Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The study aimed to calibrate the model 3-PG for Eucalyptus saligna in the region of Guaíba, RS for the following variables diameter at breast height (DBH), total height, wood volume and biomass of stem (branch, bark and wood). The study took place in the region of Guaíba, RS, and clonal plantations of Eucalyptus saligna in various spacings were used. Six different ages were selected along the crop cycle (2nd to 7th year). A forest inventory was carried out in 60 plants per plot for further collection of biomass (three trees fractionated into wood, bark, branches and leaves). The biomass of roots on the medium tree of each plot was measured to a depth of 1 m. Physical and chemical analysis were performed in the samples of soil in layers from 0 to 20 cm, 20 to 40 cm and 40 to 100 cm. Litter deposition was estimated by allocating 4 square wood collectors of 0.5 m². Leaf area was obtained through digital photographs and thus the specific leaf area was estimated. The physiological parameters were measured using the Li-Cor 6400 in six plots, one at each age. Climatic parameters were provided through the Agronomic Experimental Station of the Federal University of Rio Grande do Sul. Allometric and nonlinear equations adjusted for the fraction branch/bark, wood basic density and specific leaf area did not present a good adjustment because there was variability in the data used. Although the estimated values differed from the values observed, the model performance in terms of adjustment exceeded other parameterizations available in the literature. The parameterization and calibration of the model 3-PG were performed satisfactorily meeting all the predictions proposed by the model. The model validation was not statistically accepted, but their estimated data can be used as a source of estimates for the variables studied, demonstrating the potential of its use, however, the need for additional studies to better understanding of this species in this region. The use of the parameters raised by other authors in other regions cannot be used for the region studied. / O trabalho teve como objetivo principal calibrar o modelo 3-PG para Eucalyptus saligna na região de Guaíba, RS para as varáveis diâmetro à altura do peito (DAP), altura total, volume de madeira e biomassa de stem (galho, casca e lenho). O estudo ocorreu na região de Guaíba, RS, sendo utilizados plantios clonais de Eucalyptus saligna, em diversos espaçamentos. Foram selecionadas seis idades ao longo do ciclo de cultivo (2º ao 7º ano). Realizou-se o inventário florestal em 60 plantas por parcela, para posterior coleta da biomassa (três árvores, sendo fracionadas em lenho, casca, galhos e folhas). Na árvore média de cada parcela, mensurou-se a biomassa de raízes até a profundidade de 1 m. Análises físicas e químicas em amostras de solo foram realizadas nas camadas de 0 a 20 cm, 20 a 40 cm e 40 a 100 cm. A deposição de serapilheira foi estimada através da alocação de quatro coletores quadrados de madeira de 0,5 m². A área foliar obteve-se através de fotografias digitais e, a partir destas, estimou-se a área foliar específica. Os parâmetros fisiológicos foram mensurados através do aparelho Li-Cor 6400, em seis parcelas, uma em cada idade. Os parâmetros climáticos foram fornecidos através da Estação Experimental Agronômica da Universidade Federal do Rio Grande do Sul. As equações alométricas e as não-lineares ajustadas para fração galho/casca, densidade básica da madeira e área foliar específica não tiveram bom ajuste, pois há variabilidade nos dados utilizados. Apesar dos valores estimados serem diferentes dos valores observados, o desempenho do modelo, em termos de ajuste, superou outras parametrizações disponíveis na literatura. A parametrização e a calibração do modelo 3-PG foram feitas de modo satisfatório, atendendo todas as predições propostas pelo modelo. A validação do modelo não foi estatisticamente aceita, mas os seus dados estimados podem ser utilizados como fonte de estimativa para as variáveis estudadas, evidenciando o potencial do seu uso, porém, com a necessidade de estudos adicionais para melhor compreensão desta espécie para esta região. O emprego dos parâmetros levantados por outros autores em outras regiões não pode ser utilizada para a região de estudo.

