Biomass Representation in Synthetic Aperture Radar Interferometry Data Sets

This work makes an attempt to explain the origin, features and potential applications of the elevation bias of the synthetic aperture radar interferometry (InSAR) datasets over areas covered by vegetation. The rapid development of radar-based remote sensing methods, such as synthetic aperture radar (SAR) and InSAR, has provided an alternative to the photogrammetry and LiDAR for determining the third dimension of topographic surfaces. The InSAR method has proved to be so effective and productive that it allowed, within eleven days of the space shuttle mission, for acquisition of data to develop a three-dimensional model of almost the entire land surface of our planet. This mission is known as the Shuttle Radar Topography Mission (SRTM). Scientists across the geosciences were able to access the great benefits of uniformity, high resolution and the most precise digital elevation model (DEM) of the Earth like never before for their a wide variety of scientific and practical inquiries. Unfortunately, InSAR elevations misrepresent the surface of the Earth in places where there is substantial vegetation cover. This is a systematic error of unknown, yet limited (by the vertical extension of vegetation) magnitude. Up to now, only a limited number of attempts to model this error source have been made. However, none offer a robust remedy, but rather partial or case-based solutions. More work in this area of research is needed as the number of airborne and space-based InSAR elevation models has been steadily increasing over the last few years, despite strong competition from LiDAR and optical methods. From another perspective, however, this elevation bias, termed here as the “biomass impenetrability”, creates a great opportunity to learn about the biomass. This may be achieved due to the fact that the impenetrability can be considered a collective response to a few factors originating in 3D space that encompass the outermost boundaries of vegetation. The biomass, presence in InSAR datasets or simply the biomass impenetrability, is the focus of this research. The report, presented in a sequence of sections, gradually introduces terminology, physical and mathematical fundamentals commonly used in describing the propagation of electromagnetic waves, including the Maxwell equations. The synthetic aperture radar (SAR) and InSAR as active remote sensing methods are summarised. In subsequent steps, the major InSAR data sources and data acquisition systems, past and present, are outlined. Various examples of the InSAR datasets, including the SRTM C- and X-band elevation products and INTERMAP Inc. IFSAR digital terrain/surface models (DTM/DSM), representing diverse test sites in the world are used to demonstrate the presence and/or magnitude of the biomass impenetrability in the context of different types of vegetation – usually forest. Also, results of investigations carried out by selected researchers on the elevation bias in InSAR datasets and their attempts at mathematical modelling are reviewed. In recent years, a few researchers have suggested that the magnitude of the biomass impenetrability is linked to gaps in the vegetation cover. Based on these hints, a mathematical model of the tree and the forest has been developed. Three types of gaps were identified; gaps in the landscape-scale forest areas (Type 1), e.g. forest fire scares and logging areas; a gap between three trees forming a triangle (Type 2), e.g. depending on the shape of tree crowns; and gaps within a tree itself (Type 3). Experiments have demonstrated that Type 1 gaps follow the power-law density distribution function. One of the most useful features of the power-law distributed phenomena is their scale-independent property. This property was also used to model Type 3 gaps (within the tree crown) by assuming that these gaps follow the same distribution as the Type 1 gaps. A hypothesis was formulated regarding the penetration depth of the radar waves within the canopy. It claims that the depth of penetration is simply related to the quantisation level of the radar backscattered signal. A higher level of bits per pixels allows for capturing weaker signals arriving from the lower levels of the tree crown. Assuming certain generic and simplified shapes of tree crowns including cone, paraboloid, sphere and spherical cap, it was possible to model analytically Type 2 gaps. The Monte Carlo simulation method was used to investigate relationships between the impenetrability and various configurations of a modelled forest. One of the most important findings is that impenetrability is largely explainable by the gaps between trees. A much less important role is played by the penetrability into the crown cover. Another important finding is that the impenetrability strongly correlates with the vegetation density. Using this feature, a method for vegetation density mapping called the mean maximum impenetrability (MMI) method is proposed. Unlike the traditional methods of forest inventories, the MMI method allows for a much more realistic inventory of vegetation cover, because it is able to capture an in situ or current situation on the ground, but not for areas that are nominally classified as a “forest-to-be”. The MMI method also allows for the mapping of landscape variation in the forest or vegetation density, which is a novel and exciting feature of the new 3D remote sensing (3DRS) technique. Besides the inventory-type applications, the MMI method can be used as a forest change detection method. For maximum effectiveness of the MMI method, an object-based change detection approach is preferred. A minimum requirement for the MMI method is a time-lapsed reference dataset in the form, for example, of an existing forest map of the area of interest, or a vegetation density map prepared using InSAR datasets. Preliminary tests aimed at finding a degree of correlation between the impenetrability and other types of passive and active remote sensing data sources, including TerraSAR-X, NDVI and PALSAR, proved that the method most sensitive to vegetation density was the Japanese PALSAR - L-band SAR system. Unfortunately, PALSAR backscattered signals become very noisy for impenetrability below 15 m. This means that PALSAR has severe limitations for low loadings of the biomass per unit area. The proposed applications of the InSAR data will remain indispensable wherever cloud cover obscures the sky in a persistent manner, which makes suitable optical data acquisition extremely time-consuming or nearly impossible. A limitation of the MMI method is due to the fact that the impenetrability is calculated using a reference DTM, which must be available beforehand. In many countries around the world, appropriate quality DTMs are still unavailable. A possible solution to this obstacle is to use a DEM that was derived using P-band InSAR elevations or LiDAR. It must be noted, however, that in many cases, two InSAR datasets separated by time of the same area are sufficient for forest change detection or similar applications

