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In conventional remote sensing, visible-near infrared (VNIR) and shortwave infrared (SWIR) part of the electromagnetic spectrum (EMS) have been utilized for lithological discrimination extensively. Additionally, TIR part of the EM spectrum can also be utilized for discrimination of surface materials either through emissivity characteristics of materials or through radiance as in VNIR and SWIR. In this study, ASTER thermal multispectral infrared data is evaluated in regard to lithological discrimination and mapping through emissivity values rather than conventional methods that utilize radiance values. In order to reach this goal, Principle Component Analysis (PCA) and Decorrelation Stretch techniques are utilized for ASTER VNIR and SWIR data. Furthermore, the spectral indices which directly utilize the radiance values in VNIR, SWIR and TIR are also included in the image analysis. The emissivity values are obtained through Temperature-Emissivity Separation (TES) algorithm. The results of the image analyses, except spectral indices, are displayed in RGB color composite along with the geological map for visual interpretation. The results showed that utilizing emissivity values possesses potential for discrimination of organic matter bearing surface mixtures which has not been possible through the conventional methods. Additionally, PCA of emissivity values may increase the level of discrimination even further. Since the emissivity utilization is rather unused throughout in literature and new, further assessment of accuracy is highly recommended along with the field validations.

<p>Thermal and multispectral imagery can provide users with insights into the water stress status and evapotranspiration demand of crops. However, traditional platforms, such as satellites, for these thermal and multispectral sensors are limited in their usefulness due to low spatial and temporal resolution. Small unmanned aircraft system (UAS) have the potential to have similar sensors installed and provide canopy temperature and reflectance information at spatial and temporal resolutions more useful for crop management; however, most of the existing research on the calibration or the estimation of water status were established based on the satellite platforms either for the sensors calibration or water status quantification. There is, therefore, a need to develop methods specifically for UAS-mounted sensors. In this research, a pixel-based calibration and an atmospheric correction method based on in-field approximate blackbody sources were developed for an uncooled thermal camera, and the higher accurate vegetative temperature acquired after calibration was used as inputs to an algorithm developed for high-resolution thermal imagery for calculating crop latent heat flux. At last, a thermal index based on the Bowen ratio is proposed to quantify the water deficit stress in a crop field, along with this, a method for plot-level analysis of various vegetation and thermal indices have been demonstrated to illustrate its broad application to genetic selection. The objective was to develop a workflow to use high-resolution thermal and multispectral imagery to derive indices that can quantify crops water status on a plot level which will facilitate the research related to breeding selection.</p> <p>The camera calibration method can effectively reduce the root mean square error (RMSE) and variability of measurements. The pixel-based thermal calibration method presented here was able to reduce the measurement uncertainty across all the pixels in the images, thus improving the accuracy and reducing the between-pixel variability of the measurements. During field calibration, the RMSE values relative to ground reference targets for two flights in 2017 were reduced from 6.36°C to 1.24°C and from 4.56°C to 1.32°C, respectively. The latent heat flux estimation algorithm yields an RMSE of 65.23 W/m² compared with the ground reference data acquired from porometer. The Bowen ratio has a high correlation with drought conditions quantified using the soil moisture index, stomatal conductance, and crop water stress index (CWSI), which indicates the potential of this index to be used as a water deficit stress indicator. The thermal and multispectral indices on a plot level displayed will facilitate the breeding selection.</p>

