Wildfires across northern Australia are a growing problem with more than 2.5 million hectares being burnt each year. Accordingly, remote sensing has been used as a tool to routinely monitor and map fire histories. In northern Western Australia, the Department of Land Information Satellite Remote Sensing Services (DLI SRSS) has been responsible for providing and interpreting NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) data. SRSS staff utilise this data to automatically map hotspots on a daily basis, and manually map fire affected areas (FAA) every nine days. This information is then passed on to land managers to enhance their ability to manage the effects of fire and assess its impact over time. The aim of this study was to develop an algorithm for the near real-time automatic mapping of FAA in the Kimberley and Pilbara as an alternative to the currently used semimanual approach. Daily measures of temperature, surface reflectance and vegetation indices from twenty nine NOAA-16 (2001) passes were investigated. It was firstly necessary to apply atmospheric and BRDF corrections to the raw reflectance data to account for the variation caused by changing viewing and illumination geometry over a cycle. Findings from the four case studies indicate that case studies 1 and 2 exhibited a typical fire response (visible and near-infrared channels and vegetation indices decreased), whereas 3 and 4 displayed an atypical response (visible channel increased while the near-infrared channel and vegetation indices decreased). Alternative vegetation indices such as GEMI, GEMI3 and VI3 outperformed NDVI in some cases. Likewise atmospheric and BRDF corrected NDVI provided better performance in separating burnt and unburnt classes. The difficulties in quantifying FAA due to temporal and spatial variation result from numerous factors including vegetation type, fire intensity, rate of ash and charcoal dispersal due to wind and rain, background soil influence and rate of revegetation. In this study two different spectral responses were recorded, indicating the need to set at least two sets of thresholds in an automated or semi-automated classification algorithm. It also highlighted the necessity of atmospheric and BRDF corrections. It is therefore recommended that future research apply atmospheric and BRDF corrections at the pre-processing stage prior to analysis when utilising a temporal series of NOAAAVHRR data. Secondly, it is necessary to investigate additional FAA within the four biogeographic regions to enable thresholds to be set in order to develop an algorithm. This algorithm must take into account the variation in a fire’s spectral response which may result from fire intensity, vegetation type, background soil influence or climatic factors.

No description available.

This study computed the Normalized Difference Vegetation Index (NDVI) products derived from NOAA AVHRR, MODIS, and SPOT VGT sensors. NDVI products from different instruments vary in spatial resolution, temporal coverage and spectral range. As a result, multi-sensor NDVI products are rarely used in a single phenological study. In order to evaluate the difference and similarity of NDVI records from the three sensors, I used EPA Eco-region frameworks to determine the average annual Start of Season (SOS) and End of Season (EOS) of Contiguous United States, and analyzed dates among datasets. In addition, I created 1127 sample points within the study area, and compared relationship between SOS/EOS based on land cover. The objectives of this thesis are to: 1) compare multi-sensor NDVI data using phenological models, 2) define a strategy to merge multi-sensor NDVI products to a single phenological product without direct NDVI conversion. The spatial and statistical analysis revealed that the Land Surface Phenology (LSP) measurements retrieved from NDVI time series from different sensors follow linear and positive relationships where compared by either eco-region or sample point. The historical record of AVHRR combined with the modern MODIS and SPOT data provides a critical and reliable perspective on phenological patterns in Contiguous United States area. The success of this study will help LSP by providing understanding of how different instruments can be combined to generate multi-sensor NDVI data for phenology. / Master of Science