Application of Remote Sensing Technology and Ecological Modeling of Forest Carbon Stocks in Mt. Apo Natural Park, Philippines

This dissertation work explored the application of remote sensing technology for the assessment of forest carbon storage in Mt. Apo Natural Park. Biomass estimation is traditionally conducted using destructive sampling with high levels of uncertainty. A more accurate and non-destructive method for assessment of biomass level is imperative to characterize remaining forest cover. This research study aimed to: 1) examine the vegetation profile and estimate species-specific biomass of Mt. Apo Natural Park, 2) develop an algorithm to assess biomass in plot-level using a terrestrial lidar system (TLS), and 3) generate landscape-level biomass estimates using interferometric synthetic aperture radar (IFSAR). This research endeavors to provide answers to these questions: 1) how the 3 tropical allometries compare in estimating field collected species-level biomass and carbon stocks in three management zones?, 2) what are the significant terrestrial laser scanning-derived metrics to assess plot-level biomass?, and 3) to what degree of uncertainty can IFSAR estimate biomass at the landscape level? Field data was gathered from 1382 trees, covering 52 local species during fieldwork in July and August 2013. Twenty-six plots (30 m x 30 m) were sampled on three management zones: multiple use, strict protection and restoration. Local insurgency problems restricted the research team from sampling additional plots. Destructive sampling was not permitted inside the protected area, thus requiring biomass to be estimated via the use of referenced biomass from 3 allometric equations by relating tree height, diameter-at-breast height, and wood specificity volume. A vegetation profile across the park was generated using a canopy height map (CHM). Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC’s Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities. Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC’s Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities

Object-Based Coastal Morphological Change Analysis Based on LiDAR and Hurricane Events