Potential uses of dry weight information for simulation, and sources of data, for simulation of forest fuels were discussed. Tree and crown component dry weights of 23 Douglas fir, 18 western hemlock, and 23 western red cedar trees expanded to 314 "model" trees were investigated. Data were collected on the University Research Forest near Haney, British Columbia. Multiple regression techniques were used for the analysis. The best four independent variables are listed and the possibility of retaining a single independent variable, with its implications, are discussed. All predicting equations were conditioned to zero intercept and statistically tested for significance by the F-test. Of the independent variables tested, the combined variable of breast height diameter squared times total tree height was most closely related to tree component dry weights. The product of diameter and crown width squared was found to be the best single variable to describe crown component dry weights for Douglas fir. The dry weights of western hemlock and western red cedar crown components were most closely associated with breast height diameter times crown length. Reliable estimates of tree component dry weights were obtained. Crown components were highly variable and widely dispersed about the mean which resulted in less accurate estimates. / Forestry, Faculty of / Graduate

Le colture energetiche su larga scala, cosi come l’utilizzo di biomassa forestale non residuale, impattano notevolvente i cicli di nutrienti, la biodiversità e l’occupazione di suolo (i tre limiti del pianeta già oltrepassati, oltre al cambiamento climatico) risultando non riconciliabili con uno spazio di operazione sicuro per l’umanità. Occorre piuttosto perseguire fonti di energia rinnovabile che consentano di disaccoppiare il sistema energetico dall’emissione di gas climalteranti ed al contempo richiedano un uso minimo del suolo e limitati impatti sui cicli dei nutrienti e sulla biodiversità.La biomassa forestale residua, la biomassa coltivata in terreni marginali / abbandonati con un basso apporto di nutrienti e la biomass residual proveniente da altri settori dell'economia possono fornire una fonte temporanea di energia per quei settori più difficili da dissociare dai combustibili fossili, in un percorso che porti verso una società in meno dipendente dalle tecnologie di combustione. / Large scale dedicated cultivation of bioenergy on fertile arable land or the large scale deployment of biomass from standing forest, with their impact on nutrient cycles, biodiversity and land occupation (the three planet boundaries which are already overtaken beside climate change) is difficult to reconcile with a safe operating space for humanity. Renewable energy sources allowing the decoupling of energy systems from GHG emission requiring a minimal land use, and therefore limited impacts on nutrient cycles and biodiversity, are to be pursued. Residual biomass such as forest harvest residues, biomass cultivated in marginal/abandoned land with low nutrients input, and biowaste from other sectors of the economy may provide a temporary source of energy for those sectors more difficult to decouple from fossil fuels, towards a society less dependent on combustion technologies.

The work presented in this thesis mainly focuses on two subjects related to the application of remote sensing data: (1) for land cover classification combining optical sensor, texture features generated from spectral information and synthetic aperture radar (SAR) features, and (2) to develop a non-destructive approach for above ground biomass (AGB) and forest attributes estimation employing multi-source remote sensing data (i.e. optical data, SAR backscatter) combined with in-situ data. Information provided by reliable land cover map is useful for management of forest resources to support sustainable forest management, whereas the generation of the non-destructive approach to model forest biophysical properties (e.g. AGB and stem volume) is required to assess the forest resources more efficiently and cost-effective, and coupled with remote sensing data the model can be applied over large forest areas. This work considers study sites over tropical rain forest landscape in Indonesia characterized by different successional stages and complex vegetation structure including tropical peatland forests. The thesis begins with a brief introduction and the state of the art explaining recent trends on monitoring and modeling of forest resources using remote sensing data and approach. The research works on the integration of spectral information and texture features for forest cover mapping is presented subsequently, followed by development of a non-destructive approach for AGB and forest parameters predictions and modeling. Ultimately, this work evaluates the potential of mosaic SAR data for AGB modeling and the fusion of optical and SAR data for peatlands discrimination. The results show that the inclusion of geostatistics texture features improved the classification accuracy of optical Landsat ETM data. Moreover, the fusion of SAR and optical data enhanced the peatlands discrimination over tropical peat swamp forest. For forest stand parameters modeling, neural networks method resulted in lower error estimate than standard multi-linear regression technique, and the combination of non-destructive measurement (i.e. stem number) and remote sensing data