Forest fires have an enormous impact on biotic and abiotic variables that control runoff and soil properties in watersheds. Because wildfires do not have a uniform effect on the burned area, significant variability occurs between areas of different burn severity and likely elicits different hydrologic responses within watersheds. Much of the control on this hydrologic response stems from the variability of soil between burned and unburned watersheds. Establishing a linkage between soil infiltration and burn severity may therefore, offer insight into the likelihood of elevated levels of runoff and the likelihood of floods. Although previous studies have sought to establish a quantitative relationship between runoff and burn severity, this relation has not been evaluated with respect to soil moisture and infiltration and varying degrees of burn severity. The Loretta-Linda Basin presents a unique opportunity to compare areas with different burn severities (with the right fork of the drainage experiencing a much higher burn severity than the left), while eliminating most other variables that may occur with greater spatial variability such as elevation, temperature, precipitation, underlying geology, and soil type. Rainfall, soil moisture, runoff, and infiltration data collected over a two-month period were used to evaluate the relationship between burn severity, runoff, and infiltration for the Loretta-Linda basin as a whole as well as for the individual forks of the basin. The impact of varying burn severity on the two sub drainages was further investigated by creating a dynamic simulation model in TopoFlow®. Comparative analysis between the two forks did not show a dramatic difference in the runoff and infiltration relationship between the two burn severities. Variability of field conditions, the presence of parameters affecting runoff not accounted for, and the limitations of point measurements, are reflected by the data analysis and lack of a strong correlation between burn severity, infiltration, and runoff. The use of spatial hydrologic modeling allowed for the investigation of the relative importance of the infiltration parameters as well as the impact of Manning’s n on the response of the basin to rainfall. The modeling results indicate a strong correlation between high burn severity, low infiltration capacity, and elevated discharge volumes.

This study compared the effects of fire severity and salvage logging on early successional vegetation in the mixedwood boreal forest upland of Saskatchewan. The effects of salvage logging on post-fire forest stands are poorly understood. Few studies have investigated the short-term effects of salvage logging on the regeneration of boreal plant species or the long-term impact on overall forest composition and diversity. This study examines salvage logged and wildfire leave stands across three burn severity classes (no burn, low/moderate burn, and high burn) over two time periods (1 year post-fire and 10 years post-fire). The results indicate that salvage logging has a significant impact on the early regeneration of burned mixedwood boreal plant communities with the effect still evident in forest stands ten years post-fire. Salvage logging has long-lasting residual effects on boreal forest plant community development. Salvage logging one year post-fire reduced the number, diversity, and abundance of species within each of the burn severities, creating a less abundant and simplified plant community. It was also shown that salvage logging one year post-fire tended to create more homogenous plant communities similar to those communities typical of areas of moderate burn severity, constraining the effects of burn severity and decreasing the range of the vegetation communities. These findings are less pronounced, but still evident, within salvage logged stands ten years post-fire as three regrowth cover types have developed, characterised by no disturbance, moderate disturbance either by fire or salvage logging, and severe disturbance. The convergence of plant community characteristics between burn severity classes across logging treatments suggests that the effects of salvage logging do not have long lasting effects within areas of high burn severity.

This study compared the effects of fire severity and salvage logging on early successional vegetation in the mixedwood boreal forest upland of Saskatchewan. The effects of salvage logging on post-fire forest stands are poorly understood. Few studies have investigated the short-term effects of salvage logging on the regeneration of boreal plant species or the long-term impact on overall forest composition and diversity. This study examines salvage logged and wildfire leave stands across three burn severity classes (no burn, low/moderate burn, and high burn) over two time periods (1 year post-fire and 10 years post-fire). The results indicate that salvage logging has a significant impact on the early regeneration of burned mixedwood boreal plant communities with the effect still evident in forest stands ten years post-fire. Salvage logging has long-lasting residual effects on boreal forest plant community development. Salvage logging one year post-fire reduced the number, diversity, and abundance of species within each of the burn severities, creating a less abundant and simplified plant community. It was also shown that salvage logging one year post-fire tended to create more homogenous plant communities similar to those communities typical of areas of moderate burn severity, constraining the effects of burn severity and decreasing the range of the vegetation communities. These findings are less pronounced, but still evident, within salvage logged stands ten years post-fire as three regrowth cover types have developed, characterised by no disturbance, moderate disturbance either by fire or salvage logging, and severe disturbance. The convergence of plant community characteristics between burn severity classes across logging treatments suggests that the effects of salvage logging do not have long lasting effects within areas of high burn severity.