Storms are considered one of the rapid climatic events that have a dramatic impact on coastal morphology, hence they require further investigation and quantifying of coastal changes and responses. Light detection and ranging (LiDAR) is the most advanced technology to be widely used by researchers for coastal geomorphological studies. The purpose of this study is to apply an object-based approach using repeated LiDAR surveys to understand the short-term morphological changes that occurred on Santa Rosa Island, Florida after category 3 hurricanes Ivan (2004) and Dennis (2005), making it the first study to apply this method, as opposed to previous studies’ commonly used field-based approaches. The first analysis was conducted using a coastal morphology analysis (CMA) tool. In the second analysis, the extracted mean elevation change values were linked to three factors—mean vegetation, mean slope, and mean elevation—to demonstrate their contribution to the change using ordinary least square (OLS) analysis. The third analysis was carried out using the classification and regression tree (CART) analysis. Of the study area, 18.64% encountered erosional processes and 11.35% with depositional processes during Hurricane Ivan, whereas during Hurricane Dennis, 5.91% faced erosional processes and 8.18% was affected by depositional processes. Both hurricanes resulted in a net sediment loss; 283,167 m3 during Hurricane Ivan and 52,440 m3 during Hurricane Dennis. Generally, objects tended to be irregular, asymmetrical, and shaped with smooth boundaries. Along the coast, most objects tended to have an elongated shape, but inland the shapes were more irregular. The overall OLS model during Hurricane Ivan yielded statistically significant results for the three factors, with a confidence level of 0.00 and an adjusted r-square of 0.40; and during Hurricane Dennis, the mean vegetation and mean elevation results yielded significant statistical results (p-value 0.00), while slope did not show significance and had an adjusted r-square of 0.47. CART analysis of both hurricanes ranked the mean elevation as the most important factor in predicting the mean elevation change, followed by the mean slope and finally the mean vegetation variable

An Assessment Of Ecological Processes In The Apalachicola Estuarine System, Florida

The following is a compilation of field data collected in 2011 and 2012 in Apalachicola, FL as part of a five year study assessing the ecological effects of sea level rise in the northern Gulf of Mexico. Many coastal communities, both natural and developed, will soon be working to mitigate the effects of sea level rise, if they are not already doing so. This thesis investigates the natural patterns of the Apalachicola estuarine system through the collection and analysis of in situ water, sediment, and biomass samples. Additionally, results of the field samples are presented and recommendations for additional sampling are given. The field methods and procedures developed in this study were designed to be repeated in other estuaries to build upon the work that has been conducted in Apalachicola. Water samples were tested for total suspended solids (TSS) and compared against hydrodynamic (tidal circulation and streamflow) and meteorological (wind and precipitation) characteristics. Streamflow was determined to influence a seasonal base level concentration of TSS. Wind strength and direction consistently influenced small TSS concentration fluctuations, an effect amplified by the shallow nature of the estuary. Tidal circulation appeared to have minor influences on TSS concentration fluctuations within the base level concentration range. Precipitation appeared to influence large TSS concentration fluctuations; however, due to limited data collection during storm events, more data is required to conclusively state this. Sediment cores throughout the lower Apalachicola River revealed that coarse particles settled out in upstream areas while fine particles tended to stay in suspension until low energy areas in the lower portions of the river or marsh system were reached. Finally, biomass samples were used to iv develop regression models utilizing remotely sensed data to predict biomass density in marsh areas with unprecedented accuracy. The documented patterns of this system are to be used as inputs and validation points to update an existing hydrodynamic model and to aid in the coupling and development of sediment transport and marsh equilibrium models. The field campaign developed and implemented here provides a foundation for this novel coupled modeling effort of estuarine systems. From the 2011 and 2012 sampling conducted, it is apparent that Apalachicola can be modeled as a closed system with river inflow and sediment influx as boundary conditions. Forcing local conditions should accurately represent the system. Ultimately, these models will be used to simulate future sea level rise scenarios and will provide useful decision making tools to coastal managers. Future work will include replicating water sampling in subsequent wet and dry seasons in Apalachicola, FL to confirm observed trends, in addition to implementing this sampling in Grand Bay, MS and Weeks Bay, AL. Additional biomass samples will be taken to validate the strong correlations found between remotely sensed data and in situ samples. In similar studies, it is recommended that water samples be taken to adequately represent influences from tidal cycles and riverine inflow. It is also recommended that spatially distributed biomass samples be taken to validate regression models