Desenvolveu-se nesse trabalho uma metodologia para identificar e quantificar quinzenalmente a área queimada na região contínua do Cerrado brasileiro a partir de imagens diárias do sensor AVHRR (Advanced Very High Resolution Radiometer) do satélite NOAA-14 (National Oceanic and Atmospheric Administration), utilizando as bandas 1 (0.6 um), 2 (0,9 um), 3 (3.7 um) e IVDN (Índice de Vegetação de Diferença Normalizada). A variação temporal de características das áreas queimadas e outras superfícies, obtida de mosaicos quinzenais das imagens AVHRR, foi a base para elaborar um algoritmo de identificação de \"cicatrizes\" de queimadas. Os resultados foram validados e ajustados com dados de alta resolução espacial obtidos em imagens TM/Landsat (Thematic Mapper). A análise estatística de regressão linear entre os dados de queimadas obtidos pela aplicação do algoritmo nos mosaicos AVHRR e aqueles das imagens TM gerou duas equações para estimar a área queimada no Cerrado com r2 = 0,8 e 0,7. Com a aplicação da metodologia desenvolvida, estimou-se em ~429.000 km2 a área queimada (entre 404.000 km2 e 455.000 km2 com intervalo de confiança a 95%) no período de 01/maio/98 a 30/abril/99, correspondendo a 19% (18 a 20%) da área total estudada. A relação entre focos de queimadas obtidos do AVHRR/NOAA-12 e área queimada permitiu cálculos preliminares de área queimada no Cerrado no período de 01/maio/99 a 31/outubro/00. Os dados TM mostraram que as queimadas pequenas, menores que 0,5 km2, embora muito numerosas (53% do total), respondem por apenas ~2 % da área queimada. Por outro lado, as queimadas grandes, maiores que 10 km2, são poucas (8%), mas responsáveis por cerca de 74% da área queimada no Cerrado. Os resultados desse trabalho mostraram pela primeira vez que é possível estimar regularmente a área queimada no Cerrado com erro inferior a 15% no cálculo anual a partir dos dados diários do AVHRR. Tais estimativas poderão subsidiar estudos sobre o papel ecológico do fogo no Cerrado, planejamento ambiental em nível regional, localização das áreas críticas com ocorrências mais freqüentes de queimadas, implantação de planos de uso, manejo e fiscalização do uso do fogo em escala regional, cálculos de emissões de queimadas, etc. / This work presents the development of a methodology to identify and quantify the surface burnt in the Brazilian contiguous Cerrado on a bi-weekly basis using daily images of the AVHRR (Advanced Very High resolution Radiometer) sensor on-board the NOAA-14 (National Oceanographic and Atmospheric Administration) satellite after its bands 1 (0,6 um), 2 (0,9 um) and 3 (3,7 um), as well as the NDVI (Normalized Difference Vegetation Index). The temporal variation of the burnt areas and of other surface covers in bi-weekly AVHRR mosaics was the basis for an algorithm to identify the \"scars\" from vegetation fires. The results were validated and adjusted with high resolution data from TM-Landsat (Thematic Mapper). The statistical analysis of linear regression between the fire data obtained with the use of the algorithm and those of the TM produced two equations to estimate burnt area in the Cerrado, with r2 = 0.8 and 0.7. Applying the methodology developed, ~429,000 km2 burned in the period of May/01/98 to April/04/99 (range of 404,000 to 455,000 km2 for the 95% confidence interval), corresponding to 19% (18 to 20 %) of the total study area. The relation between active fires obtained with AVHRR/NOAA-12 and the burnt area supplied preliminary estimates of burnt area in the Cerrado from May/01/99 to Oct/31/00. The TM data showed that small scars, with less than 0.5 km2, although numerous (53 % of the total), account for just ~2 % of the burnt area. Large scars, with more than 10 km2, correspond to a small number (8 %), but to 74 % of the Cerrado burnt area. The results of this work showed for the first time that it is possible to estimate on a regular basis the Cerrado yearly burnt area with an error smaller than 15 %, using daily AVHRR data. These estimates should provide important information to understand the ecological role of fire in the Cerrado, identify areas with higher fire frequency, help environmental planning at regional levels, and plan soil use and control, as well as provide subsidies in biomass burning emission studies. Data from new sensors in satellites to be made available in 2001 should improve even further the methodology developed.