Portugal is one of the Mediterranean countries that besides its natural condition to occur forest fires, has had an increase of forest fires during the last decades and has a consequence the increase of the burned surface and the costs associated, economic, social and environmental. This study case took place in Serra da Freita, a mountain region in the north of Portugal in the Aveiro District. The aim of this case study was to establish a relation between forest fires, erosion and social consequences for the region. For this purpose, a mixed approach was used with Remote sensing to acquire burn severity (dNBR) by comparing the areas before and after forest fires, soil analyses, and with a questionnaire to the local community to comprehend how they are affected. The results obtained permits to understand that not only the forest fires have a direct impact on the soil erosion, but also affect the local community by promoting the abandonment of the area.

A new mathematical model has been developed along with a new parameter estimation routine using surface temperature and heat flux measurements to estimate blood perfusion and thermal resistance in living tissue. Dynamic thermal measurements collected at the surface of the sensor before and after imposing a dynamic thermal cooling event are used with the model to estimate the blood perfusion, thermal resistance and core temperature. The Green\'s function based analytical solution does not require calculation of the whole tissue temperature distribution, which was not the case for the previous models. The result from the new model was proved to have better and more consistent results than previous models. The new model was validated to solve one of the unsolved biomedical problems which is the ability of detecting burn severity. The method was tested with a phantom perfusion system. The results matched known blood perfusion and thermal resistance values. The method was also tested with burns on animal models. Inflammation effects associated with the burns were studied using a newly developed term called the Burn Factor. This correlated with the severity of imposed burns. This work consists of three journal papers. The first paper introduces the mathematical model and its validation with finite-difference solutions. The second paper validates the physical aspects of the usage of the model with thermal measurement in detecting simulated burned layers and the associated perfusion. The third paper demonstrates the ability of the model to use thermal measurements to detect different burn severity of an animal model and to study the healing process. / Ph. D.

Human-caused forest fires have increased in magnitude and frequency, affecting global vegetation and requiring a re-evaluation of fire regimes. Changing fire regimes have led to reduced burned areas in fire- dependent ecosystems and increased areas in fire-independent ecosystems, resulting in changes in land cover and posing a threat to native plant communities. This study focuses on monitoring vegetation recovery after fires in California, USA, using the Enhanced Vegetation Index (EVI) from MODIS time series. The goal is to determine the full recovery time and half recovery time (HRT) after forest fires in year 2017 and analyze the influence of burn severity on three land cover classes in two different climate zones in California.Analyzes show that the "Closed Forest" land cover type exhibits the longest recovery period, followed by the "Open Forest" type and “Herbaceous/Shrub” type in both climate zones but no general connection between recovery time and climate zone was observed. It is found that burn severity degree affects HRT but not the full recovery time in both Mediterranean and Semi-arid climate zones. The study mainly highlights the variations in forest fire recovery patterns between land cover types, as well as differences observed between climate zones.

This study focuses on soil hydrological parameters that are expected to be related to burn severity in forests; infiltration rate, soil moisture, grain size distribution and carbon content along a burn severity gradient in Västmanland Sweden, where a major fire occurred in 2014. Hälleskogsbrännan was divided into two burn severities: a moderate severity and a high severity, and a control area. Ten soil samples were taken for laboratory analyses at each severity level. Soil moisture and infiltration rate was measured in situ. Infiltration rates and soil moisture were highest in the most severely affected site, whereas fire effects on soil texture were insignificant. Soil organic carbon content was highest at the low fire severity site, followed by control and high severity fire sites. Inorganic carbon content followed the opposite trend. These results had clear trends but were insignificant, this call for more comprehensive sampling to separate possible confounding site effects.

