The photochemical reflectance index (PRI) is a remotely sensed vegetation index that detects a decrease in spectral reflectance at 531nm associated with xanthophyll cycle activity. PRI has been shown to track light use efficiency (LUE) in a number of plant species. PRI shows great promise in improving our ability to sense photosynthetic fluxes of CO2 remotely. However, it has not been tested in all environments, and its applicability is particularly uncertain for peatland environments dominated by mosses. This research investigates the ability of PRI to track LUE in a boreal forest and peatland, and examines the spectral signal associated with xanthophyll cycle activity in heterogeneous peatland plots. This research also investigates the relationship between PRI and leaf area index (LAI) over space and time in a peatland. We found most plots examined in the peatland site did not exhibit a spectral signal associated with xanthophyll cycle activity when exposed to a transition from dark conditions to full sunlight. This transition should lead to a de-epoxidation of xanthophylls in leaf tissues and a decrease in reflectance at 531nm. Plots that did show the decrease in reflectance at 531nm after this change in light conditions also displayed a decrease in PRI. This indicates that PRI effectively detects the 531nm signal as well as xanthophyll cycle activity and light stress in these plots. However, the variability in the strength of the spectral response to changing light conditions may confound the PRI signal in practice, and make it difficult to interpret results of airborne or satellite data. We also found PRI at the peatland site to be sensitive to and directly correlated with spatial variability in LAI, and negatively correlated with temporal variability in LAI. These characteristics may result in further difficulties applying PRI in peatlands. PRI and LUE were correlated at both the forest and peatland site, however at both sites the PRI signal saturated around 500 µmol m-2 s-1 of photosynthetically active radiation (PAR). This saturation effect has not, to our knowledge, been reported in other studies. Saturation of the PRI signal may limit our ability to determine carbon fluxes from airborne or satellite based remotely sensed data which is generally collected under clear skies during the brightest parts of the day when PAR exceeds 500 µmol m-2 s-1. / L'indice de réflectance photochimique (IRP) est un indice de végétation par télédétection qui détecte une diminution de la réflectance spectrale à 531nm associée à l'activité du cycle des xanthophylles. Il a été démontré que l'IRP est associé à l'efficacité d'utilisation de lumière (EUL) dans un certain nombre d'espèces végétales. L'IRP permet donc d'améliorer notre capacité à détecter les flux photosynthétiques du CO2 à distance. Cependant, il n'a pas été testé dans tous les environnements, et son applicabilité est particulièrement incertaine pour les écosystèmes tels que les tourbières dominées par les mousses. Cette étude examine la capacité des IRP de déceler l'EUL dans une forêt boréale et une tourbière, et examine le signal spectral associé à l'activité du cycle xanthophylle dans des parcelles hétérogènes d'une tourbière. Cette étude explore également la relation entre l'IRP et l'indice de surface foliaire (ISF) dans l'espace et le temps dans une tourbière.Nous avons trouvé que la plupart des parcelles examinées dans la tourbière ne présentent pas un signal spectral associé à l'activité du cycle de xanthophylle lorsqu'exposées à des conditions passant de l'obscurité à la lumière du soleil. Cette transition de luminosité devrait mener à la de-époxydation des xanthopylles dans les tissus foliaires et à une diminution de la réflectance à 531 nm. Les parcelles qui ont montré une telle diminution de la réflectance à 531 nm après les changements de luminosité ont aussi affiché une baisse de l'IRP. Ceci indique que l'IRP peut détecter le signal à 531 nm ainsi que l'activité du cycle de xanthophylle et le stress lumineux dans ces parcelles. Par contre, la variabilité de la réponse spectrale à l'évolution des conditions de lumière peuvent confondre le signal de l'IRP, ce qui rend difficile d'interpréter les résultats provenant de données aériennes ou satellitaires. Nous avons également constaté que l'IRP dans la tourbière est sensible et directement corrélé avec la variabilité spatiale de l'ISF, et négativement corrélé avec la variabilité temporelle de l'ISF. Ces caractéristiques peuvent entraîner des difficultés supplémentaires quant à l'application de l'IRP dans les tourbières.L'IRP et l'EUL étaient corrélés à la forêt et à la tourbière, mais il y avait saturation du signal de l'IRP autour de 500 µmol m-2 s-1 du rayonnement photosynthétiquement actif (RPA) aux deux sites. Cet effet de saturation n'a pas, à notre connaissance, été signalé dans d'autres études. La saturation du signal de l'IRP peut limiter notre capacité à déterminer les flux de carbone provenant de données aériennes ou satellitaires qui sont généralement recueillies sous un ciel clair pendant les parties les plus brillantes de la journée où la RPA dépasse 500 µmol m-2 s-1.