Desenvolveu-se nesse trabalho uma metodologia para identificar e quantificar quinzenalmente a área queimada na região contínua do Cerrado brasileiro a partir de imagens diárias do sensor AVHRR (Advanced Very High Resolution Radiometer) do satélite NOAA-14 (National Oceanic and Atmospheric Administration), utilizando as bandas 1 (0.6 um), 2 (0,9 um), 3 (3.7 um) e IVDN (Índice de Vegetação de Diferença Normalizada). A variação temporal de características das áreas queimadas e outras superfícies, obtida de mosaicos quinzenais das imagens AVHRR, foi a base para elaborar um algoritmo de identificação de \"cicatrizes\" de queimadas. Os resultados foram validados e ajustados com dados de alta resolução espacial obtidos em imagens TM/Landsat (Thematic Mapper). A análise estatística de regressão linear entre os dados de queimadas obtidos pela aplicação do algoritmo nos mosaicos AVHRR e aqueles das imagens TM gerou duas equações para estimar a área queimada no Cerrado com r2 = 0,8 e 0,7. Com a aplicação da metodologia desenvolvida, estimou-se em ~429.000 km2 a área queimada (entre 404.000 km2 e 455.000 km2 com intervalo de confiança a 95%) no período de 01/maio/98 a 30/abril/99, correspondendo a 19% (18 a 20%) da área total estudada. A relação entre focos de queimadas obtidos do AVHRR/NOAA-12 e área queimada permitiu cálculos preliminares de área queimada no Cerrado no período de 01/maio/99 a 31/outubro/00. Os dados TM mostraram que as queimadas pequenas, menores que 0,5 km2, embora muito numerosas (53% do total), respondem por apenas ~2 % da área queimada. Por outro lado, as queimadas grandes, maiores que 10 km2, são poucas (8%), mas responsáveis por cerca de 74% da área queimada no Cerrado. Os resultados desse trabalho mostraram pela primeira vez que é possível estimar regularmente a área queimada no Cerrado com erro inferior a 15% no cálculo anual a partir dos dados diários do AVHRR. Tais estimativas poderão subsidiar estudos sobre o papel ecológico do fogo no Cerrado, planejamento ambiental em nível regional, localização das áreas críticas com ocorrências mais freqüentes de queimadas, implantação de planos de uso, manejo e fiscalização do uso do fogo em escala regional, cálculos de emissões de queimadas, etc. / This work presents the development of a methodology to identify and quantify the surface burnt in the Brazilian contiguous Cerrado on a bi-weekly basis using daily images of the AVHRR (Advanced Very High resolution Radiometer) sensor on-board the NOAA-14 (National Oceanographic and Atmospheric Administration) satellite after its bands 1 (0,6 um), 2 (0,9 um) and 3 (3,7 um), as well as the NDVI (Normalized Difference Vegetation Index). The temporal variation of the burnt areas and of other surface covers in bi-weekly AVHRR mosaics was the basis for an algorithm to identify the \"scars\" from vegetation fires. The results were validated and adjusted with high resolution data from TM-Landsat (Thematic Mapper). The statistical analysis of linear regression between the fire data obtained with the use of the algorithm and those of the TM produced two equations to estimate burnt area in the Cerrado, with r2 = 0.8 and 0.7. Applying the methodology developed, ~429,000 km2 burned in the period of May/01/98 to April/04/99 (range of 404,000 to 455,000 km2 for the 95% confidence interval), corresponding to 19% (18 to 20 %) of the total study area. The relation between active fires obtained with AVHRR/NOAA-12 and the burnt area supplied preliminary estimates of burnt area in the Cerrado from May/01/99 to Oct/31/00. The TM data showed that small scars, with less than 0.5 km2, although numerous (53 % of the total), account for just ~2 % of the burnt area. Large scars, with more than 10 km2, correspond to a small number (8 %), but to 74 % of the Cerrado burnt area. The results of this work showed for the first time that it is possible to estimate on a regular basis the Cerrado yearly burnt area with an error smaller than 15 %, using daily AVHRR data. These estimates should provide important information to understand the ecological role of fire in the Cerrado, identify areas with higher fire frequency, help environmental planning at regional levels, and plan soil use and control, as well as provide subsidies in biomass burning emission studies. Data from new sensors in satellites to be made available in 2001 should improve even further the methodology developed.