Die in den letzten Jahrzehnten aufgenommenen Satellitenbilder zur Erdbeobachtung bieten eine ideale Grundlage für eine genaue Langzeitüberwachung und Kartierung der Erdoberfläche und Atmosphäre. Unterschiedliche Sensoreigenschaften verhindern jedoch oft eine synergetische Nutzung. Daher besteht ein dringender Bedarf heterogene Multisensordaten zu kombinieren und als geometrisch und spektral harmonisierte Zeitreihen nutzbar zu machen. Diese Dissertation liefert einen vorwiegend methodischen Beitrag und stellt zwei neu entwickelte Open-Source-Algorithmen zur Sensorfusion vor, die gründlich evaluiert, getestet und validiert werden. AROSICS, ein neuer Algorithmus zur Co-Registrierung und geometrischen Harmonisierung von Multisensor-Daten, ermöglicht eine robuste und automatische Erkennung und Korrektur von Lageverschiebungen und richtet die Daten an einem gemeinsamen Koordinatengitter aus. Der zweite Algorithmus, SpecHomo, wurde entwickelt, um unterschiedliche spektrale Sensorcharakteristika zu vereinheitlichen. Auf Basis von materialspezifischen Regressoren für verschiedene Landbedeckungsklassen ermöglicht er nicht nur höhere Transformationsgenauigkeiten, sondern auch die Abschätzung einseitig fehlender Spektralbänder. Darauf aufbauend wurde in einer dritten Studie untersucht, inwieweit sich die Abschätzung von Brandschäden aus Landsat mittels synthetischer Red-Edge-Bänder und der Verwendung dichter Zeitreihen, ermöglicht durch Sensorfusion, verbessern lässt. Die Ergebnisse zeigen die Effektivität der entwickelten Algorithmen zur Verringerung von Inkonsistenzen bei Multisensor- und Multitemporaldaten sowie den Mehrwert einer geometrischen und spektralen Harmonisierung für nachfolgende Produkte. Synthetische Red-Edge-Bänder erwiesen sich als wertvoll bei der Abschätzung vegetationsbezogener Parameter wie z. B. Brandschweregraden. Zudem zeigt die Arbeit das große Potenzial zur genaueren Überwachung und Kartierung von sich schnell entwickelnden Umweltprozessen, das sich aus einer Sensorfusion ergibt. / Earth observation satellite data acquired in recent years and decades provide an ideal data basis for accurate long-term monitoring and mapping of the Earth's surface and atmosphere. However, the vast diversity of different sensor characteristics often prevents synergetic use. Hence, there is an urgent need to combine heterogeneous multi-sensor data to generate geometrically and spectrally harmonized time series of analysis-ready satellite data. This dissertation provides a mainly methodical contribution by presenting two newly developed, open-source algorithms for sensor fusion, which are both thoroughly evaluated as well as tested and validated in practical applications. AROSICS, a novel algorithm for multi-sensor image co-registration and geometric harmonization, provides a robust and automated detection and correction of positional shifts and aligns the data to a common coordinate grid. The second algorithm, SpecHomo, was developed to unify differing spectral sensor characteristics. It relies on separate material-specific regressors for different land cover classes enabling higher transformation accuracies and the estimation of unilaterally missing spectral bands. Based on these algorithms, a third study investigated the added value of synthesized red edge bands and the use of dense time series, enabled by sensor fusion, for the estimation of burn severity and mapping of fire damage from Landsat. The results illustrate the effectiveness of the developed algorithms to reduce multi-sensor, multi-temporal data inconsistencies and demonstrate the added value of geometric and spectral harmonization for subsequent products. Synthesized red edge information has proven valuable when retrieving vegetation-related parameters such as burn severity. Moreover, using sensor fusion for combining multi-sensor time series was shown to offer great potential for more accurate monitoring and mapping of quickly evolving environmental processes.