improved the model accuracy. The up scaling of stem volume and biomass estimates using Kriging method and bi-temporal ETM image also provide favorable estimate results upon comparison with the land cover map. / Die in dieser Dissertation präsentierten Ergebnisse konzentrieren sich hauptsächlich auf zwei Themen mit Bezug zur angewandten Fernerkundung: 1) Der Klassifizierung von Oberflächenbedeckung basierend auf der Verknüpfung von optischen Sensoren, Textureigenschaften erzeugt durch Spektraldaten und Synthetic-Aperture-Radar (SAR) features und 2) die Entwicklung eines nichtdestruktiven Verfahrens zur Bestimmung oberirdischer Biomasse (AGB) und weiterer Waldeigenschaften mittels multi-source Fernerkundungsdaten (optische Daten, SAR Rückstreuung) sowie in-situ Daten. Eine zuverlässige Karte der Landbedeckung dient der Unterstützung von nachhaltigem Waldmanagement, während eine nichtdestruktive Herangehensweise zur Modellierung von biophysikalischen Waldeigenschaften (z.B. AGB und Stammvolumen) für eine effiziente und kostengünstige Beurteilung der Waldressourcen notwendig ist. Durch die Kopplung mit Fernerkundungsdaten kann das Modell auf große Waldflächen übertragen werden. Die vorliegende Arbeit berücksichtigt Untersuchungsgebiete im tropischen Regenwald Indonesiens, welche durch verschiedene Regenerations- und Sukzessionsstadien sowie komplexe Vegetationsstrukturen, inklusive tropischer Torfwälder, gekennzeichnet sind. Am Anfang der Arbeit werden in einer kurzen Einleitung der Stand der Forschung und die neuesten Forschungstrends in der Überwachung und Modellierung von Waldressourcen mithilfe von Fernerkundungsdaten dargestellt. Anschließend werden die Forschungsergebnisse der Kombination von Spektraleigenschaften und Textureigenschaften zur Waldbedeckungskartierung erläutert. Desweiteren folgen Ergebnisse zur Entwicklung eines nichtdestruktiven Ansatzes zur Vorhersage und Modellierung von AGB und Waldeigenschaften, zur Auswertung von Mosaik- SAR Daten für die Modellierung von AGB, sowie zur Fusion optischer mit SAR Daten für die Identifizierung von Torfwäldern. Die Ergebnisse zeigen, dass die Einbeziehung von geostatistischen Textureigenschaften die Genauigkeit der Klassifikation von optischen Landsat ETM Daten gesteigert hat. Desweiteren führte die Fusion von SAR und optischen Daten zu einer Verbesserung der Unterscheidung zwischen Torfwäldern und tropischen Sumpfwäldern. Bei der Modellierung der Waldparameter führte die Neural-Network-Methode zu niedrigeren Fehlerschätzungen als die multiple Regressions. Die Kombination von nichtdestruktiven Messungen (z.B. Stammzahl) und Fernerkundungsdaten führte zu einer Steigerung der Modellgenauigkeit. Die Hochskalierung des Stammvolumens und Schätzungen der Biomasse mithilfe von Kriging und bi-temporalen ETM Daten lieferten positive Schätzergebnisse im Vergleich zur Landbedeckungskarte.

La thèse a pour objectif de participer à l’étude de l’Union européenne et à celle des relations internationales en ciblant spécifiquement la régulation du secteur forêt-bois-papier. La question de fond est de savoir comment la gestion des forêts est construite en problème public européen. Prenant acte d’un agenda mondial qui donne à voir un problème forestier globalisé et des processus de gouvernance opposant multilatéralisme et acteurs transnationaux, la thèse propose de porter la focale sur les acteurs européens qui définissent et politisent les enjeux forestiers selon leur propre relation à la ressource. Pour ce faire, le travail de recherche s’appuie sur une hypothèse centrale selon laquelle l’institutionnalisation des territoires forestiers constitue une ressource d’action publique pour les acteurs face à la régulation politique multiscalaire. Afin de mettre en avant la capacité des acteurs européens à circuler parmi les échelles de régulation pour participer à la construction des politiques publiques sectorielles, la thèse s’appuie sur un cadre théorique empruntant aux Théories des relations internationales et à l’Analyse des politiques publiques. Forte d’une telle grille d’analyse sociologisée, une seconde partie s’articule autour de trois études de cas de politiques européennes de la forêt (la protection des forêts contre les feux, la valorisation énergétique de la biomasse forestière et la lutte contre le commerce international de bois illégal). Au total, elles montrent toutes trois la capacité des acteurs locaux à territorialiser des enjeux globalisés de gestion d’une ressource naturelle. / This work aims at contributing to the study of the European Union and International Relations. Through analyzing the regulation of forest-based industries and the globalization of forest issues, the aim is to identify how both have been constructed as a European public problem. This is implemented around a central hypothesis: forest territories are institutionalized by actors who participate in its regulation. In order to ascertain the ability of actors to move between scales of regulation, the thesis is grounded on theoretical tools derived from the Theories of international relations and Public policy analysis. After a first part dedicated to defining this approach, a second is presents three case studies of European public policy (forest protection against fire, t renewable energy and actions to counter the trade of illegal wood). In sum, each one shows the ability of actors to territorialize a globalized forest issue.