Forest height inventory from airborne Synthetic Aperture Radar

This study assesses the capabilities of commercially available airborne short wavelength Synthetic Aperture Radar (SAR) Interferometry (JnSAR) for retrieving individual tree and forest stand height. Individual tree and stand heights are of importance to the forest industry for a number of reasons. Tree height is a key variable for calculating the amount of wood volume in a tree stem, as well as for predictions of amount of timber for extraction. Forest stand height is an important indicator of standing biomass for management purposes as well as for the assessment of carbon storage. Height is also an important ecological parameter in its own right, and an important input parameter for line-of-site analysis. Remote sensing offers an alternative to destructive measurements for accurate, rapid and cost effective technique without user subjectivity. SAR provides the potential for direct height measurement over large areas, and can operate independently of lighting or weather conditions, which often restricts the use of other remote sensing techniques.In this study, tree height is estimated by subtracting a ground surface elevation model (a UK Ordnance Survey DEM, OSDE M , or a Digital Terrain Model, DTM, from commercial Intermap Technologies) from a Digital Surface Model, DSM, (from Intermap Technologies) and the results are then compared to field measurements of tree and stand heights. The accuracy of Intermap Technologies ST AR-3i InSAR DEM products are initially compared to national elevation data sets. Over various ground types, it was concluded that, within the test areas, over non-vegetated ground the mean difference between the DTM and OSDEM was l.38m RMSE with a l.05m Standard Deviation (SD), and this is within Intermap's stated accuracies. Over forested ground the mean difference was 13.5lm RMSE (2.2lm SD). This vegetation bias was primarily due to limitations of the interpolation procedure used to determine the DTM from the DSM.Subsequently, the use of two airborne InSAR data sets is assessed for top height retrieval as an operational product, as well as a precursor and supplement to satellite data. Firstly, X-band data from Intermap are used to retrieve homogenous plantation top height over four UK study sites using the difference between the DSM and OSDEM with mean underestimations of 33.48% (6.99m mean difference). When assessed for single species, the DSM-OSDEM procedure gave height underestimations of 18-24% for Sitka spruce and 40% for Scots pine, indicating a dependency on canopy structure. Correcting retrieved height based on linear regression with ground reference data is shown to improve height estimation; as such, applying a generic correction to retrieved heights from all four UK study sites improves overall accuracy to 16.77% (3.12m mean difference). For trees greater than 18m measured height, the accuracy is increased to 12.27% (0.92m mean difference).Secondly, X-band data are also used to retrieve tree total height over two heterogeneous woodland areas in Belize and the UK. In Glen Affric, UK, height retrieval using the X-band DSM-OSDEM procedure for individual trees produce mean underestimation of 94.87% (6.08m mean difference). In Belize, height retrieval using the X-band DSM-DEM procedure for individual trees produces a mean underestimation of 74.71% (6.85m mean difference). For the Belize test site, height retrieval using JPL Airsar C-band DSM-DEM procedure for individual trees produces retrieved heights with a mean underestimation of 55.97% (4.79m mean difference). The primary cause of error is that layover effects due to SAR geometry may result in the retrieved height from a specific image coordinate not representing the same geographical position as the measured height.Relationships between radar retrieved height and forest parameters such as stocking density and tree height and radar dependent properties such as slope and edge effects are presented as possible explanations for variations across the collected data. Supporting work using a simple coherent interferometric scattering model is also used to characterise and explain the effects on tree height retrieval due to variations in slope, number density, stand height and forest edges.The results indicate that top height retrieval over homogenous forest stands is feasible with similar accuracies to those found with other remote sensing techniques and ground survey. Individual tree location assessment does not appear to be a suitable technique for assessing height retrieval in heterogeneous environments, and further investigations are required to determine a more suitable approach. This new data set therefore potentially allows a rapid and timely management tool for use in cost-effective sustainable forest management and related applications