In der vorliegenden Arbeit werden die Möglichkeiten einer Nutzung thermal-infraroter Wellenlängen zur fernerkundlichen Erfassung/Quantifizierung von Bodenparametern vorgestellt. Die Studie basiert auf Bodenproben des Untersuchungsgebietes Mullewa, welches sich in einer semiariden Agrarregion im West-Australischen Weizengürtel befindet. Im Mittelpunkt der Arbeit steht die Bewertung des langwelligen Infrarots (LWIR), innerhalb des atmosphärischen Fensters zwischen 8 und 14 Mikrometer, bezüglich seines spektralen Potentials für die quantitative Ableitung des Ton- und Sandgehaltes sowie des Gehaltes an organischem Kohlenstoff (SOC). Zur Abschätzung der Effizienz wurden die Ergebnisse des LWIR einer Quantifizierung aus dem herkömmlich gebrauchten solar-reflektiven Wellenlängenbereichs zwischen 0,4 und 2,5 Mikrometer (VNIR-SWIR) gegenübergestellt. Mit verschiedenen Methoden der Laborspektroskopie wurden Bodenproben aus dem Untersuchungsgebiet im thermalen (Emissions-FTIR-Spektroskopie und direktional-hemisphärische Reflexions- (DHR) Spektroskopie)und im solar-reflektiven (Diffuse Reflexions-Spektroskopie) Wellenlängenbereich eingemessen und anschließend auf ihren Informationsgehalt hin untersucht. Die quantitative Modellierung der pedologischen Parameter aus den gemessenen spektralen Signaturen wurde mithilfe einer multivariaten Regressionsanalyse (Partial Least Squares Regression – PLSR) realisiert. Diese Grundlagenstudie konnte zeigen, dass die spektralen Voraussetzungen im LWIR für ein mögliches Monitoring der Bodenparameter mit thermalen Fernerkundungsdaten gegeben sind. Die Arbeit demonstriert darüber hinaus, dass für die Erfassung/Quantifizierung der Textur-Parameter (Sand- und Tongehalt) der relevante spektrale Informationsgehalt im LWIR deutlich höher ist als im VNIR-SWIR. / This study embraces the feasibility of using the thermal infrared wavelength region for future remote sensing applications to detect/quantify soil parameters. The research is based on soil samples from the semiarid agricultural area of Mullewa, located within the wheat belt of Western Australia. The main focus of this study is to assess the potential of the longwave infrared (LWIR), within the atmospheric window between 8 and 14 micrometer, to predict the content of sand, clay and organic carbon (SOC) in soils. The results are compared with predictions made with the traditionally used solar-reflective wavelength region (visible, VIS: 0.4 - 0.7 micrometer; near infrared, NIR: 0.7 - 1.1 micrometer; shortwave infrared, SWIR: 1.1 - 2.5 micrometer). Using laboratory spectroscopy, the Mullewa soil samples were measured, both in the thermal infrared (emission FTIR spectroscopy and directional hemispherical reflection (DHR) spectroscopy) and in the solar-reflective (diffuse reflection spectroscopy) wavelength region. This data was analyzed to determine the relevant content of information for the soil parameters. Multivariate regression analyses (partial least squares regression - PLSR) were used to quantitatively model the soil parameters from the spectral signatures. This basic research demonstrated that the spectral requirements in the LWIR are met for monitoring these soil parameters with thermal remote sensing instruments. Furthermore the study found that the relevant spectral information for the detection/quantification of the sand- and the clay content (textural parameters) is explicitly higher in the LWIR than in the VNIR-SWIR.

The aim of this thesis is the modeling of surface directional thermal radiation and angular correction on the LST by using empirical and physical methods as well as the analysis of field validation. The work has conducted to some conclusions. The directional emissivity of natural surfaces was obtained from MODIS emissivity product and then used in the split-window algorithm for angular correction on LST. The parameterization models of directional emissivity and thermal radiation were developed. As for the non-isothermal pixels, the daytime-TISI method was proposed to retrieve directional emissivity and effective temperature from multi-angular middle and thermal infrared data. This was validated using an airborne dataset. The kernel-driven BRDF model was checked in the thermal infrared domain and its extension was used to make angular normalization on the LST. A new model, namely FovMod that concerns on the footprint of ground sensor, was developed to simulate directional brightness temperature of row crop canopy. Based on simulation result of the FovMod, an optimal footprintfor field validation of LST was obtained. This thesis has systematically investigated the topic of directional thermal radiation and angular correction on surface temperature and its findings will improve the retrieval accuracy of temperature and emissivity from remotely sensed data and will also provide suggestion for the future design of airborne or spaceborne multi-angular thermal infrared sensors and also for the ground measurement of surface parameters.