Approved for public release; distribution is unlimited. / An established cloud analysis routine has been modified for use in the Arctic. The separation of clouds from the snow and sea ice backgrounds is accomplished through a multispectral technique which utilizes VHRR channel 2 (visible), channel 3 (near infrared) and channel 4 (infrared) data. The primary means of cloud identification is based on a derived channel 3 reflectance image. At this wavelength, a significant contrast exists between liquid clouds and the arctic backgrounds, unlike in the standard visible and infrared images. The channel 3 reflectance is obtained by first using the channel 4 emission temperature to estimate the thermal emission component of the total channel 3 radiance. This thermal emission component is subsequently removed from the total radiance, leaving only the solar reflectance component available for analysis. Since many ice clouds do not exhibit a substantially greater reflectance is channel 3, the routine exploits differences in transmissive characteristics between channels 3 and 4 for identification. The routine was applied to six case studies which had been analyzed by three independent experts to establish 'ground truth'. Verification of the cloud analysis results, through a comparison to the subjective analyses, yielded impressive statistics. A success rate of 77.9% was obtained with an arguably small data base of 131 undisputed scenes / http://archive.org/details/objectivetechniq00barr / Lieutenant, United States Navy

Student Number : 0216831W - MSc research report - School of Environmental Sciences - Faculty of Science / This report deals with the relationship between the NDVI obtained from the NOAA AVHRR sensor and that obtained from the MODIS sensor. The relationship is quantitatively assessed for distinct polygons over various land-cover types in the northeastern Kwa-Zulu Natal Province of South Africa. Spatial and temporal variations in the relationships are addressed and discussed with reference to spectral response, sunsensor- target geometries and atmospheric factors. Specifically, various methods are investigated to estimate a MODIS-equivalent NDVI from the AVHRR NDVI and in so doing create the potential to develop a self-consistent NDVI between the historically available AVHRR NDVI dataset and the relatively new MODIS NDVI dataset. NOAA-16 AVHRR NDVI data and AQUA MODIS NDVI data for the two-year period from January 2002 to December 2003 are used to develop the method. A linear relationship exists between the AVHRR and MODIS NDVI. However, spatial variations in the relationship in terms of land-cover and mean NDVI are pointed out. The potential of atmospheric corrections applied to AVHRR data through a radiative transfer atmospheric correction model to improve the relationship between the two NDVI datasets is also investigated. The importance of geo-location accuracy of the AVHRR NDVI dataset is assessed in the light of the accuracy obtainable with the proposed method to estimate a MODIS-equivalent NDVI from the AVHRR NDVI. A method to estimate the MODIS NDVI from the AVHRR NDVI that takes the mean AVHRR NDVI value into account, as opposed to a constant linear relationship over all the points, is proposed. Atmospheric correction is shown not to improve the accuracy of the method in a statistically significant way. The root-mean-square error of the proposed method is in the order of 0.05 NDVI units and varies between 0.5 and 2 standard deviations of the MODIS NDVI over an entire season.

The role of remote sensing data for monitoring different parameters in the study of ecosystems has been increasing. Particularly the development of different indices has played a great role to study the properties of vegetation and vegetation dynamics in large countries. In addition to this, satellite rainfall estimate data has been used to study the pattern of precipitation in areas where station rain-gauge data is not available. The Normalized Difference Vegetation Index (NDVI) and rainfall estimates data from the National Oceanic and Atmospheric Administration (NOAA) satellites were used to investigate the spatio-tempotal pattern of precipitation and the response of vegetation to precipitation in Ethiopia from 1996 to 2008. The patterns were studied in different land cover classes using data from the Global Land Cover Network (GLCN). The spatial patternof NDVI and precipitation showed that vegetation responded directly to precipitation. The seasonal patterns showed that there was between 0 to 3 months lag between precipitationand vegetation. However it was not possible to draw conclusion regarding the annual trendsof precipitation and NDVI because of the nature of the NDVI data, which was produced using the 10 day maximum composite values.