UNDERSTANDING ENVIRONMENTAL FACTORS DRIVING WILDLAND FIRE IGNITIONS IN ALASKAN TUNDRA

Wildland fire is a dominant disturbance agent that drives ecosystem change, climate forcing, and carbon cycle in the boreal forest and tundra ecosystems of the High Northern Latitudes (HNL). Tundra fires can exert a considerable influence on the local ecosystem functioning and contribute to climate change through biogeochemical and biogeophysical effects. However, the drivers and mechanisms of tundra fires are still poorly understood. Research on modeling contemporary fire occurrence in the tundra is also lacking. This dissertation addresses the overarching scientific question of “What environmental factors and mechanisms drive wildfire ignition in Alaskan tundra?” Environmental factors from multiple aspects are considered including fuel type and state, fire weather, topography, and ignition source. First, to understand the spatial distribution of fuel types in the tundra, multi- year satellite observations and field data were used to develop the first fractional coverage product of major fuel type components across the entire Alaskan tundra at 30 m resolution. Second, to account for the primary ignition source of fires in the HNL, an empirical-dynamical modeling framework was developed to predict the probability of cloud-to-ground (CG) lightning across Alaskan tundra, through the integration of Weather Research and Forecast (WRF) model and machine learning algorithm. Finally, environmental factors including fuel type distribution, fuel moisture state, WRF simulated ignition source and fire weather, and topographical features, were combined with empirical modeling methods to understand their roles in driving wildland fire ignitions across Alaskan tundra from 2001 to 2019. This work demonstrates the strong capability for accurate prediction of CG lightning and wildland fire probabilities, by incorporating dynamic weather models, empirical methods, and satellite observations in data-scarce regions like the HNL. The developed models present a novel component of fire danger modeling that can considerably strengthen the current capability to forecast fire occurrence and support operational fire management agencies in the HNL. In addition, the insights gained from this research will allow for more accurate representation of wildfire ignition probabilities in studies focused on assessing the impact of the projected climate change in HNL tundra which has largely absent in previous modeling efforts

Caractérisation spatio-temporelle de la dynamique des trouées et de la réponse de la forêt boréale à l'aide de données lidar multi-temporelles

