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Monitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)  

Public Titre : Monitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon Type de document : Thèse/HDR Auteurs : Le Bienfaiteur Sagang Takougoum, Auteur ; Bonaventure Sonké, Directeur de thèse ; Nicolas Barbier, Directeur de thèse Editeur : Yaoundé : Université de Yaoundé Année de publication : 2022 Importance : 166 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse pour obtenir le grade de Docteur de l'Université de Yaoundé 1, Spécialité Botanique-Ecologie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] Cameroun [Termes IGN] carte d'utilisation du sol [Termes IGN] carte de la végétation [Termes IGN] classification dirigée [Termes IGN] classification par maximum de vraisemblance [Termes IGN] données de terrain [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] dynamique de la végétation [Termes IGN] écotone [Termes IGN] flore locale [Termes IGN] forêt [Termes IGN] Google Earth Engine [Termes IGN] image Landsat [Termes IGN] image SPOT 6 [Termes IGN] image SPOT 7 [Termes IGN] incendie de forêt [Termes IGN] modèle statistique [Termes IGN] savane [Termes IGN] surveillance forestière Index. décimale : THESE Thèses et HDR Résumé : (Auteur) Understanding the effects of global change (combining anthropic and climatic pressures) on biome distribution needs innovative approaches allowing to address the large spatial scales involved and the scarcity of available ground data. Characterizing vegetation dynamics at landscape to regional scale requires both a high level of spatial detail (resolution), generally obtained through precise field measurements, and a sufficient coverage of the land surface (extent) provided by satellite images. The difficulty usually lies between these two scales as both signal saturation from satellite data and ground sampling limitations contribute to inaccurate extrapolations. Airborne laser scanning (ALS) data has revolutionized the trade-off between spatial detail and landscape coverage as it gives accurate information of the vegetation’s structure over large areas which can be used to calibrate satellite data. Also recent satellite data of improved spectral and spatial resolutions (Sentinel 2) allow for detailed characterizations of compositional gradients in the vegetation, notably in terms of the abundance of broad functional/optical plant types. Another major obstacle comes from the lack of a temporal perspective on dynamics and disturbances. Growing satellite imagery archives over several decades (45 years; Landsat) and available computing facilities such as Google Earth Engine (GEE) provide new possibilities to track long term successional trajectories and detect significant disturbances (i.e. fire) at a fine spatial detail (30m) and relate them to the current structure and composition of the vegetation. With these game changing tools our objective was to track long-term dynamics of forest-savanna ecotone in the Guineo-Congolian transition area of the Central Region of Cameroon with induced changes in the vegetatio structure and composition within two contrasted scenarios of anthropogenic pressures: 1) the Nachtigal area which is targeted for the dam construction and subject to intense agricultural activities and 2) the Mpem et Djim National Park (MDNP) which has no management plan. The maximum likelihood classification of the Spot 6/7 image aided with the information from the canopy height derived from ALS data discriminated the vegetation types within the Nachtigal area with good accuracy (96.5%). Using field plots data in upscaling aboveground biomass (AGB) form field plots estimates to the satellite estimates with model-based approaches lead to a systematic overestimation in AGB density estimates and a root mean squared prediction error (RMSPE) of up to 65 Mg.ha−1 (90%), whereas calibration with ALS data (AGBALS) lead to low bias and a drop of ~30% in RMSPE (down to 43 Mg.ha−1, 58%) with little effect of the satellite sensor used. However, these results also confirm that, whatever the spectral indices used and attention paid to sensor quality and pre-processing, the signal is not sufficient to warrant accurate pixel wise predictions, because of large relative RMSPE, especially above (200–250 Mg.ha−1). The design-based approach, for which average AGB density values were attributed to mapped land cover classes, proved to be a simple and reliable alternative (for landscape to region level estimations), when trained with dense ALS samples. AGB and species diversity measured within 74 field inventory plots (distributed along a savanna to forest successional gradient) were higher for the vegetation located in the MDNP compared to their pairs in the Nachtigal area. The automated unsupervised long-term (45 years) land cover change monitoring from Landsat image archives based on GEE captured a consistent and regular pattern of forest progression into savanna at an average rate of 1% (ca. 6 km².year-1). No fire occurrence was captured for savanna that transited to forest within five years of monitoring. Distinct assemblages of spectral species are apparent in forest vegetation which is consistent with the age of transition. As forest gets older AGBALS recovers at a rate of 4.3 Mg.ha-1.year-1 in young forest stands ( Note de contenu : Chapter 1. Generalities 1.1 Introduction 1.2 Literature Review Chapter 2. Material And Methods 2.1 Material 2.2 Methods Chapter 3. Results And Discussion 3.1 Results 3.2 Discussion Chapter 4. Conclusion And Perspectives 4.1 Conclusion 4.2 Perspectives Numéro de notice : 26820 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : Thèse de doctorat : Botanique-Ecologie : Yaoundé : 2022 Organisme de stage : Institut de Recherche pour le Développement IRD nature-HAL : Thèse DOI : sans Date de publication en ligne : 13/04/2022 En ligne : https://hal.inrae.fr/tel-03528875/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100465