Made available in DSpace on 2016-06-02T19:29:43Z (GMT). No. of bitstreams: 1 TeseACP.pdf: 5193455 bytes, checksum: 5bc13e84b2705d44928f3d7b974a269a (MD5) Previous issue date: 2002-11-14 / Universidade Federal de Sao Carlos / At the present, the Cerrado (a type of the Brazilian savannas) is burned on about 20 to 30% of its area during the dry season mainly owing to anthropic causes. Three simultaneous factors are needed for the burnings to happen: favourable meteorological conditions; availability of vegetation fuel; existence of an ignition source. This work studied the susceptibility of the Cerrado vegetation to fire with respect to parameters linked to the three factors: rainfall, relative air humidity and air temperature with respect to the meteorological conditions; vegetation coverage classes with respect to the biomass fuel; proximity to the roads and fire spots from previous days with respect to the ignition source. Location data for the fire spots obtained from the AVHRR/NOAA-12 channel 3 (3,7 mm) images were used as field truth. The study period was between May and October 1998. The study area was divided into 50 km x 50 km cells. The meteorological conditions occurring in 95% of the cells presents fire spots were: rainfall lower than 2 mm; 5-day cumulative precipitation lower than 25 mm; relative air humidity lower than 60%; air temperature higher than 28oC; more than one rainless day before the burning. More than 80% of the Cerrado were susceptible to the fire occurrence, with both locations with and without fire spots presented the minimum meteorological conditions favourable to the vegetation burning described in the literature: rainfall lower than 5 mm; 5-day cumulative precipitation lower than 20 mm; relative air humidity lower than 60%; air temperature higher than 25oC; A method for classifying the Cerrado vegetation coverage to fire susceptibility was also developed. This method was based on 2-weekly mosaics of the AVHRR/NOAA-14 Normalized Difference Vegetation Index (NDVI) and of the channel 3 images. Seven classes of vegetation coverage were discriminated and associated to four degrees of susceptibility: very low, low, medium and high. It was verified that 72% of the burning occurred in the high and medium susceptibility classes, which indicated satisfactory results on the preliminary development of this method. Lastly, the distance between the fire spots and two indicators of anthropic activity was analysed. The indicators were: roads and fire spots previously occurred. About a quarter of the fire spots occurred at up to 10 km from the roads in a area of 582,000 km2 surrounding the roads, which is about 27% of the Cerrado´s total area. On the same way, a quarter of the spots occurred at up to 10 km from the fire spots of the previous day, in an average area of 33,000 km2 at the burning spots surroundings. This area is about 2% of the total area of the Cerrado. In conclusion, the indicators of anthropic activity analysed here area good tools for studying the vegetation susceptibility to fire. / Anualmente, o Cerrado é queimado em 20 a 30% de sua área durante a estação seca, principalmente devido a causas antrópicas. Três fatores simultâneos são necessários para que as queimadas ocorram: condições meteorológicas propícias; disponibilidade de combustível vegetal; existência de fonte de ignição. Este trabalho estudou a susceptibilidade da vegetação do Cerrado ao fogo em relação a parâmetros desses três fatores: precipitação, umidade relativa e temperatura do ar, em relação às condições meteorológicas; classes de cobertura vegetal, em relação ao combustível vegetal; proximidade de malha viária e de focos de queimadas dos dias anteriores, em relação à fonte de ignição. Como verdade de campo foram utilizados os dados de localização dos focos de queimadas obtidos de imagens do canal 3 (3,7 mm) do Advanced Very High Resolution Radiometer / National Oceanic and Atmospheric Administration - 12 (AVHRR/NOAA-12). O período de estudo foi de maio a outubro/1998. A área de estudo foi dividida em células de 50 km por 50 km. As condições meteorológicas em 95% das células com queimadas foram: precipitação inferior a 2 mm; precipitação acumulada de 5 dias inferior a 25 mm; umidade relativa do ar inferior a 60%; temperatura do ar superior a 28oC; mais de um dia sem chuva antecedendo a queimada. Mais de 80% do Cerrado estavam susceptível a ocorrência de fogo, com os locais com e sem focos de queimadas apresentando as condições meteorológicas mínimas propícias à combustão da vegetação relatadas na literatura: precipitação inferior a 5 mm; precipitação acumulada de 5 dias inferior a 20 mm; umidade relativa do ar inferior a 60%; temperatura do ar superior a 25oC. Um método para classificar a cobertura vegetal do Cerrado quanto à susceptibilidade ao fogo também foi desenvolvido, baseado em mosaicos quinzenais do Índice de Vegetação por Diferença Normalizada (IVDN) e do canal 3 gerados com base em imagens AVHRR/NOAA-14. Sete classes de cobertura vegetal foram discriminadas, as quais foram associadas a quatro graus de susceptibilidade: muito baixo, baixo, médio e alto. Foi verificado que 72% dos focos de queimadas ocorreram nas classes de susceptibilidade alta e média, indicando resultados satisfatórios no desenvolvimento preliminar desse método. Por último, foi analisada a distância entre focos de queimadas e dois indicadores de atividade antrópica: malha viária e focos de queimadas recentemente ocorridos. Cerca de um quarto dos focos de queimadas ocorreram até 10 km da malha viária, em uma área ao longo das vias de 582 mil km2, cerca de 27% da área total do Cerrado. Do mesmo modo, um quarto dos focos ocorreu até 10 km dos focos de queimadas ocorridos no dia anterior, em uma área média no entorno dos focos de 33 mil km2, cerca de 2% do Cerrado. Portanto, a proximidade de indicadores de atividade antrópicas pode ser um bom instrumento para avaliação da susceptibilidade da vegetação ao fogo.