La forêt boréale est un écosystème hétérogène et dynamique façonné par les perturbations naturelles comme les feux, les épidémies d'insectes, le vent et la régénération. La dynamique des trouées joue un rôle important dans la dynamique forestière parce qu'elle influence le recrutement de nouveaux individus au sein de la canopée et la croissance de la végétation avoisinante par une augmentation des ressources. Bien que l'importance des trouées en forêt boréale fut reconnue, les connaissances nécessaires à la compréhension des relations entre le régime de trouées et la dynamique forestière, en particulier sur la croissance, sont souvent manquantes. Il est difficile d'observer et de mesurer extensivement la dynamique des trouées ou les changements de la canopée simultanément dans le temps et l'espace avec des données terrain ou des images bidimensionnelles (photos aériennes,...) et ce particulièrement dans des systèmes complexes comme les forêts ouvertes ou morcelées. De plus, la plupart des recherches furent menées en s'appuyant sur seulement quelques trouées représentatives bien que les interactions entre les trouées et la structure forestière furent rarement étudiées de manière conjointe. Le lidar est un système qui balaye la surface terrestre avec des faisceaux laser permettant d'obtenir une image dense de points en trois dimensions montrant les aspects structuraux de la végétation et de la topographie sous-jacente d'une grande superficie. Nous avons formulé l'hypothèse que lorsque les retours lidar de tirs quasi-verticaux sont denses et précis, ils permettent une interprétation de la géométrie des trouées et la comparaison de celles-ci dans le temps, ce qui nous informe à propos de leur influence sur la dynamique forestière. De plus, les mesures linéaires prises à différents moments dans le temps permettraient de donner une estimation fiable de la croissance. Ainsi, l'objectif de cette recherche doctorale était de développer des méthodes et d'accroître nos connaissances sur le régime de trouées et sa dynamique, et de déterminer comment la forêt boréale mixte répond à ces perturbations en termes de croissance et de mortalité à l'échelle locale. Un autre objectif était aussi de comprendre le rôle à court terme des ouvertures de la canopée dans un peuplement et la dynamique successionelle. Ces processus écologiques furent étudiés en reconstituant la hauteur de la surface de la canopée de la forêt boréale par l'utilisation de données lidar prises. en 1998, 2003 (et 2007), mais sans spécifications d'études similaires. L'aire d'étude de 6 km² dans la Forêt d'Enseignement et de Recherche du Lac Duparquet, Québec, Canada, était suffisamment grande pour capter la variabilité de la structure de la canopée et de la réponse de la forêt à travers une gamme de peuplements à différents stades de développement. Les recherches menées lors de cette étude ont révélé que les données lidar multi-temporelles peuvent être utilisées a priori dans toute étude de télédétection des changements, dont l'optimisation de la résolution des matrices et le choix de l'interpolation des algorithmes sont essentiels (pour les surfaces végétales et terrestres) afin d'obtenir des limites précises des trouées. Nous avons trouvé qu'une technique basée sur la croissance de régions appliquée à une surface lidar peut être utilisée pour délimiter les trouées avec une géométrie précise et pour éliminer les espaces entre les arbres représentant de fausses trouées. La comparaison de trouées avec leur délimitation Iidar le long de transects linéaires de 980 mètres montre une forte correspondance de 96,5%. Le lidar a été utilisé avec succès pour délimiter des trouées simples (un seul arbre) ou multiples (plus de 5 m²). En utilisant la combinaison de séries temporelles de trouées dérivées du lidar, nous avons développé des méthodes afin de délimiter les divers types d'évènements de dynamique des trouées: l'occurrence aléatoire de trouées, l'expansion de trouées et la fermeture de trouées, tant par la croissance latérale que la régénération. La technique proposée pour identifier les hauteurs variées arbre/gaulis sur une image lidar d'un Modèle de Hauteur de Couvert (MHC) a montré près de 75 % de correspondance avec les localisations photogrammétriques. Les taux de croissance libre suggérés basés sur les donnés lidar brutes après l'élimination des sources possibles d'erreur furent utilisés subséquemment pour des techniques statistiques afin de quantifier les réponses de croissance en hauteur qui ont été trouvées afin de faire varier la localisation spatiale en respect de la bordure de la trouée. À partir de la combinaison de donnés de plusieurs groupes d'espèces (de conifères et décidues) interprétée à partir d'images à haute résolution avec des données structurales lidar nous avons estimé les patrons de croissance en hauteur des différents groupes arbres/gaulis pour plusieurs contextes de voisinage. Les résultats on montré que la forêt boréale mixte autour du lac Duparquet est un système hautement dynamique, où la perturbation de la canopée joue un rôle important même pour une courte période de temps. La nouvelle estimation du taux de formation des trouées était de 0,6 %, ce qui correspond à une rotation de 182 ans pour cette forêt. Les résultats ont montré aussi que les arbres en périphérie des trouées étaient plus vulnérables à la mortalité que ceux à l'intérieur du couvert, résultant en un élargissement de la trouée. Nos résultats confirment que tant la croissance latérale que la croissance en hauteur de la régénération contribuent à la fermeture de la canopée à un taux annuel de 1,2 %. Des évidences ont aussi montré que les trouées de conifères et de feuillus ont des croissances latérales (moyenne de 22 cm/an) et verticales similaires sans tenir compte de leur localisation et leur hauteur initiale. La croissance en hauteur de tous les gaulis était fortement positive selon le type d'évènement et la superficie de la trouée. Les résultats suggèrent que la croissance des gaulis de conifères et de feuillus atteint son taux de croissance maximal à des distances respectives se situant entre 0,5 et 2 m et 1,5 et 4 m à partir de la bordure d'une trouée et pour des ouvertures de moins de 800 m² et 250 m² respectivement. Les effets des trouées sur la croissance en hauteur d'une forêt intacte se faisaient sentir à des distance allant jusqu'à à 30 m et 20 m des trouées, respectivement pour les feuillus et les conifères. Des analyses fines de l'ouverture de la canopée montrent que les peuplements à différents stades de développement sont hautement dynamiques et ne peuvent systématiquement suivre les mêmes patrons successionels. Globalement, la forêt est presqu'à l'équilibre compositionnel avec une faible augmentation de feuillus, principalement dû à la régénération de type infilling plutôt qu'une transition successionelle de conifères tolérants à l'ombre. Les trouées sont importantes pour le maintien des feuillus puisque le remplacement en sous-couvert est vital pour certains résineux. L'étude à démontré également que la dernière épidémie de tordeuse des bourgeons de l'épinette qui s'est terminée il y a 16 ans continue d'affecter de vieux peuplements résineux qui présentent toujours un haut taux de mortalité. Les résultats obtenus démontrent que lidar est un excellent outil pour acquérir des détails rapidement sur les dynamiques spatialement extensives et à court terme des trouées de structures complexes en forêt boréale. Les évidences de cette recherche peuvent servir tant à l'écologie, la sylviculture, l'aménagement forestier et aux spécialistes lidar. Ces idées ajoutent une nouvelle dimension à notre compréhension du rôle des petites perturbations et auront une implication directe pour les aménagistes forestiers en quête d'un aménagement forestier écologique et du maintien des forêts mixtes. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Perturbation naturelle, Dynamique forestière, Dynamique des trouées, Croissances latérales, Régénération, Succession, Lidar à retours discrets, Grande superficie, Localisation des arbres individuels, Croissance en hauteur