L'objectif de cette thèse est la modélisation du rayonnement thermique directionnel des surfaces et de la correction angulaire sur la LST par des méthodes empiriques et physiques ainsi que l'analyse de validation sur le terrain. L'émissivité directionnelle des surfaces naturelles a été obtenue à partir du produit émissivité MODIS et est ensuite utilisée dans l'algorithme de split-window de correction angulaire sur la LST. Les modèles de paramétrage de l'émissivité directionnelle et du rayonnement thermique ont été développés. En ce qui concerne les pixels non iso-thermiques, la méthode de jour-TISI a été proposée pour obtenir l'émissivité directionnelle et la température effective à partir de données multi-angulaires infrarouges médian et thermique. Cela a été validé à l'aide de données aéroportée. Le modèle de noyaux Kernel BRDF a été vérifié dans le domaine de l'infrarouge thermique et son extension a servi à la normalisation angulaire de la LST. Un nouveau modèle, FovMod, qui concerne l'empreinte du capteur au sol, a été développé pour simuler la température de brillance directionnelle de couvert végétal en rang. Basé sur le résultat de la simulation de FovMod, une empreinte optimale pour la validation de champ de vue a été obtenue. Cette thèse a étudié systématiquement le rayonnement thermique directionnel et les corrections angulaires sur la température de surface et ses résultats amélioreront la précision sur la température et émissivité à partir de données de télédétection. Ils fourniront également des indices pour la conception de capteurs infrarouges thermiques multi-angulaires aéro/spatio portés et également pour la mesure au sol des paramètres de surface. / The aim of this thesis is the modeling of surface directional thermal radiation and angular correction on the LST by using empirical and physical methods as well as the analysis of field validation. The work has conducted to some conclusions. The directional emissivity of natural surfaces was obtained from MODIS emissivity product and then used in the split-window algorithm for angular correction on LST. The parameterization models of directional emissivity and thermal radiation were developed. As for the non-isothermal pixels, the daytime-TISI method was proposed to retrieve directional emissivity and effective temperature from multi-angular middle and thermal infrared data. This was validated using an airborne dataset. The kernel-driven BRDF model was checked in the thermal infrared domain and its extension was used to make angular normalization on the LST. A new model, namely FovMod that concerns on the footprint of ground sensor, was developed to simulate directional brightness temperature of row crop canopy. Based on simulation result of the FovMod, an optimal footprintfor field validation of LST was obtained. This thesis has systematically investigated the topic of directional thermal radiation and angular correction on surface temperature and its findings will improve the retrieval accuracy of temperature and emissivity from remotely sensed data and will also provide suggestion for the future design of airborne or spaceborne multi-angular thermal infrared sensors and also for the ground measurement of surface parameters.