This work was written as a cumulative doctoral thesis based on reviewed publications. Climate projections are mainly based on the results of numeric simulations from global or regional climate models. Up to now processes between atmosphere and land surface are only rudimentarily known. This causes one of the major uncertainties in existing models. In order to reduce parameterisation uncertainties and to find a reasonable description of sub grid heterogeneities, the determination and evaluation of parameterisation schemes for modelling require as many datasets from different spatial scales as possible. This work contributes to this topic by implying different datasets from different platforms. Its objective was to analyse the spatial heterogeneity of land surface parameters and energy flux densities obtained from both satellite observations with different spatial and temporal resolutions and in-situ measurements. The investigations were carried out for two target areas in Germany. First, satellite data for the years 2002 and 2003 were analysed and validated from the LITFASS-area (Lindenberg Inhomogeneous Terrain - Fluxes between Atmosphere and Surface: a longterm Study). Second, the data from the experimental field sites of the FLUXNET cluster around Tharandt from the years 2006 and 2007 were used to determine the NDVI (Normalised Difference Vegetation Index for identifying vegetated areas and their "condition"). The core of the study was the determination of land surface characteristics and hence radiant and energy flux densities (net radiation, soil heat flux, sensible and latent heat flux) using the three optical satellite sensors ETM+ (Enhanced Thematic Mapper), MODIS (Moderate Resolution Imaging Spektroradiometer) and AVHRR 3 (Advanced Very High Resolution Radiometer) with different spatial (30 m – 1 km) and temporal (1 day – 16 days) resolution. Different sensor characteristics and different data sets for land use classifications can both lead to deviations of the resultant energy fluxes between the sensors. Thus, sensor differences were quantified, sensor adaptation methods were implemented and a quality analysis for land use classifications was performed. The result is then a single parameterisation scheme that allows for the determination of the energy fluxes from all three different sensors. The main focus was the derivation of the latent heat flux (L.E) using the Penman-Monteith (P-M) approach. Satellite data provide measurements of spectral reflectance and surface temperatures. The P-M approach requires further surface parameters not offered by satellite data. These parameters include the NDVI, Leaf Area Index (LAI), wind speed, relative humidity, vegetation height and roughness length, for example. They were derived indirectly from the given satellite- or in-situ measurements. If no data were available so called default values from literature were taken. The quality of these parameters strongly influenced the exactness of the radiant- and energy fluxes. Sensitivity studies showed that NDVI is one of the most important parameters for determination of evaporation. In contrast it could be shown, that the parameters as vegetation height and measurement height have only minor influence on L.E, which justifies the use of default values for these parameters. Due to the key role of NDVI a field study was carried out investigating the spatial variability and sensitivity of NDVI above five different land use types (winter wheat, corn, grass, beech and spruce). Methods to determine this parameter not only from space (spectral), but also from in-situ tower measurements (broadband) and spectrometer data (spectral) were compared. The best agreement between the methods was found for winter wheat and grass measurements in 2006. For these land use types the results differed by less than 10 % and 15 %, respectively. Larger differences were obtained for the forest measurements. The correlation between the daily MODIS-NDVI data and the in-situ NDVI inferred from the spectrometer and the broadband measurements were r=0.67 and r=0.51, respectively. Subsequently, spatial variability of land surface parameters and fluxes were analysed. The several spatial resolutions of the satellite sensors can be