Flood hazard hydrology: interdisciplinary geospatial preparedness and policy

Thesis (Ph.D.) University of Alaska Fairbanks, 2017Floods rank as the deadliest and most frequently occurring natural hazard worldwide, and in 2013 floods in the United States ranked second only to wind storms in accounting for loss of life and damage to property. While flood disasters remain difficult to accurately predict, more precise forecasts and better understanding of the frequency, magnitude and timing of floods can help reduce the loss of life and costs associated with the impact of flood events. There is a common perception that 1) local-to-national-level decision makers do not have accurate, reliable and actionable data and knowledge they need in order to make informed flood-related decisions, and 2) because of science--policy disconnects, critical flood and scientific analyses and insights are failing to influence policymakers in national water resource and flood-related decisions that have significant local impact. This dissertation explores these perceived information gaps and disconnects, and seeks to answer the question of whether flood data can be accurately generated, transformed into useful actionable knowledge for local flood event decision makers, and then effectively communicated to influence policy. Utilizing an interdisciplinary mixed-methods research design approach, this thesis develops a methodological framework and interpretative lens for each of three distinct stages of flood-related information interaction: 1) data generation—using machine learning to estimate streamflow flood data for forecasting and response; 2) knowledge development and sharing—creating a geoanalytic visualization decision support system for flood events; and 3) knowledge actualization—using heuristic toolsets for translating scientific knowledge into policy action. Each stage is elaborated on in three distinct research papers, incorporated as chapters in this dissertation, that focus on developing practical data and methodologies that are useful to scientists, local flood event decision makers, and policymakers. Data and analytical results of this research indicate that, if certain conditions are met, it is possible to provide local decision makers and policy makers with the useful actionable knowledge they need to make timely and informed decisions

An interdisciplinary study of the hazards associated with an AD1754 style eruption of Taal Volcano, Philippines