Airborne discrete-return lidar is an active remote sensing technology capable of obtaining accurate, fine-resolution three-dimensional measurements over large areas. Discrete-return lidar data produce three-dimensional object characterizations in the form of point clouds defined by precise x, y and z coordinates. The data also provide intensity values for each point that help quantify the reflectance and surface properties of intersected objects. These data features have proven to be useful for the characterization of many important forest attributes, such as standing tree biomass, height, density, and canopy cover, with new applications for the data currently accelerating. This dissertation explores three new applications for airborne discrete-return lidar data. The first application uses lidar-derived metrics to predict understory vegetation cover, which has been a difficult metric to predict using traditional explanatory variables. A new airborne lidar-derived metric, understory lidar cover density, created by filtering understory lidar points using intensity values, increased the coefficient of variation (R²) from non-lidar understory vegetation cover estimation models from 0.2-0.45 to 0.7-0.8. The method presented in this chapter provides the ability to accurately quantify understory vegetation cover (± 22%) at fine spatial resolutions over entire landscapes within the interior ponderosa pine forest type. In the second application, a new method for quantifying and locating snags using airborne discrete-return lidar is presented. The importance of snags in forest ecosystems and the inherent difficulties associated with their quantification has been well documented. A new semi-automated method using both 2D and 3D local-area lidar point filters focused on individual point spatial location and intensity information is used to identify points associated with snags and eliminate points associated with live trees. The end result is a stem map of individual snags across the landscape with height estimates for each snag. The overall detection rate for snags DBH ≥ 38 cm was 70.6% (standard error: ± 2.7%), with low commission error rates. This information can be used to: analyze the spatial distribution of snags over entire landscapes, provide a better understanding of wildlife snag use dynamics, create accurate snag density estimates, and assess achievement and usefulness of snag stocking standard requirements. In the third application, live above-ground biomass prediction models are created using three separate sets of lidar-derived metrics. Models are then compared using both model selection statistics and cross-validation. The three sets of lidar-derived metrics used in the study were: 1) a 'traditional' set created using the entire plot point cloud, 2) a 'live-tree' set created using a plot point cloud where points associated with dead trees were removed, and 3) a 'vegetation-intensity' set created using a plot point cloud containing points meeting predetermined intensity value criteria. The models using live-tree lidar-derived metrics produced the best results, reducing prediction variability by 4.3% over the traditional set in plots containing filtered dead tree points. The methods developed and presented for all three applications displayed promise in prediction or identification of unique forest attributes, improving our ability to quantify and characterize understory vegetation cover, snags, and live above ground biomass. This information can be used to provide useful information for forest management decisions and improve our understanding of forest ecosystem dynamics. Intensity information was useful for filtering point clouds and identifying lidar points associated with unique forest attributes (e.g., understory components, live and dead trees). These intensity filtering methods provide an enhanced framework for analyzing airborne lidar data in forest ecosystem applications. / Graduation date: 2013

South Africa depends largely on afforestation programs for its timber supplies due to the great demands for fiber and wood products. This has brought discomfort to other water users who have advocated that the effects of afforestation on water resources are detrimental to the country as a whole since South Africa is known as a water scarce country. This study has undertaken to integrate a process-based model and remote sensing data to estimate water use and productivity of Eucalyptus grandis in the Zululand areas of South Africa. The remote sensing techniques and recently developed "process based model" that is 3PG-S were used to estimate water use and productivity of Eucalyptus grandis, an economically important plantation species grown in the summer rainfall areas of South Africa. The study utilized monthly Landsat Thematic Mapper datasets and climatic data as inputs into the 3PG-S model, determined the Leaf Area Index (LAI) and Specific Leaf Area (SLA) through direct (destructive sampling) and indirect measurements (LiCor- 2000) and assessed the relationships between various vegetation indices (VI's) using correlation and regression analyses. The results suggest that all the indices, except the ratio VI, correlated significantly with LiCor-determined and destructively measured LAI values with both normalized difference vegetation index (NDVI) and Ratio Vegetation Index (RVI) (r=0.86, p / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritburg, 2007.