used to describe subscale heterogeneity from one scale to the other and to study the effects of spatial averaging. Therefore land use dependent parameters and fluxes were investigated to find typical distribution patterns of land surface properties and energy fluxes. Implying the distribution patterns found here for albedo and NDVI from ETM+ data in models has high potential to calculate representative energy flux distributions on a coarser scale. The distribution patterns were expressed as probability density functions (PDFs). First results of applying PDFs of albedo, NDVI, relative humidity, and wind speed to the L.E computation are encouraging, and they show the high potential of this method. Summing up, the method of satellite based surface parameter- and energy flux determination has been shown to work reliably on different temporal and spatial scales. The data are useful for detailed analyses of spatial variability of a landscape and for the description of sub grid heterogeneity, as it is needed in model applications. Their usability as input parameters for modelling on different scales is the second important result of this work. The derived vegetation parameters, e.g. LAI and plant cover, possess realistic values and were used as model input for the Lokalmodell of the German Weather Service. This significantly improved the model results for L.E. Additionally, thermal parameter fields, e.g. surface temperature from ETM+ with 30 m spatial resolution, were used as input for SVAT-modelling (Soil-Vegetation-Atmosphere-Transfer scheme). Thus, more realistic L.E results were obtained, providing highly resolved areal information. / Die vorliegende Arbeit wurde auf der Grundlage begutachteter Publikationen als kumulative Dissertation verfasst. Klimaprognosen basieren im Allgemeinen auf den Ergebnissen numerischer Simulationen mit globalen oder regionalen Klimamodellen. Eine der entscheidenden Unsicherheiten bestehender Modelle liegt in dem noch unzureichenden Verständnis von Wechselwirkungsprozessen zwischen der Atmosphäre und Landoberflächen und dem daraus folgenden Fehlen entsprechender Parametrisierungen. Um das Problem einer unsicheren Modell-Parametrisierung aufzugreifen und zum Beispiel subskalige Heterogenität in einer Art und Weise zu beschreiben, dass sie für Modelle nutzbar wird, werden für die Bestimmung und Evaluierung von Modell-Parametrisierungsansätzen so viele Datensätze wie möglich benötigt. Die Arbeit trägt zu diesem Thema durch die Verwendung verschiedener Datensätze unterschiedlicher Plattformen bei. Ziel der Studie war es, aus Satellitendaten verschiedener räumlicher und zeitlicher Auflösung sowie aus in-situ Daten die räumliche Heterogenität von Landoberflächenparametern und Energieflussdichten zu bestimmen. Die Untersuchungen wurden für zwei Zielgebiete in Deutschland durchgeführt. Für das LITFASS-Gebiet (Lindenberg Inhomogeneous Terrain - Fluxes between Atmosphere and Surface: a longterm Study) wurden Satellitendaten der Jahre 2002 und 2003 untersucht und validiert. Zusätzlich wurde im Rahmen dieser Arbeit eine NDVI-Studie (Normalisierter Differenzen Vegetations Index: Maß zur Detektierung von Vegetationflächen, deren Vitalität und Dichte) auf den Testflächen des FLUXNET Clusters um Tharandt in den Jahren 2006 und 2007 realisiert. Die Grundlage der Arbeit bildete die Bestimmung von Landoberflächeneigenschaften und daraus resultierenden Energieflüssen, auf Basis dreier optischer Sensoren (ETM+ (Enhanced Thematic Mapper), MODIS (Moderate Resolution Imaging Spectroradiometer) und AVHRR 3 (Advanced Very High Resolution Radiometer)) mit unterschiedlichen räumlichen (30 m – 1 km) und zeitlichen (1 – 16 Tage) Auflösungen. Unterschiedliche Sensorcharakteristiken, sowie die Verwendung verschiedener, zum Teil ungenauer Datensätze zur Landnutzungsklassifikation führen zu Abweichungen in den Ergebnissen der einzelnen Sensoren. Durch die Quantifizierung der Sensorunterschiede, die Anpassung der Ergebnisse der Sensoren aneinander und eine Qualitätsanalyse von verschiedenen Landnutzungsklassifikationen, wurde eine Basis für eine vergleichbare Parametrisierung der Oberflächenparameter und damit auch für die daraus berechneten Energieflüsse geschaffen. Der Schwerpunkt lag dabei auf