Taal Volcano, 60 km south of Metro Manila in Batangas Province, is one of the most active volcanoes in the Philippines. With 33 known eruptions, Taal has caused tremendous impacts on lives, property, economy and environment. The exposure of people and assets around Taal has increased greatly in recent years with around two million people living within a 35 km radius all at risk to volcanic hazards. The risk from Taal poses multiple challenges for local volcano disaster risk reduction (DRR) efforts. This interdisciplinary study combines a synthesis and critical review of historical eruptions of Taal; physical studies (geologic mapping, stratigraphic analyses and grain size measurements of the AD1754 tephra deposit); reconstruction of tephra dispersal for the AD1754 Plinian event using TEPHRA2 inversion modelling; and consideration of the social aspects of volcanic hazard and risk (e.g. socio-economic, political and DRR contexts for Batangas Province, and a pilot study assessing the knowledge, education, awareness and preparedness of Barangay Captains who are responsible for local level volcano disaster preparedness and response). Key outputs of the research include: 1) the first single, comprehensive chronology of identified historical eruptions of Taal; 2) discovery, mapping and sampling of 41 suspected AD1754 tephra outcrops; 3) first detailed field-based verification of two of the four identified phases of this event; 4) determination of likely eruption source parameters for the AD1754 event and new tephra dispersal isopachs through inversion modelling; and 5) preliminary insights into the knowledge, awareness and preparedness of the Barangay Captains, which show that while they do take volcanic risk seriously, they are ill-prepared to effectively support their communities in the case of a major volcanic crisis at Taal. The results and recommendations are aimed at strengthening volcano disaster risk management plans for Batangas Province

Establishing the sensitivity of Synthetic Aperture Radar to above-ground biomass in wooded savannas

Radar for biomass estimation has been widely investigated for temperate, boreal and tropical forests, yet tropical savanna woodlands, which generally form non-continuous cover canopies or sparse woodlands, have been largely neglected in biomass studies. This thesis evaluates the capability of Synthetic Aperture Radar (SAR) for estimating the above-ground biomass of the woody vegetation in a savanna in Belize, Central America. This is achieved by evaluating (i) polarimetric Synthetic Aperture Radar (SAR) backscatter and (ii) single-pass shortwave interferometric SAR (InSAR) as indicators of above-ground biomass. Specifically, the effect on SAR backscatter of woody vegetation structure such as canopy cover, basal area, vegetation height and above-ground biomass is evaluated. Since vegetation height is often correlated to above-ground biomass, the effectiveness of vegetation height retrieval from InSAR is evaluated as an indicator of above-ground biomass. The study area, situated in Belize, is representative of Central American savannas. Radar data used are AIRSAR fully polarimetric L- and P-band SAR, and AIRSAR C-band InSAR, Intermap Technologies STAR-3i X-band InSAR, and Shuttle Radar Topography Mission (SRTM) C-band InSAR. The field data comprise accurately georeferenced three-dimensional measurements for 1,133 trees and shrubs and 75 palmetto clumps and thickets in a transect of 800 m x 60 m which spans the main savanna vegetation strata of the study area. An additional 2,464 ground points were observed. Results show that savanna woodlands present a challenge for radar remote sensing methods due to the sparse and heterogeneous nature of savanna woodlands. Long-wave SAR backscatter is dominated not only by high biomass areas, but also by areas of leafy palmetto which have low vegetative biomass. Retrieved woodland canopy heights from X- and C-band InSAR are indicative of the general patterns of tree height, although retrieved heights are underestimated. The amount of underestimation is variable across the different canopy conditions. Of these two methods, the shortwave InSAR data give a better indication of the spatial distribution of the above-ground biomass of the woody vegetation in the savannas than SAR backscatter. These results have implications for new and planned future global biomass estimation missions, such as ALOS PALSAR, ESA’s planned P-band BIOMASS and TanDEM-X. Without appropriate mediation, SAR backscatter methods might overestimate above-ground biomass of the woody vegetation of savannas while InSAR height retrieval methods might underestimate biomass estimates. Some possible mediating approaches are discussed