In this work, the various sources of errors in radar rain estimation are quantified and procedures are developed to reduce them. The few topics explored here are: the variability of drop size distributions (DSDs), radar calibration, and errors in polarimetric rain estimation. The findings resulting from this study include 1) a new filtering technique that reduces the spurious DSD sampling variability while maintaining the physical variability, 2) a generalization of previously suggested DSD models in terms of scaling concepts, 3) the experimental evidence of the physical interpretation of DSD evolution and of R-Z relationships, 4) the time scale dependence of the DSD variability and its implication for radar rain estimation, 5) the quantification of error sources in polarimetric rain estimation and its feasibility in operational environment, and 6) a complete set of stable radar calibration methods and their theoretical limits. All error statistics from this work will be used as a guideline in radar rain estimation.

The estimation or modeling of biophysical variables such as surface roughness, vegetation phytomass, and soil moisture in the Arctic is an important step towards understanding arctic energy fluxes, effects of changing climate, and hydrological patterns. This research uses Synthetic Aperture Radar (SAR) data, along with ancillary optical and environmental data, to create models that estimate these biophysical variables across different High Arctic landscapes, with the goal of applying the models across even larger areas. Field work was conducted at two High Arctic locations on Melville Island, Nunavut, Canada. At each location, surface roughness values were measured at a number of randomized plot locations using a pin meter. Soil moisture values were measured using a time domain reflectometry (TDR) instrument within six hours of multiple overpasses of the RADARSAT-2 SAR sensor. Surface roughness models were generated with multi-incidence angle and fully polarimetric SAR data, with resulting R2 values ranging between 0.39 and 0.66, and normalized root mean squared error (N_RMSE) values of 14% - 22%. The output from the final surface roughness model was used as an input to the soil moisture models. Vegetation phytomass was modeled with multi-angular SAR data, using a soil adjusted vegetation index (SAVI) derived from optical data across the study area as a measure of verification. The resulting model had a significant (p <0.05) relationship to the SAVI values, with an R2 of 0.60. This model was then compared to field-collected above-ground phytomass values, and a model was derived that related SAR data directly to phytomass. This model again showed a strong relationship, with an R2 value of 0.87. The final biophysical variable that was modeled, soil moisture, showed moderate agreement to field-measured soil moisture values (R2 = 0.46, N_RMSE = 0.15%), but much stronger relationships were found for relative moisture values at fine scales across the landscape. These models, when taken together, demonstrate that SAR data is capable of modeling biophysical variables across high latitude environments. These models will help address larger questions, such as how SAR can be used to better understand moisture and energy exchanges over regional areas in high arctic environments. / Thesis (Ph.D, Geography) -- Queen's University, 2014-02-03 16:52:26.856

Stephens Lake, Manitoba is an example of a peatland reservoir that has undergone physical changes related to mineral erosion and peatland disintegration processes since its initial impoundment. In this thesis I focused on the processes of peatland upheaval, transport, and disintegration as the primary drivers of dynamic change within the reservoir. The changes related to these processes are most frequent after initial reservoir impoundment and decline over time. They continue to occur over 35 years after initial flooding. I developed a remote sensing approach that employs both optical and microwave sensors for discriminating land (i.e. floating peatlands, forested land, and barren land) from open water within the reservoir. High spatial resolution visible and near-infrared (VNIR) optical data obtained from the QuickBird satellite, and synthetic aperture radar (SAR) microwave data obtained from the RADARSAT-1 satellite were implemented. The approach was facilitated with a Geographic Information System (GIS) based validation map for the extraction of optical and SAR pixel data. Each sensor’s extracted data set was first analyzed separately using univariate and multivariate statistical methods to determine the discriminant ability of each sensor. The initial analyses were followed by an integrated sensor approach; the development of an image classification model; and a change detection analysis. Results showed excellent (> 95%) classification accuracy using QuickBird satellite image data. Discrimination and classification of studied land cover classes using SAR image texture data resulted in lower overall classification accuracies (~ 60%). SAR data classification accuracy improved to > 90% when classifying only land and water, demonstrating SAR’s utility as a land and water mapping tool. An integrated sensor data approach showed no considerable improvement over the use of optical satellite image data alone. An image classification model was developed that could be used to map both detailed land cover classes and the land and water interface within the reservoir. Change detection analysis over a seven year period indicated that physical changes related to mineral erosion, peatland upheaval, transport, and disintegration, and operational water level variation continue to take place in the reservoir some 35 years after initial flooding. This thesis demonstrates the ability of optical and SAR satellite image remote sensing data sets to be used in an operational context for the routine discrimination of the land and water boundaries within a dynamic peatland reservoir. Future monitoring programs would benefit most from a complementary image acquisition program in which SAR images, known for their acquisition reliability under cloud cover, are acquired along with optical images given their ability to discriminate land cover classes in greater detail.