der Bestimmung des latenten Wärmestromes (L.E) mit Hilfe des Penman-Monteith Ansatzes (P-M). Satellitendaten liefern Messwerte der spektralen Reflexion und der Oberflächentemperatur. Die P-M Gleichung erfordert weitere Oberflächenparameter wie zum Beispiel den NDVI, den Blattflächenindex (LAI), die Windgeschwindigkeit, die relative Luftfeuchte, die Vegetationshöhe oder die Rauhigkeitslänge, die jedoch aus den Satellitendaten nicht bestimmt werden können. Sie müssen indirekt aus den oben genannten Messgrößen der Satelliten oder aus in-situ Messungen abgeleitet werden. Stehen auch aus diesen Quellen keine Daten zur Verfügung, können sogenannte Standard- (Default-) Werte aus der Literatur verwendet werden. Die Qualität dieser Parameter hat einen großen Einfluss auf die Bestimmung der Strahlungs- und Energieflüsse. Sensitivitätsstudien im Rahmen der Arbeit zeigen die Bedeutung des NDVI als einen der wichtigsten Parameter in der Verdunstungsbestimmung nach P-M. Im Gegensatz dazu wurde deutlich, dass z. B. die Vegetationshöhe und die Messhöhe einen relativ kleinen Einfluss auf L.E haben, so dass für diese Parameter die Verwendung von Standardwerten gerechtfertigt ist. Aufgrund der Schlüsselrolle, welche der NDVI in der Bestimmung der Verdunstung einnimmt, wurden im Rahmen einer Feldstudie Untersuchungen des NDVI über fünf verschiedenen Landnutzungstypen (Winterweizen, Mais, Gras, Buche und Fichte) hinsichtlich seiner räumlichen Variabilität und Sensitivität, unternommen. Dabei wurden verschiedene Bestimmungsmethoden getestet, in welchen der NDVI nicht nur aus Satellitendaten (spektral), sondern auch aus in-situ Turmmessungen (breitbandig) und Spekrometermessungen (spektral) ermittelt wird. Die besten Übereinstimmungen der Ergebnisse wurden dabei für Winterweizen und Gras für das Jahr 2006 gefunden. Für diese Landnutzungstypen betrugen die Maximaldifferenzen aus den drei Methoden jeweils 10 beziehungsweise 15 %. Deutlichere Differenzen ließen sich für die Forstflächen verzeichnen. Die Korrelation zwischen Satelliten- und Spektrometermessung betrug r=0.67. Für Satelliten- und Turmmessungen ergab sich ein Wert von r=0.5. Basierend auf den beschriebenen Vorarbeiten wurde die räumliche Variabilität von Landoberflächenparametern und Flüssen untersucht. Die unterschiedlichen räumlichen Auflösungen der Satelliten können genutzt werden, um zum einen die subskalige Heterogenität zu beschreiben, aber auch, um den Effekt räumlicher Mittelungsverfahren zu testen. Dafür wurden Parameter und Energieflüsse in Abhängigkeit der Landnutzungsklasse untersucht, um typische Verteilungsmuster dieser Größen zu finden. Die Verwendung der Verteilungsmuster (in Form von Wahrscheinlichkeitsdichteverteilungen – PDFs), die für die Albedo und den NDVI aus ETM+ Daten gefunden wurden, bietet ein hohes Potential als Modellinput, um repräsentative PDFs der Energieflüsse auf gröberen Skalen zu erhalten. Die ersten Ergebnisse in der Verwendung der PDFs von Albedo, NDVI, relativer Luftfeuchtigkeit und Windgeschwindigkeit für die Bestimmung von L.E waren sehr ermutigend und zeigten das hohe Potential der Methode. Zusammenfassend lässt sich feststellen, dass die Methode der Ableitung von Oberflächenparametern und Energieflüssen aus Satellitendaten zuverlässige Daten auf verschiedenen zeitlichen und räumlichen Skalen liefert. Die Daten sind für eine detaillierte Analyse der räumlichen Variabilität der Landschaft und für die Beschreibung der subskaligen Heterogenität, wie sie oft in Modellanwendungen benötigt wird, geeignet. Ihre Nutzbarkeit als Inputparameter in Modellen auf verschiedenen Skalen ist das zweite wichtige Ergebnis der Arbeit. Aus Satellitendaten abgeleitete Vegetationsparameter wie der LAI oder die Pflanzenbedeckung liefern realistische Ergebnisse, die zum Beispiel als Modellinput in das Lokalmodell des Deutschen Wetterdienstes implementiert werden konnten und die Modellergebnisse von L.E signifikant verbessert haben. Aber auch thermale Parameter, wie beispielsweise die Oberflächentemperatur aus ETM+ Daten in 30 m Auflösung, wurden als Eingabeparameter eines Soil-Vegetation-Atmosphere-Transfer-Modells (SVAT) verwendet. Dadurch erhält man realistischere Ergebnisse für L.E, die hochaufgelöste Flächeninformationen bieten.