The real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)  

Public [article]  inRemote sensing in ecology and conservation > vol 7 n° 3 (September 2021) . - pp 504 - 520 Titre : The real potential of current passive satellite data to map aboveground biomass in tropical forests Type de document : Article/Communication Auteurs : Nidhi Jha, Auteur ; Nitin Kumar Tripathi, Auteur ; Nicolas Barbier, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 504 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] biomasse aérienne [Termes IGN] forêt tropicale [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] image Worldview [Termes IGN] Thaïlande Résumé : (auteur) Forest biomass estimation at large scale is challenging and generally entails large uncertainty in tropical regions. With their wall-to-wall coverage ability, passive remote sensing signals are frequently used to extrapolate field estimates of forest aboveground biomass (AGB). However, studies often use limited reference data and/or flawed validation schemes and thus report unreliable extrapolation error estimates. Here, we compared the ability of three medium- to high-resolution passive satellite sensors, Landsat-8 (L8), Sentinel-2B (S2) and Worldview-3 (WV3), to map AGB in a forest landscape of Thailand. We used a large airborne LiDAR-derived AGB dataset as a reference to train and validate a random forest algorithm and conducted robust error assessments and variable selection using spatialized cross-validations. Our results indicate that the selected predictors strongly varied among the three sensors and between analyses restricted to low (≤200 Mg ha−1) and high (>200 Mg ha−1) AGB areas. WV3 and S2 data outperformed L8 data to extrapolate AGB (RMSE of 68 and 72 against 84 Mg ha−1, respectively) due to the inclusion of the red-edge band and, probably, to their higher spatial and spectral resolution. Sensitivity to large AGB values was higher for WV3 than for S2 and L8 with saturation point of 247 Mg ha−1 against 204 and 192 Mg ha−1. AGB values above these saturation points remained poorly predictable, especially for L8, indicating that several tropical forest AGB maps should be interpreted with extreme caution. However, predicted gradients of lower AGB values (≤200 Mg ha−1), i.e., in early forest successional stages, were fairly consistent among sensors (r > 0.70), even if the mean absolute difference between estimates was large when AGB predictions were extrapolated out of the calibration area at regional level (34%). We finally showed that calibrating the model only within the sensitivity AGB domain (e.g., Numéro de notice : A2021-731 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.203 En ligne : https://doi.org/10.1002/rse2.203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98676 [article]