Bacterial biofilms are microbial communities that adhere to abiotic or biotic surfaces. Biofilm formation (BF) studies in E. coli have primarily concentrated on uropathogenic E. coli, commensal K-12 and enterohemorrhagic E. coli O157:H7. This does not include the vast diversity of environmental strains. Quorum sensing (QS) is a means by which bacteria can communication with one another through the production of signalling molecules. The autoinducer 2 (AI-2) QS system is utilized by E. coli and several other bacterial species for controlling gene expression. The role of AI-2 in E. coli BF varies among different strains. For example in the K-12 strain, AI-2 regulates motility, and thus can affect BF; whereas in O157:H7, AI-2 has a more metabolic role. Interestingly, in strain O157:H7, motility is controlled by a newly discovered QS system regulated by the autoinducer 3 (AI-3) molecule plus the mammalian hormones epinephrine (Epi) and norepinephrine (Ne). The purpose of this study was to investigate the ability of a panel of environmental E. coli strains to form biofilms and to determine whether QS is involved in the process. A new pathotype of E. coli, adherent invasive E. coli (AIEC) which is associated with Crohn’s disease was included in the investigation. Study 1 sought to determine whether BF under different media conditions correlated with the presence of genes involved in the AI-2 QS system or adhesin factors. Media conditions were the principal variable affecting the BF. Study 2 examined the role of the AI-2 and AI-3/Epi/Ne QS systems in motility and BF by the AIEC strain. It was discovered that the AI-3 system is involved in motility; whereas the AI-2 system had no effect on BF or motility. In Study 3, microarray gene expression analysis and invasion assays were performed using qseB or qseC mutants. These genes encode the two-component regulatory system recognizing AI-3 or its cognate, epinephrine. Our findings indicate that alternative pathways likely account for the BF observed for the qseB and qseC mutants. It was concluded that the AI-3/Epi/Ne QS system partially controls AIEC motility and the invasion of epithelial cells.

Wetlands are recognized as valuable landscapes for their contribution to biodiversity, ecosystem services and population livelihoods. However, current global wetland inventories do not spatially represent wetland extent at a spatial and temporal resolution appropriate for conservation and management purposes. Among the best existing global inventories, the Global Lakes & Wetlands Database (GLWD; Lehner & Döll, 2004) is a static database assembled from various existing data sources that unfortunately suffers from the inconsistency among its data sources. Another, the Global Surface Water Extent Dataset (GSWED; Prigent et al. 2007; Papa et al. 2010) produced from a multi-satellite method is capable of monthly measurements but possesses a coarse spatial resolution incapable of discriminating distinct surface water bodies. Faced with the limitations of current global inventories, a new methodological approach is required to provide the improved wetland inventory needed by the research and conservation communities.This thesis investigates a methodology capable of producing a high-resolution (~ 500 m) surface water extent map by spatially downscaling the coarse resolution (~27 km) inundated area estimates of GSWED. The methodology inspired by Bwangoy et al. (2010) has a pragmatic and straight-forward design to ensure and ease its global application. The work of this thesis consists of an initial implementation and validation of the methodology across the African continent. The downscaling approach relies on the topographic and hydrographic information from the globally available HydroSHEDS data (Lehner et al., 2008) to distribute inundated area at the finer resolution to the most topographically inundation prone areas. Thirteen hydro-topographic variables were computed from HydroSHEDS and then consolidated into a single inundation probability map with the use of decision tree learners. The decision trees were trained on regional inundation maps and subsequently employed to generate a topographic probability of inundation map at high-resolution for the entire continent. The probability map is turned into an inundated/non-inundated map by splitting the probability distribution into two (inundated/non-inundated) with a defined threshold value. A threshold value is chosen for each GSWED cell to produce an inundation map replicating the inundated area estimates of GSWED within the cell at the finer resolution. To represent the maximum wetland extent at different timescales, two sets of inundated areas estimates were downscaled as high-resolution inundation maps with this MWT downscaling procedure: 1) the mean annual maximum (MAMax) estimates were calculated for each cell from the monthly estimates of GSWED between 1993 and 2004; 2) the fusion maximum (MaxFusion) was generated from a fusion of the time-series maximum (TSMax) also calculated from GSWED, with the wetland area from GLWD. The MaxFusion estimates were produced to correct some data gaps of GSWED, as well as to offer a more complete and reliable maximum wetland extent map. The MAMax and MaxFusion estimates respectively totalled 1339 and 2779 thousand km2 of wetland area across the continent; higher than most previous estimates for Africa.Validation of the spatial distribution of inundation at the finer resolution exhibited high levels of agreement against reference regional maps (Overall