hypothesis of independence between points. In a tropical tree data set we detect intraspecific aggregation and inter specific competition
Auteurs, date et publication :
Auteurs Eric Marcon , Florence Puech , Stéphane Traissac
Publication : International Journal of Ecology
Date : 2025
Volume : 2012
Catégorie(s)
#CIRAD #FORET ParacouRésumé
When 2 Mha of Amazonian forests are disturbed by selective logging each year, more than 90 Tg of carbon (C) is emitted to the atmosphere. Emissions are then counterbalanced by forest regrowth. With an original modelling approach, calibrated on a network of 133 permanent forest plots (175 ha total) across Amazonia, we link regional differences in climate, soil and initial biomass with survivors' and recruits' C fluxes to provide Amazon-wide predictions of post-logging C recovery. We show that net aboveground C recovery over 10 years is higher in the Guiana Shield and in the west (21 ±3 Mg C ha-1) than in the south (12 ±3 Mg C ha-1) where environmental stress is high (low rainfall, high seasonality). We highlight the key role of survivors in the forest regrowth and elaborate a comprehensive map of post-disturbance C recovery potential in Amazonia.
Auteurs, date et publication :
Auteurs Camille Piponiot , Plinio Sist , Lucas Mazzei , Marielos Peña-Claros , Francis E Putz , Ervan Rutishauser , Alexander Shenkin , Nataly Ascarrunz , Celso P de Azevedo , Christopher Baraloto , Mabiane França , Marcelino Guedes , Eurídice N.Honorio Coronado , Marcus V.N. D'Oliveira , Ademir R Ruschel , Kátia E da Silva , Eleneide Doff Sotta , Cintia R de Souza , Edson Vidal , Thales Ap West
Publication : eLife
Date : 2025
Volume : 5
Issue : DECEMBER2016
Catégorie(s)
#CIRAD #FORET ParacouRésumé
The objective of this paper is to provide a better understanding of the capabilities of the BIOMASS tomography concerning the retrieval of forest biomass and height in tropical areas. The analysis presented in this paper is carried out on airborne data acquired by Office National d'Etudes et de Recherches Aérospatiales (ONERA) over the site of Paracou, French Guiana, during the European Space Agency campaign TropiSAR. This high-resolution data set (125-MHz bandwidth) was reprocessed in order to generate a new data stack consistent with BIOMASS as for the bandwidth (6 MHz) and the azimuth resolution (about 12 m). To do this, two different processing approaches have been considered. One approach consisted of degrading the resolution of the airborne data through the linear filtering of raw data, followed by standard SAR processing. The other approach consisted of recovering the 3-D distribution of the scatterers at a high resolution, which was then reprojected onto the BIOMASS geometry. The latter procedure allows us to obtain a data stack that is the most realistic emulation of BIOMASS imaging capabilities. In both approaches, neither ionospheric disturbances nor temporal decorrelation has been considered. The connection to the forest biomass has been examined in both cases by investigating the correlation between the backscatter at different forest heights and the above-ground biomass (AGB) values from in situ data. As expected, the reduction of the system bandwidth to 6 MHz resulted in significant vertical resolution losses compared with the original airborne data. Nevertheless, it was possible to retrieve the forest height to within an accuracy of better than 4 m, whereas the backscattered power at the volume height (30 m above the ground) exhibited a correlation higher than 0.8 with the in situ data and no bias phenomena over the AGB values ranging from 250 to 450 t/ha.
Auteurs, date et publication :
Auteurs Dinh Ho Tong Minh , Stefano Tebaldini , Fabio Rocca , Thuy Le Toan , Ludovic Villard , Pascale C. Dubois-Fernandez
Publication : IEEE Transactions on Geoscience and Remote Sensing
Date : 2015
Volume : 53
Issue : 2
Pages : 965–975
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Quantifying forest biomass is of crucial importance for estimating carbon fluxes on the regional and global scale in climate change studies. Significant relationships have already been established between radar mean intensity and forest biomass, but these relationships show a reduced sensitivity to biomass variations for mature stands (about 80 t/ha and more). On the contrary, recent studies have shown that image texture is significantly related to biomass even for mature stands for a temperate, monospecific, even-aged forest the biomass of which is 140 t/ha at its highest point. The present paper aims at extending these observations to tropical forests which represent a large terrestrial biomass pool with values higher than 450 t/ha. Radar images were acquired during the TropiSAR experiment in 2009, which took place over a tropical rain forest located in French Guiana at P band and cross-polarization with the use of SETHI ONERA airborne instrument. Three sets of treatments applied to 15 forest stands provided biomass values from 268 to 466 t/ha where permanent zones of 6.25 ha each were mapped and regularly measured. Homogeneous patches were selected inside each of the 15 experimental stands. Statistical features were then derived for each patch: a) from grey level statistics; b) from the statistics of pixel pairs on the basis of the gray level co-occurrence matrix. It is shown that linear relationships between texture features and forest biomass are heavily influenced by stand structure and the local topography and soil of the experimental stands. But, when stands are separated on two structural groups using texture descriptors, texture/biomass regressions reveal to be very significant.
Auteurs, date et publication :
Auteurs Isabelle Champion , Jean Pierre , Da Costa , Adrien Godineau , Ludovic Villard
Publication : EARSel eProceedings
Date : 2025
Volume : 12
Issue : 1
Pages : 25–32
Catégorie(s)
#CIRAD #FORET ParacouRésumé
Mapping tropical forests to a sufficient level of spatial resolution and structural detail is a prerequisite for their rational management, which however remains a largely unmet challenge. We explore the degree to which a forest canopy height model (CHM) derived from airborne laser scanning (ALS) can discriminate between five forest types of similar height but varying structure or composition. We systematically compare various textural features (Haralick, Fourier transform-based, and wavelet- based features) and various classification procedures (linear discriminant analysis (LDA), random forest (RF), and support vector machine (SVM)) applied to two sizes of sampling units (64 m × 64 m and 32 m × 32 m). Simple height distribution statistics achieve at best 70% classification accuracy in our sample set comprising 120 sampling units of 64 m × 64 m. Using wavelet-based features, this accuracy increases to 79% but drops by 10% with smaller sampling units (32 m × 32 m). Classifier performance depends on the texture feature set used, but SVM and RF tend to perform better than LDA. High discrimination rates between forests types of similar height indicate that the ALS-derived CHM provides information suitable for mapping of tropical forest types. Wavelet-based texture features coupled with a SVM classifier was found to be the most promising combination of methods. Ancillary data derived from laser scans and notably topography could be used jointly for an improved segmentation scheme. 1.
Auteurs, date et publication :
Auteurs Pol Kennel , Marie Tramon , Nicolas Barbier , Grégoire Vincent
Publication : International Journal of Remote Sensing
Date : 2025
Volume : 34
Issue : 24
Pages : 8917–8935