Fast unsupervised multi-scale characterization of urban landscapes based on Earth observation data / Claire Teillet in Remote sensing, vol 13 n° 12 (June-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 12 (June-2 2021) . - n° 2398 Titre : Fast unsupervised multi-scale characterization of urban landscapes based on Earth observation data Type de document : Article/Communication Auteurs : Claire Teillet, Auteur ; Benjamin Pillot, Auteur ; Thibault Catry, Auteur ; Laurent Demagistri, Auteur ; Dominique Lyszczarz, Auteur ; Marc Lang, Auteur ; Pierre Couteron, Auteur ; Nicolas Barbier, Auteur ; Arsène Adou Kouassi, Auteur ; Quentin Gunther , Auteur ; Nadine Dessay, Auteur Année de publication : 2021 Projets : GeoSud / , TOSCA / Article en page(s) : n° 2398 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Bouaké [Termes IGN] Brasilia [Termes IGN] caractérisation [Termes IGN] empreinte [Termes IGN] image Pléiades-HR [Termes IGN] image Sentinel-MSI [Termes IGN] paysage urbain [Termes IGN] texture d'image [Termes IGN] zone urbaine Résumé : (auteur) Most remote sensing studies of urban areas focus on a single scale, using supervised methodologies and very few analyses focus on the “neighborhood” scale. The lack of multi-scale analysis, together with the scarcity of training and validation datasets in many countries lead us to propose a single fast unsupervised method for the characterization of urban areas. With the FOTOTEX algorithm, this paper introduces a texture-based method to characterize urban areas at three nested scales: macro-scale (urban footprint), meso-scale (“neighbourhoods”) and micro-scale (objects). FOTOTEX combines a Fast Fourier Transform and a Principal Component Analysis to convert texture into frequency signal. Several parameters were tested over Sentinel-2 and Pleiades imagery on Bouake and Brasilia. Results showed that a single Sentinel-2 image better assesses the urban footprint than the global products. Pleiades images allowed discriminating neighbourhoods and urban objects using texture, which is correlated with metrics such as building density, built-up and vegetation proportions. The best configurations for each scale of analysis were determined and recommendations provided to users. The open FOTOTEX algorithm demonstrated a strong potential to characterize the three nested scales of urban areas, especially when training and validation data are scarce, and computing resources limited. Numéro de notice : A2021-505 Affiliation des auteurs : ENSG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13122398 Date de publication en ligne : 19/06/2021 En ligne : https://doi.org/10.3390/rs13122398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98125 [article]

Déterminants de la composition floristique et estimations des stocks de carbone des peuplements forestiers matures de Uma (Tshopo, RDC) / John Katembo Mukirania (2021)  

Public Titre : Déterminants de la composition floristique et estimations des stocks de carbone des peuplements forestiers matures de Uma (Tshopo, RDC) Titre original : Determinants of floristic composition and estimates of carbon stocks in mature forest stands in Uma (Tshopo, DRC) Type de document : Thèse/HDR Auteurs : John Katembo Mukirania, Auteur ; Faustin Boyemba Bosela, Directeur de thèse ; Nicolas Barbier, Directeur de thèse Editeur : Montpellier : Centre de Coopération Internationale en recherche agronomique pour le Développement CIRAD Année de publication : 2021 Note générale : bibliographie thèse soutenue le 30 mars 2021 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse forestière [Termes IGN] composition floristique [Termes IGN] Congo [Termes IGN] dynamique de la végétation [Termes IGN] image Geoeye [Termes IGN] puits de carbone Résumé : (auteur) The study of tree assemblages in tropical forests is gaining new impetus with the need to assess carbon emissions at high precision and resolution, while limiting the erosion of diversity and promoting sustainable forest management. The objective of this study was to (i) investigate the respective roles of topographic / soil gradients and endogenous dynamics in shaping local variations in dominance; (ii) demonstrate the feasibility of studying canopy texture by harmonizing Fourier-based Textural Ordination (FOTO) indices of two GeoEye - 50 cm images, acquired from different phenologic seasons, to calibrate AGB inversion model using inventory plots. The study was conducted in Uma forest, East of Kisangani, Democratic Republic of Congo. Dataset of 30 1-ha plots, in which all trees above 10 cm diameter at 1.30 m height (DBH) were measured and identified. Standard physical and chemical properties of soil samples were determined (macro-nutrients, textural classes and pH) and a digital elevation model (SRTM 30 m) was used to infer relevant topographical features (altitude and hydromorphy). The forest in the study area is characterized by variations in the abundance of three dominant species: Petersianthus macrocarpus (P. BEAUV.) LIBEN, Gilbertiodendron dewevrei (De Wild.) J. Léonard and Julbernardia seretii (DE WILD.) TROUPIN, one non-pioneer, light demanding species and two late successional, shade tolerant species respectively. These variations occur nearly independently of variations in the substratum or topography, despite important gradients of the range of considered variables. Analyzing differential relative abundance of the three dominant species in the lower strata and in the canopy, did not provide evidence of shifts in dominance, in which a species would obviously tend to replace another through time in any of the three floristic groups. This suggests that in this study area the states of dominance in the vegetation are stable across generations, that successional dynamics are very slow or that they are localized to peculiar locations. Using FOTO method, this study documents a strong relation between observed and predicted AGBs, without cross validation (R² of the linear regression reached 0.82 (mean square error = 27.24 T/ha). This correlation was still present, although weaker, with cross validation (R² of the linear regression between observed and predicted AGBs = 0.64). The mean square error increases to 46.68 T/ha after cross validation for a mean of 450 T/ha. This result confirms the potential of FOTO indices of optical very high resolution satellite images to quantify aboveground biomass without no signal saturation in high AGB tropical forests. Numéro de notice : 17670 Affiliation des auteurs : non IGN Thématique : FORET Nature : Thèse étrangère Note de thèse : thèse : Ecologie et gestion des ressources végétales : Kisangani (République Démocratique du Congo) : 2021 Organisme de stage : UMR AMAP - Botanique et Modélisation de l'Architecture des Plantes et des Végétations nature-HAL : Thèse DOI : sans En ligne : https://hal.archives-ouvertes.fr/tel-03268307 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97979

Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach / Stéphane Momo Takoudjou in Methods in ecology and evolution, vol 9 n° 4 (April 2018)  

Public [article]  inMethods in ecology and evolution > vol 9 n° 4 (April 2018) . - pp 905 - 916 Titre : Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach Type de document : Article/Communication Auteurs : Stéphane Momo Takoudjou, Auteur ; Pierre Ploton, Auteur ; Bonaventure Sonké, Auteur ; Jan Hackenberg , Auteur ; Sébastien Griffon, Auteur ; François de Coligny, Auteur ; Narcisse Guy Kamdem, Auteur ; Moses Libalah, Auteur ; Gislain 2 Mofack, Auteur ; Gilles Le Moguédec, Auteur ; Raphaël Pélissier, Auteur ; Nicolas Barbier, Auteur Année de publication : 2018 Projets : 3-projet - voir note / Article en page(s) : pp 905 - 916 Note générale : bibliographie Funding Information : Global Environment Facility (Grant Number: TF010038), World Bank and French Government scholarship Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Afrique centrale [Termes IGN] biomasse aérienne [Termes IGN] Cameroun [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt tropicale [Termes IGN] modèle de croissance végétale [Termes IGN] puits de carbone [Termes IGN] volume en bois Mots-clés libres : Quantitative Structure Model Résumé : (auteur) Calibration of local, regional or global allometric equations to estimate biomass at the tree level constitutes a significant burden on projects aiming at reducing Carbon emissions from forest degradation and deforestation. The objective of this contribution is to assess the precision and accuracy of Terrestrial Laser Scanning (TLS) for estimating volumes and above‐ground biomass (AGB) of the woody parts of tropical trees, and for the calibration of allometric models. We used a destructive dataset of 61 trees, with diameters and AGB of up to 186.6 cm and 60 Mg respectively, which were scanned, felled and weighed in the semi‐deciduous forests of eastern Cameroon. We present an operational approach based on available software allowing the retrieving of TLS volume with low bias and high accuracy for large tropical trees. Edition of the obtained models proved necessary, mainly to account for the complexity of buttressed parts of tree trunks, which were separately modelled through a meshing approach, and to bring a few corrections in the topology and geometry of branches, thanks to the amapstudio‐scan software. Over the entire dataset, TLS‐derived volumes proved highly reliable for branches larger than 5 cm in diameter. The volumes of the remaining woody parts estimated for stumps, stems and crowns as well as for the whole tree proved very accurate (RMSE below 2.81% and R² above of .98) and unbiased. Once converted into AGB using mean local‐specific wood density values, TLS estimates allowed calibrating a biomass allometric model with coefficients statistically undistinguishable from those of a model based on destructive data. The Unedited Quantitative Structure Model (QSM) however leads to systematic overestimations of woody volumes and subsequently to significantly different allometric parameters. We can therefore conclude that a non‐destructive TLS approach can now be used as an operational alternative to traditional destructive sampling to build the allometric equations, although attention must be paid to the quality of QSM model adjustments to avoid systematic bias. Numéro de notice : A2018-205 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1111/2041-210X.12933 Date de publication en ligne : 07/11/2017 En ligne : https://doi.org/10.1111/2041-210X.12933 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93819 [article]

Regional scale rain-forest height mapping using regression-kriging of spaceborne and airborne Lidar data: application on French Guiana / Ibrahim Fayad in Remote sensing, vol 8 n° 3 (March 2016)  

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