Accuracy ~ 92%; KIA ~ 80%). Over selected wetland study sites, comparisons of the MaxFusion downscaled map with the global land cover GLC2000 (Mayaux et al. 2004) and wetland database GLWD indicated that the downscaled map possessed slightly lower but more consistent agreement with GLC2000 than GLWD did. Regardless, the level accuracy of the tested methodology is considered satisfactory to pursue production of a first version global inundation map. Possible follow-up applications making use of the downscaled inundation maps such as a global hydro-geomorphic wetland classification. / Bien que l'importance des milieux humides pour la biodiversité et les services écosystémiques soit reconnue, les bases de données actuellement disponibles ne sont pas en mesure de décrire globalement les charactéristiques biophysiques des milieux humides de façon utile à des fins de gestion et de conservation. Parmi les inventaires globaux de milieux humides disponibles, la Global Lake & Wetland Database (GLWD) (Lehner & Döll, 2004), , est une représentation statique constituée de plusieurs sources qui est cependant spatiallement inconsistente. Un autre inventaire, le Global Surface Water Extent Dataset (GSWED) (Prigent et al. 2007; Papa et al. 2010) produite à partir d'une méthode multi-satellitaire, possède une faible résolution spatiale incapable de différencier des plans d'eau distincts. Compte tenue des limites des actuels inventaires, une nouvelle approche est nécessaire pour générer le nouvel et amélioré inventaire que demande diverses communautés de chercheurs.Cette thèse examine la possibilité de produire une représentation spatiale d'inondation et de milieux humides globale à haute résolution (~ 500 m) à partir d'une réduction d'échelle des estimés surfaces inondées de faible résolution (~27 km) du GSWED. La méthode inspirée par Bwangoy et al. (2010) a été développée de façon pragmatique et simple afin d'assurer son application globale sans heurt. Cette thèse est une application initiale de la méthodologie à des fins de validations sur le continent africain. La méthode de réduction de résolution repose sur de l'information topographiques et hydrographiques globales provenant des données HydroSHEDS (Lehner et al. 2008) pour distribuer la surface inondée de GSWED à la plus fine résolution aux endroits les plus prompt à l'inondation. Treize variables hydro-topographiques furent calculées à partir d'HydroSHEDS et ensuite consolidée dans une probabilité d'inondation calculée pour chaque pixel de haute résolution d'HydorSHED,S grâce à un arbre de décision. L'arbre de décision fut entraîné et validé avec des images satellitaires régionales d'inondation et fut utilisé par la suite pour générer des probabilités d'inondation sur l'ensemble du continent. La carte de probabilités d'inondation résultante est ensuite transformée en carte d'inondation en utilisant une valeur seuil divisant la distribution de probabilités en deux. Une valeur seuil est choisie pour la surface de chaque cellule de GSWED pour répliquer la surface inondée de GSWED.En tant qu'estimé de surface provenant de GSWED, les valeurs mensuelles entre 1993 et 2004 furent agrégée pour produire des estimés du maximum annuel moyen (MAMax) ainsi que le maximum historique (TSMax). Pour produire des estimées fiables représentant la surface maximale inondée et pour corriger pour certaines des lacunes des estimés de GSWED, les estimés du TSMax furent fusionnés à celles de GLWD, générant les estimées maximales de fusion (MaxFusion). La surface totale estimée pour l'ensemble du continent africain pour MAMax et MaxFusion est estimées respectivement à 1339 et 2779 milliers de km2, plus élevée que la plupart des estimés précédents.La validation de la distribution spatiale de l'inondation à la plus fine résolution a démontré un bon accord (Précision globale ~ 92%; KIA ~ 80%) lorsque comparée à des cartes régionales d'inondations ou de milieux humides. De plus, la comparaison du résultat cartographique avec le GLC2000 et le GLWD sur quelques sites particuliers a indiqué une concordance avec GLC2000 consistante, malgré qu'inférieure à celle de GLWD. Malgré les défauts du produit, le niveau de précision de la méthodologie testée peut être considérée suffisant pour poursuivre son développement et son application globale. D'autre projets de recherches découlant de celui-ci et faisant usage d'une carte d'inondation global à haute-résolution peuvent avoir faire à un classification hydro-géomorphique de milieux humides.

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<p> Three-dimensional mapping and modeling can contribute to knowledge about the real world. Techniques are largely driven by available technology and typically involve expensive equipment and expert skill. Recent advances have led to low-cost remotely sensed data collection and generation of 3D terrain models using Uninhabited Aerial Vehicles (UAV) and Structure from Motion (SfM) processing software. This research presents a low-cost alternative to 3D mapping by pairing UAV collection methods with three SfM processing techniques. Surface models are generated from the same image set captured from a low-cost UAV coupled with a digital camera. Accuracy of resulting models identifies strengths and weaknesses of each technique. Analysis of different slope ranges investigates the divide at which surfaces generated become less reliable. This research provides a deeper understanding of the strengths and limitations of emerging technologies used together in a fresh approach to photogrammetry.</p>