Human pressure on forest resources increased significantly during the past decades through land use and land use change, especially in the tropics where forest clearing is a major source of CO2 release in the atmosphere. Consequently, forests are the focus of international environmental policies and discussions aiming to reduce emissions from deforestation and forest degradation (i.e. REDD+). The capacity of participating countries to regularly provide accurate forests C stocks measurements at a national scale thus represents an important challenge to address. In dense forests, generally only the above ground biomass (AGB) is measured as it accounts for more than 50% of total C stocks. However, important gaps remain at each scale of measurement, i.e. from felled tree to regional mapping, with the resulting errors propagation through these different scales being probably the most concerning issue.<p><p>In the present work, we propose to address these issues by using a multi-scale approach in order to improve our global understanding of AGB variations in dense tropical forests of Central Africa. In particular, we studied (i) forest AGB prediction from remote-sensing textural analysis, (ii) the potential role of largest trees as predictor of the entire forest-stand AGB and (iii) intra- and inter-individual radial variation of wood specific gravity (WSG, i.e. oven-dry mass divided by its green volume) and its potential consequences on the estimation of the AGB of the tree. <p>First, we analyzed the potential use of textural analysis to predict AGB distribution based on very high spatial resolution satellite scenes. In particular, we used the Fast Fourier Transform Ordination (FOTO) method to predict AGB from heterogeneous forest stands of the Democratic Republic of the Congo (DRC). Here, based on 26 ground plots of 1-ha gathered from the field, plus a successful combination of Geoeye and Quickbird contrasted scenes, we were able to predict and to map AGB with a robust model (R² = 0.85; RMSE = 15%) based on textural gradients. <p>Secondly, the research of AGB indicators was focused on the dissection of the role played by largest trees. Here we found largest trees not only hold large share of forest carbon stock but they contain the print of most of forest-stand structure and diversity. Using a large dataset from western Cameroon to eastern DRC, we developed a non-linear model to predict forest carbon stock from the measurement of only a few large trees. We found the AGB of the 5 % largest stems allow to predict the AGB of the entire forest-stand yielding an R² of 0.87 at a regional scale. Focusing on largest trees species composition, we also showed only 5 % of species account for 50 % of total AGB.<p>In the end, we investigated inter- and intra-individual WSG variations. Despite recognized inter- and intra-specific variations along the radial axis, their ecological determinants and their consequences on trees aboveground biomass assessments remain understudied in tropical regions. To our knowledge, it has never been investigated in Africa. Using a 3-D X-Ray scanner, we studied the radial WSG variation of 14 canopy species of DRC tropical forests. Wood specific gravity variance along the radial profile was dominated by differences between species intercepts (~76%), followed by the differences between their slope (~11%) and between individual cores intercept (~10%). Residual variance was minimal (~3%). Interestingly, no differences were found in the comparison of mean WSG observed on the entire core and the mean WSG at 1-cm under the bark (intercept ~0; coefficient = 1.03). In addition, local values of WSG are strongly correlated with mean value in the global data base at species level. <p><p>I deeply believe these results favor the development of promising tools to map and to estimate accurately the AGB of tropical forest-stands. The information provided by largest trees on the entire forest-stand is particularly interesting both for developing new sampling strategies for carbon stocks monitoring and to characterize tropical forest-stand structure. In particular, our results should provide the opportunity to decrease current sampling cost while decreasing its main related uncertainties, and might also favor an increase of the current sampling coverage. <p> / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished