Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-08-30T13:43:17Z No. of bitstreams: 1 ANA PAULA NUNES DA SILVA - TESE (PPGMet) 2016.pdf: 25525790 bytes, checksum: 973f4462b19d6c6616cfec5845906a37 (MD5) / Made available in DSpace on 2018-08-30T13:43:17Z (GMT). No. of bitstreams: 1 ANA PAULA NUNES DA SILVA - TESE (PPGMet) 2016.pdf: 25525790 bytes, checksum: 973f4462b19d6c6616cfec5845906a37 (MD5) Previous issue date: 2016-05-06 / CNPq / O objetivo deste trabalho foi verificar a ocorrência de ilha de calor urbana (ICU) e sua influência no microclima na Região Metropolitana de Macapá (RMM), situada no Nordeste da Amazônia Legal, já que esta região vem apresentando um rápido processo de urbanização. Este processo de crescimento urbano provoca mudanças na cobertura e uso do solo, que podem modificar diretamente o balanço de energia em superfície gerando modificações na atmosfera que podem variar da escala local até a regional. Para verificar o crescimento urbano da RMM utilizou-se imagens do LANDSAT TM e OLI/TIRS de cinco diferentes épocas e através da classificação supervisionada MAXVER, verificou-se a expansão da classe área construída entre 1986 e 2015, classe que subentende a malha urbana. Uma análise climática com dados de precipitação e temperatura, permitiu verificar que possivelmente a variabilidade da temperatura e precipitação encontrada deve estar mais associado com eventos como El Niño do que com mudanças climáticas, entretanto, as tendências de aquecimento observadas podem estar relacionadas com o crescimento urbano. Para entender os impactos do crescimento urbano na modificação do microclima da RMM analisou-se índices de extremos climáticos de duas estações meteorológicas: uma situada no perímetro urbano e outra numa área rural da RMM. Verificou-se que as maiores mudanças térmicas ocorreram na área mais afastada da cidade, fato devido às mudanças de uso do solo na região periférica da RMM, enquanto que os índices relacionados a precipitação foram mais significativos na área urbana. Foram instalados termo-higrômetros em quatro pontos da RMM em áreas suburbanas e rurais para analisar os índices ICU, verificou-se que o índice sazonal de ICU foi maior (menor) nos meses de março a abril (outubro a dezembro), enquanto o índice horário obteve diferentes resultados de acordo com a época do ano: no mês chuvoso (seco) foi mais intenso no início da noite (do dia) com valor para a RMM atingiram valores máximos de 6°C (4,9°C). Na análise da Ilha de Calor Urbana em Superfície (ICUS) utilizaram-se cinco imagens de satélite e se verificou que em todas as imagens houve a comprovação de ICUS com núcleos nos centros da malhas urbanas das duas cidades da RMM e num distrito situado entre os dois centros urbanos analisados. Verificando os índices de conforto térmico gerados pela formação de ICU na RMM, comprovou-se que a região central da RMM apresenta os maiores valores e, que os índices de calor e de temperatura efetiva apresentaram boa relação com a percepção térmica da população de RMM, entrando o índice de conforto humano não se mostrou aplicabilidade na região em estudo. / The goal of the this Doctoral Thesis is to verify the occurrence of the Urban Heat Island (UHI) in the Macapá Metropolitan Area (RMM) Micro climate, which is placed in the Legal Amazon Northeast, due to the fact of the fast urbanization of the area. The development of the urban areas causes changes on the cover and use of the soil which could have a direct effect on the surface energy balance that may result in atmospheric modification in a local, or even regional,scale. In order to verify the RMM urban development, were used images from LANDSAT TM and OLI/TIRS of five different periods. Therefore, through the supervised classification MAXVER, it was possible to verify a expansion of the build-up area, the class of soil that covers the urban sheet, between 1986 and 2015. A climatic Analysis containing precipitation and temperature data showed that, probably, the variation of precipitation and temperature which appeared in the numbers presented are more likely to be associated with specific events, e.g. El Niño, than with the climatic changes. How ever, the growing heat trend observed during the research may be related to the urban development. In order to understand the impact of the development of the urban areas in the modification of the RMM micro climate, extreme climatic levels from two meteorologic bases were adopted: one of the those was placed within the urban perimeter; while the other was located in the RMM rural area. The data collected showed the biggest thermal changes took place further from the city, due to changes in the use of the soil in the isolated region of the RMM. About the levels related to precipitation, they were more significant in the urban areas. Term-hygrometers were installed in four different spots of the RMM, in suburban and rural areas, with the objective of analyzing the UHI levels. It was possible to verify that the season UHI levels were bigger (smaller) between March and April (October and December). The schedule levels showed different results along the year: during the rainy month (dry) it was more intense in the beginning of night (day) reaching maximum levels, in the RMM, of 6.0ºC (4.9ºC). For the analysis of the Urban Heat Island on Surface (SUHI) 5 satellite images were used and it was possible to verify in all of them the existence of ICUS with their cores located in the center of the urban sheets of the two cities that form the RMM and in a district placed between them. Trough the verification of the heat levels generated by the UHI formation in the RMM, it was possible to probe that the central area of the RMM presents the biggest values, and the IC and ITE levels are well connected to the RMM population's thermal perception. Considering the ICH it was evident the applicability of this Thesis in the area of the research.

A geada é um fenômeno meteorológico adverso que causa perdas severas ao setor agrícola, em especial no Sul do Brasil. A baixa distribuição espacial da rede de estações meteorológicas dificulta o monitoramento e a previsão do fenômeno. O propósito principal desta tese foi o desenvolvimento de um modelo matemático para quantificar de forma direta e simples a probabilidade do risco de ocorrência de geada tendo como base em dados de fácil obtenção como altitude, latitude, continentalidade e temperatura do ar. O modelo criado, denominado Risco Geral de Geada (RGG), foi idealizado a partir de dois riscos básicos, o risco geográfico e o risco advindo da temperatura mínima do local, ambos com o mesma contribuição para a ocorrência de geada. O risco geográfico de geada (RGeo) foi obtido a partir do somatório dos riscos atribuídos aos fatores geográficos altitude, latitude e continentalidade. Cada um destes fatores contribui de forma diferente para a formação da geada e suas contribuições foram estimadas a partir de um modelo de regressão linear múltipla para a estimativa da temperatura mínima do ar climatológica de inverno no Rio Grande do Sul. No risco de geada associado à temperatura mínima (RTmín) foi feita a atribuição de riscos em um intervalo de temperatura entre 0 e 6°C. O modelo final obtido, válido apenas para o Rio Grande do Sul, foi testado com dados coletados em estações meteorológicas de superfície da mesorregião do Sudeste Rio-grandense, localizadas em Encruzilhada do Sul, Rio Grande e Santa Vitória do Palmar. Dados de temperatura mínima do ar nos meses de junho, julho e agosto, coletados entre os anos de 1961 e 2015, comprovaram a utilidade do modelo RGG para a definição da probabilidade do risco de ocorrência de geada, mesmo diante de incertezas atribuídas a outros fatores não descritos no modelo. Na região de teste também foi avaliada a qualidade de dados orbitais de temperatura da superfície terrestre (TST), obtidos do produto MDY11A1 da passagem noturna do sensor MODIS/AQUA, na detecção de temperaturas baixas relacionadas com a ocorrência de geada. A frequência de dias com TST inferiores a 3°C mostrou coerência tanto com os dados observados em estação meteorológica, quanto com o risco determinado pelo RGG. A coerência entre os resultados obtidos do modelo RGG e os dados reais observados em superfície e obtidos por satélite torna o modelo útil na descrição da probabilidade do risco de ocorrência de geada sobre o Rio Grande do Sul. / Frost is an adverse meteorological phenomenon that causes severe losses to the agricultural sector, especially in Southern Brazil. Low spatial distribution of the network of meteorological stations hinders monitoring and forecast phenomenon. The main purpose of this thesis was to develop a mathematical model to measure directly and easily the probability of the risk of frost based on readily available data such as altitude, latitude, continentality and air temperature. The model, called Frost General Risk (RGG), was designed from two basic risk, geographic risk and risk arising out of the local minimum temperature, both with the same contribution to the occurrence of frost. The geographical risk of frost (RGeo) was obtained from the sum of the risks attributed to geographical factors altitude, latitude and continental influence. Each of these factors contributes differently to the formation of frost and their contributions were estimated from a multiple linear regression model to estimate the minimum air temperature winter climatological in Rio Grande do Sul. In the frost risk associated with minimum temperature (RTmín) assigning risk was taken in a temperature range between 0 and 6° C. The final model obtained, valid only for the Rio Grande do Sul, has been tested with data collected from weather stations surface of the middle region of Sudeste Rio-grandense, located in Encruzilhada do Sul, Rio Grande and Santa Vitória do Palmar. Minimum temperature, the air in the months of june, july and august, collected between 1961 and 2015, have proved the usefulness of the model RGG to define the probability of the risk of frost, even in the face of uncertainty attributed to other factors not described in the model. In the test region was also evaluated the quality of satellite data of the land surface temperature (LST), the product obtained MDY11A1 the night passage of MODIS / AQUA sensor to detect low temperatures related to the occurrence of frost. The frequency of days with LST below 3° C showed much consistency with the observed data in weather station, and with the particular risk for the RGG. Consistency between the results obtained from the RGG model and the actual data observed in surface and from satellites makes the model useful in describing the probability of the risk of frost on the Rio Grande do Sul.

A geada é um fenômeno meteorológico adverso que causa perdas severas ao setor agrícola, em especial no Sul do Brasil. A baixa distribuição espacial da rede de estações meteorológicas dificulta o monitoramento e a previsão do fenômeno. O propósito principal desta tese foi o desenvolvimento de um modelo matemático para quantificar de forma direta e simples a probabilidade do risco de ocorrência de geada tendo como base em dados de fácil obtenção como altitude, latitude, continentalidade e temperatura do ar. O modelo criado, denominado Risco Geral de Geada (RGG), foi idealizado a partir de dois riscos básicos, o risco geográfico e o risco advindo da temperatura mínima do local, ambos com o mesma contribuição para a ocorrência de geada. O risco geográfico de geada (RGeo) foi obtido a partir do somatório dos riscos atribuídos aos fatores geográficos altitude, latitude e continentalidade. Cada um destes fatores contribui de forma diferente para a formação da geada e suas contribuições foram estimadas a partir de um modelo de regressão linear múltipla para a estimativa da temperatura mínima do ar climatológica de inverno no Rio Grande do Sul. No risco de geada associado à temperatura mínima (RTmín) foi feita a atribuição de riscos em um intervalo de temperatura entre 0 e 6°C. O modelo final obtido, válido apenas para o Rio Grande do Sul, foi testado com dados coletados em estações meteorológicas de superfície da mesorregião do Sudeste Rio-grandense, localizadas em Encruzilhada do Sul, Rio Grande e Santa Vitória do Palmar. Dados de temperatura mínima do ar nos meses de junho, julho e agosto, coletados entre os anos de 1961 e 2015, comprovaram a utilidade do modelo RGG para a definição da probabilidade do risco de ocorrência de geada, mesmo diante de incertezas atribuídas a outros fatores não descritos no modelo. Na região de teste também foi avaliada a qualidade de dados orbitais de temperatura da superfície terrestre (TST), obtidos do produto MDY11A1 da passagem noturna do sensor MODIS/AQUA, na detecção de temperaturas baixas relacionadas com a ocorrência de geada. A frequência de dias com TST inferiores a 3°C mostrou coerência tanto com os dados observados em estação meteorológica, quanto com o risco determinado pelo RGG. A coerência entre os resultados obtidos do modelo RGG e os dados reais observados em superfície e obtidos por satélite torna o modelo útil na descrição da probabilidade do risco de ocorrência de geada sobre o Rio Grande do Sul. / Frost is an adverse meteorological phenomenon that causes severe losses to the agricultural sector, especially in Southern Brazil. Low spatial distribution of the network of meteorological stations hinders monitoring and forecast phenomenon. The main purpose of this thesis was to develop a mathematical model to measure directly and easily the probability of the risk of frost based on readily available data such as altitude, latitude, continentality and air temperature. The model, called Frost General Risk (RGG), was designed from two basic risk, geographic risk and risk arising out of the local minimum temperature, both with the same contribution to the occurrence of frost. The geographical risk of frost (RGeo) was obtained from the sum of the risks attributed to geographical factors altitude, latitude and continental influence. Each of these factors contributes differently to the formation of frost and their contributions were estimated from a multiple linear regression model to estimate the minimum air temperature winter climatological in Rio Grande do Sul. In the frost risk associated with minimum temperature (RTmín) assigning risk was taken in a temperature range between 0 and 6° C. The final model obtained, valid only for the Rio Grande do Sul, has been tested with data collected from weather stations surface of the middle region of Sudeste Rio-grandense, located in Encruzilhada do Sul, Rio Grande and Santa Vitória do Palmar. Minimum temperature, the air in the months of june, july and august, collected between 1961 and 2015, have proved the usefulness of the model RGG to define the probability of the risk of frost, even in the face of uncertainty attributed to other factors not described in the model. In the test region was also evaluated the quality of satellite data of the land surface temperature (LST), the product obtained MDY11A1 the night passage of MODIS / AQUA sensor to detect low temperatures related to the occurrence of frost. The frequency of days with LST below 3° C showed much consistency with the observed data in weather station, and with the particular risk for the RGG. Consistency between the results obtained from the RGG model and the actual data observed in surface and from satellites makes the model useful in describing the probability of the risk of frost on the Rio Grande do Sul.

A geada é um fenômeno meteorológico adverso que causa perdas severas ao setor agrícola, em especial no Sul do Brasil. A baixa distribuição espacial da rede de estações meteorológicas dificulta o monitoramento e a previsão do fenômeno. O propósito principal desta tese foi o desenvolvimento de um modelo matemático para quantificar de forma direta e simples a probabilidade do risco de ocorrência de geada tendo como base em dados de fácil obtenção como altitude, latitude, continentalidade e temperatura do ar. O modelo criado, denominado Risco Geral de Geada (RGG), foi idealizado a partir de dois riscos básicos, o risco geográfico e o risco advindo da temperatura mínima do local, ambos com o mesma contribuição para a ocorrência de geada. O risco geográfico de geada (RGeo) foi obtido a partir do somatório dos riscos atribuídos aos fatores geográficos altitude, latitude e continentalidade. Cada um destes fatores contribui de forma diferente para a formação da geada e suas contribuições foram estimadas a partir de um modelo de regressão linear múltipla para a estimativa da temperatura mínima do ar climatológica de inverno no Rio Grande do Sul. No risco de geada associado à temperatura mínima (RTmín) foi feita a atribuição de riscos em um intervalo de temperatura entre 0 e 6°C. O modelo final obtido, válido apenas para o Rio Grande do Sul, foi testado com dados coletados em estações meteorológicas de superfície da mesorregião do Sudeste Rio-grandense, localizadas em Encruzilhada do Sul, Rio Grande e Santa Vitória do Palmar. Dados de temperatura mínima do ar nos meses de junho, julho e agosto, coletados entre os anos de 1961 e 2015, comprovaram a utilidade do modelo RGG para a definição da probabilidade do risco de ocorrência de geada, mesmo diante de incertezas atribuídas a outros fatores não descritos no modelo. Na região de teste também foi avaliada a qualidade de dados orbitais de temperatura da superfície terrestre (TST), obtidos do produto MDY11A1 da passagem noturna do sensor MODIS/AQUA, na detecção de temperaturas baixas relacionadas com a ocorrência de geada. A frequência de dias com TST inferiores a 3°C mostrou coerência tanto com os dados observados em estação meteorológica, quanto com o risco determinado pelo RGG. A coerência entre os resultados obtidos do modelo RGG e os dados reais observados em superfície e obtidos por satélite torna o modelo útil na descrição da probabilidade do risco de ocorrência de geada sobre o Rio Grande do Sul. / Frost is an adverse meteorological phenomenon that causes severe losses to the agricultural sector, especially in Southern Brazil. Low spatial distribution of the network of meteorological stations hinders monitoring and forecast phenomenon. The main purpose of this thesis was to develop a mathematical model to measure directly and easily the probability of the risk of frost based on readily available data such as altitude, latitude, continentality and air temperature. The model, called Frost General Risk (RGG), was designed from two basic risk, geographic risk and risk arising out of the local minimum temperature, both with the same contribution to the occurrence of frost. The geographical risk of frost (RGeo) was obtained from the sum of the risks attributed to geographical factors altitude, latitude and continental influence. Each of these factors contributes differently to the formation of frost and their contributions were estimated from a multiple linear regression model to estimate the minimum air temperature winter climatological in Rio Grande do Sul. In the frost risk associated with minimum temperature (RTmín) assigning risk was taken in a temperature range between 0 and 6° C. The final model obtained, valid only for the Rio Grande do Sul, has been tested with data collected from weather stations surface of the middle region of Sudeste Rio-grandense, located in Encruzilhada do Sul, Rio Grande and Santa Vitória do Palmar. Minimum temperature, the air in the months of june, july and august, collected between 1961 and 2015, have proved the usefulness of the model RGG to define the probability of the risk of frost, even in the face of uncertainty attributed to other factors not described in the model. In the test region was also evaluated the quality of satellite data of the land surface temperature (LST), the product obtained MDY11A1 the night passage of MODIS / AQUA sensor to detect low temperatures related to the occurrence of frost. The frequency of days with LST below 3° C showed much consistency with the observed data in weather station, and with the particular risk for the RGG. Consistency between the results obtained from the RGG model and the actual data observed in surface and from satellites makes the model useful in describing the probability of the risk of frost on the Rio Grande do Sul.

Vegetation controls the exchange of heat, mass and momentum between the land surface and the atmosphere, and is also the primary producer that sustains life on Earth. We combine theoretical analyses, satellite and in-situ observations, and Earth system model simulations in this dissertation to illustrate the key role of vegetation in the climate system and human society. Specifically, this is accomplished via three studies, described below. First, we address the problem of how to retrieve Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FPAR) from a novel satellite Bidirectional Reflectance Factor product derived from the Multi-Angle Implementation of Atmospheric Correction algorithm. The LAI/FPAR retrieval is done via a radiative transfer model using the recently developed theory of spectral invariants. Our analyses show that the LAI/FPAR data sets developed in this study have higher accuracy and better stability relative to the existing products, especially in cloudy conditions and under high aerosol loadings. Second, we analyze the long-term trend in LAI derived from the Moderate Resolution Imaging Spectroradiometer observations and identify its main driver. We find that over a third of the terrestrial vegetation shows statistically significant increasing trends in LAI (i.e., Earth greening) during the 21st century. Both remote sensing and inventory data show that land-use management is the key driver of this greening, arising primarily from large-scale tree planting and intensive agriculture in emerging countries like China and India. This finding highlights the need for a more realistic representation of land-use practices in Earth system models. Third, we use a new method based on the concept of “two-resistances” and the Community Land Model (CLM5) runs with prescribed satellite-derived LAI to quantify the impacts of Earth greening on land surface temperature (LST). We find that over 90% of the Earth greening can lead to a local cooling effect at the annual scale. Further attribution analysis with multiple data sources reveals that aerodynamic resistance is the dominant factor controlling the LST change. The greening produces a decrease in aerodynamic resistance, which favors increased heat dissipation by turbulent fluxes, including the latent heat flux. These studies that span LAI data production, long-term trends and their impacts highlight the importance of vegetation dynamics in the natural and human systems.

Ces travaux ont pour objectif général d'améliorer la représentation spatio-temporelle des processus hydrologiques de surface à partir de modèles dont la complexité est adaptée aux informations disponibles par la télédétection multi-capteur/multi-résolution. Nous avons poursuivi des développements méthodologiques (désagrégation, assimilation, modélisation du bilan d'énergie) autour de l'estimation de l'humidité du sol dans le contexte de la gestion des ressources en eau dans les régions semi-arides. Récemment, des missions spatiales permettent d'observer l'humidité des sols en surface; notamment avec le capteur AMSR-E (Advanced Microwave Scanning Radiometer-EOS) et la mission SMOS (Soil Moisture Ocean Salinity). Toutefois la résolution spatiale de ces capteurs est trop large (> 40 km) pour des applications hydrologiques. Afin de résoudre le problème d'échelle, l'algorithme de désagrégation DisPATCh (Disaggregation based on Physical and Theoretical Scale Change) a été développé en se basant sur un modèle d'évapotranspiration. Dans la première partie de thèse, l'algorithme est appliqué et validé sur le bassin du Murrumbidgee (sud-est de l'Australie) avec une résolution spatiale cible de 1 km à partir des données de LST (Température de surface) et NDVI (indice de végétation) issues de MODIS (MODerate resolution Imaging Spectroradiometer) et de deux produits d'humidité du sol basse résolution : SMOS et AMSR-E. Les résultats montrent que la désagrégation est plus efficace en été, où la performance du modèle d'évapotranspiration est optimale. L'étude précédente a notamment mis en évidence que la résolution temporelle des données DisPATCh est limitée par la couverture nuageuse visible sur les images MODIS et la résolution temporelle des radiomètres micro-ondes (3 jours pour SMOS). Dans la deuxième partie, une nouvelle approche est donc développée pour assurer la continuité temporelle des données d'humidité de surface en assimilant les données DisPATCh dans un modèle dynamique de type force-restore, forcé par des données météorologiques issus de ré-analyses, dont les précipitations. La méthode combine de manière originale un système variationnel (2D-VAR) pour estimer l'humidité du sol en zone racinaire et une approche séquentielle (filtre de Kalman simplifié) pour analyser l'humidité du sol en surface. La performance de l'approche est évaluée sur deux zones: la région Tensift-Haouz au Maroc et la région de Yanco en Australie. Les résultats montrent que le couplage désagrégation/assimilation de l'humidité du sol est un outil performant pour estimer l'humidité en surface à l'échelle journalière, même lorsque les données météorologiques sont incertaines. Dans la troisième partie, une méthode de correction des effets topographiques sur la LST est développée dans le but d'étendre l'applicabilité de DisPATCh aux zones vallonnées ou montagneuses qui jouent souvent le rôle de château d'eau sur les régions semi-arides. Cette approche, basée sur un modèle de bilan d'énergie à base physique, est testée avec les données ASTER (Advanced Spaceborne Thermal Emission Reflection Radiometer) et Landsat sur la vallée d'Imlil dans le Haut Atlas Marocain. Les résultats indiquent que les effets topographiques ont été fortement réduits sur les images de LST à ~100 m de résolution et que la LST corrigée pourrait être utilisée comme une signature de l'état hydrique en montagne. Les perspectives ouvertes par ces travaux concernent la correction/désagrégation des données de précipitations et l'estimation des apports par l'irrigation pour une gestion optimisée de l'eau. / This thesis aims to improve the spatio-temporal resolution of surface water fluxes at the land surface-atmosphere interface based on appropriate models that rely on readily available multi-sensor remote sensing data. This work has been set up to further develop (disaggregation, assimilation, energy balance modeling) approaches related to soil moisture monitoring in order to optimize water management over semi-arid areas. Currently, the near surface soil moisture data sets available at global scale have a spatial resolution that is too coarse for hydrological applications. Especially, the near surface soil moisture retrieved from passive microwave observations such as AMSR-E (Advanced Microwave Scanning Radiometer-EOS) and SMOS (Soil Moisture and Ocean Salinity) data have a spatial resolution of about 60 km and 40 km, respectively. In this context, the downscaling algorithm "DISaggregation based on Physical And Theoretical scale Change" (or DisPATCh) has been developed. The near surface soil moisture variability is estimate within a low resolution pixel at the targeted 1 km resolution based on an evapotranspiration model using LST (Land surface temperature) and NDVI (vegetation index) derived from MODIS (MODerate resolution Imaging Spectroradiometer) data. Within a first step, DisPATCh is applied to SMOS and AMSR-E soil moisture products over the Murrumbidgee river catchment in Southeastern Australia and is evaluated during a one-year period. It is found that the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. However, the temporal resolution of DisPATCh data is limited by the gaps in MODIS images due to cloud cover, and by the temporal resolution of passive microwave observations (global coverage every 3 days for SMOS). The second step proposes an approach to overcome these limitations by assimilating the 1 km resolution DisPATCh data into a simple dynamic soil model forced by reanalysis meteorological data including precipitation. The original approach combines a variational scheme for root-zone soil moisture analysis and a sequential approach for the update of surface soil moisture. The performance is assessed using ground measurements of soil moisture in the Tensift-Haouz region in Morocco and the Yanco area in Australia during 2014. It is found that the downscaling/assimilation scheme is an efficient approach to estimate the dynamics of the 1 km resolution surface soil moisture at daily time scale, even when coarse scale and inaccurate meteorological data including rainfall are used. The third step presents a physically-based method to correct LST data for topographic effects in order to offer the opportunity for applying DisPATCh over mountainous areas. The approach is tested using ASTER (Advanced Spaceborne Thermal Emission Reflection Radiometer) and Landsat data over a 6 km by 6 km steep-sided area in the Moroccan Atlas. It is found that the strong correlations between LST and illumination over rugged terrain before correction are greatly reduced at ~100 m resolution after the topographic correction. Such a correction method could potentially be used as a proxy of the surface water status over mountainous terrain. This thesis opens the path for developing new remote sensing-based methods in order to retrieve water inputs -including both precipitation and irrigation- at high spatial resolution for water management.

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Städtische Gebiete unterscheiden sich von Flächen mit ruraler Prägung, im Ergebnis sind sie stark modifiziert bezüglich ihrer Strahlungs- und Energiebilanz. In der vorliegenden Arbeit werden die Oberflächentemperaturen der Metropole Berlin im Mesomaßstab, unter Verwendung von Satellitenaufnahmen der ASTER- und Landsat-5- und 7-Sensoren untersucht sowie durch zusätzliche Messungen mit einer Thermalbildkamera über einen Zeitraum von 17 Monaten im Mikromaßstab erweitert. Diese Daten kombiniert mit GIS-basierten Informationen über die Landnutzungs- und Strukturtypen werden für die Analyse der räumlichen und zeitlichen Verteilung der Oberflächentemperaturen genutzt ebenso wie zur Ermittlung funktioneller Beziehungen zwischen dem thermischen Verhalten der Oberflächen und der zugehörigen Stadtstruktur. Bei der Auswertung geht es vorrangig um physikalische Prozesse und Eigenschaften, die einen Einfluss auf energetische Flüsse und ihre Interaktion mit städtischen Oberflächen haben. Eine thermische Charakteristik einzelner Bezirke über verschiedene Nutzungsklassen bis hin zu einzelnen Materialien wird erstellt. Dabei sind Temperaturdifferenzen von mehreren zehntel Kelvin zwischen den typischen städtischen Oberflächen Dächern und Rasenflächen zu beobachten. Die Resultate zeigen, dass die Verteilung der LST sehr verschieden ist und stark korreliert mit den Landbedeckungen. Es wird dargestellt, welche Stadtstrukturen besonders thermisch belastet sind, welche individuelle thermische Bedeutung einzelne Materialien haben. Besonderes Augenmerk wird auf Möglichkeiten der Beeinflussung durch Abschattung gelegt. Durch Verschattung können Differenzen der Oberflächentemperaturen von mehr als 10 Kelvin erreicht werden. Abschließend werden Modellierungen zur Verifizierung der Kameramessungen sowie zum Aufzeigen des Einflusses minimaler Änderungen in kleinräumigen Klimaten genutzt. / Urban areas differ from surfaces of rural character. They are very modified in their radiation- and energy balance. In this study land-surface temperatures of the city of Berlin are analyzed with the help of satellite pictures of the ASTER- and Landsat-5 and -7 sensors in mesoscale and then extended by extra measurements of an infrared camera in microscale over the course of 17 months. This data combined with GIS based information on different land use and -structures are used for the analysis of spatial and time distribution, as well as for the determination of functional relations between thermal behaviour of surfaces and the related urban structures. The evaluation mainly deals with physical processes and properties that have an influence on energetic flows and their interactions with urban surfaces. A thermal characteristic of individual districts, from different land use classes to specific materials is being created. In this there are differences in temperature of several tenths Kelvin between the typical urban surfaces of roofs and grass areas visible. The results show that the distribution of the LST varies immensely and correlates with the land coverage. It is shown, what urban structures are most thermic burdened, what individual significance specific materials have. Special attention is paid to the different possibilities of the influence through shadow. It is possible to reach a difference of surface temperatures of more than 10 Kelvin by shadow. At the end models with the 3-dimensional ENVImet are used to verify the camera measurements as well as to show the influence of minimal changes in microscale climate.

abstract: This dissertation research studies long-term spatio-temporal patterns of surface urban heat island (SUHI) intensity, urban evapotranspiration (ET), and urban outdoor water use (OWU) using Phoenix metropolitan area (PMA), Arizona as the case study. This dissertation is composed of three chapters. The first chapter evaluates the SUHI intensity for PMA using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product and a time-series trend analysis to discover areas that experienced significant changes of SUHI intensity between 2000 and 2017. The heating and cooling effects of different urban land use land cover (LULC) types was also examined using classified Landsat satellite images. The second chapter is focused on urban ET and the impacts of urban LULC change on ET. An empirical model of urban ET for PMA was built using flux tower data and MODIS land products using multivariate regression analysis. A time-series trend analysis was then performed to discover areas in PMA that experienced significant changes of ET between 2001 and 2015. The impact of urban LULC change on ET was examined using classified LULC maps. The third chapter models urban OWU in PMA using a surface energy balance model named METRIC (Mapping Evapotranspiration at high spatial Resolution with Internalized Calibration) and time-series Landsat Thematic Mapper 5 imagery for 2010. The relationship between urban LULC types and OWU was examined with the use of very high-resolution land cover classification data generated from the National Agriculture Imagery Program (NAIP) imagery and regression analysis. Socio-demographic variables were selected from census data at the census track level and analyzed against OWU to study their relationship using correlation analysis. This dissertation makes significant contributions and expands the knowledge of long-term urban climate dynamics for PMA and the influence of urban expansion and LULC change on regional climate. Research findings and results can be used to provide constructive suggestions to urban planners, decision-makers, and city managers to formulate new policies and regulations when planning new constructions for the purpose of sustainable development for a desert city. / Dissertation/Thesis / Doctoral Dissertation Geography 2018

Land surface temperature (LST) and mean radiant temperature (MRT) are commonly used as proxies to evaluate urban heat environments. Many scholars use one of them to represent heat exposure when assessing the urban thermal environment. This research fills a research gap by analyzing two meteorological parameters simultaneously through correlation analysis, hotspot analysis, and the distinctive information they respectively express with the results of vulnerable population distribution based on the case of Linköping. Scatter plots are used to explore the correlation between LST and MRT, and hot spot analysis is applied to investigate their spatial patterns through the clusters of hot and cold spots. Furthermore, the distribution of vulnerable populations is assessed and visualized through a vulnerability index. The results show that there is a moderate positive linear correlation between the mean values of LST and MRT for the whole study area. They have different spatial patterns based on the results of the hot spot analysis. The comparison of different meteorological parameters to the vulnerability index also shows variations in high heat risk areas. All of these conclude that LST or MRT could, to some extent, be presented as references to each other; however, they cannot be used interchangeably as proxies for urban heat exposure. When developing urban thermal adaptation strategies, it is necessary for municipalities to select the parameters appropriately according to the purpose and requirements and to understand what the chosen parameters can and cannot convey.