Arid regions, that have a terrestrial share of 30 %, heavily rely on groundwater for do-mestic, industrial and irrigation purposes. The reliance on groundwater has partly turned into a dependency in areas where the increasing population number and the expansion of irrigated agricultural areas demand more groundwater than is naturally replenished. Yet, spatial and temporal information on groundwater are often scarce induced by the facts that groundwater is given a low priority in many national budgets and numerous (semi-) arid regions in the world encompass large and inaccessible areas. Hence, there is an urgent need to provide low-cost alternatives that in parallel cover large spatial and temporal scales to gain information on the groundwater system. Remote sensing holds a tremendous potential to represent this alternative. The main objective of this thesis is the improvement of existing and the development of novel remote sensing applications to infer information on the scarce but indispensable resource groundwater at the example of the Dead Sea. The background of these de-velopments relies mainly on freely available satellite data sets. I investigate 1) the pos-sibility to infer potential groundwater flow-paths from digital elevation models, 2) the applicability of multi-temporal thermal satellite data to identify groundwater discharge locations, 3) the suitability of multi-temporal thermal satellite data to derive information on the long-term groundwater discharge behaviour, and 4) the differences of thermal data in terms of groundwater discharge between coarse-scaled satellite data and fine-scaled airborne data including a discharge quantification approach. 1) I develop a transparent, reproducible and objective semi-automatic approach us-ing a combined linear filtering and object based classification approach that bases on a medium resolution (30 m ground sampling distance) digital elevation model to extract lineaments. I demonstrate that the obtained lineaments have both, a hydrogeological and groundwater significance, that allow the derivation of potential groundwater flow-paths. These flow-paths match results of existing groundwater flow models remarkably well that validate the findings and shows the possibility to infer potential groundwater flow-paths from remote sensing data. 2) Thermal satellite data enable to identify groundwater discharge into open water bodies given a temperature contrast between groundwater and water body. Integrating a series of thermal data from different periods into a multi-temporal analysis accounts for the groundwater discharge intermittency and hence allows obtaining a representa-tive discharge picture. I analyse the constraints that arise with the multi-temporal anal-ysis (2000-2002) and show that ephemeral surface-runoff causes similar thermal anomalies as groundwater. To exclude surface-runoff influenced data I develop an au-tonomously operating method that facilitates the identification. I calculate on the re-maining surface-runoff uninfluenced data series different statistical measures on a per pixel basis to amplify groundwater discharge induced thermal anomalies. The results reveal that the range and standard deviation of the data series perform best in terms of anomaly amplification and spatial correspondence to in-situ determined spring dis-charge locations. I conclude on the reason that both mirror temperature variability that is stabilized and therefore smaller at areas where spatio-temporal constant groundwater discharge occurs. 3) The application of the before developed method on a thermal satellite data set spanning the years 2000 to 2011 enables to localise specific groundwater discharge sites and to semi-quantitatively analyse the temporal variability of the thermal anomalies (termed groundwater affected area - GAA). I identify 37 groundwater discharge sites along the entire Dead Sea coastline that refine the so far coarsely given spring areas to specific locations. All spatially match independent in-situ groundwater discharge observations and additionally indicate 15 so far unreported discharge sites. Comparing the variability of the GAA extents over time to recharge behaviour reveals analogous curve progressions with a time-shift of two years. This observation suggests that the thermally identified GAAs directly display the before only assumed groundwater discharge volume. This finding provides a serious alternative to monitor groundwater discharge over large temporal and spatial scales that is relevant for different scientific communities. From the results I furthermore conclude to observe the before only assumed and modelled groundwater discharge share from flushing of old brines during periods with an above average Dead Sea level drop. This observation implies the need to not only consider discharge from known terrestrial and submarine springs, but also from flushing of old-brines in order to calculate the total Dead Sea water budget. 4) I present a complementary airborne thermal data set recorded in 01/2011 over the north-western part of the Dead Sea coast. The higher spatial resolution allows to refine the satellite-based GAA to 72 specific groundwater discharge sites and even to specify the so far unknown abundance of submarine springs to six sites with a share of <10 % to the total groundwater discharge. A larger contribution stems from newly iden-tified seeping spring type (24 sites) where groundwater emerges diffusively either ter-restrial or submarine close to the land/water interface with a higher share to the total discharge than submarine springs provide. The major groundwater contribution origi-nates from the 42 identified terrestrial springs. For this spring type, I demonstrate that 93 % of the discharge volume can be modelled with a linear ordinary least square re-gression (R2=0.88) based on the thermal plume extents and in-situ measured discharge volumes from the Israel Hydrological Service. This result implies the possibility to determine discharge volumes at unmonitored sites along the Dead Sea coast as well that can provide a complete physically-based picture of groundwater discharge magni-tude to the Dead Sea for the first time.

Arid regions, that have a terrestrial share of 30 %, heavily rely on groundwater for do-mestic, industrial and irrigation purposes. The reliance on groundwater has partly turned into a dependency in areas where the increasing population number and the expansion of irrigated agricultural areas demand more groundwater than is naturally replenished. Yet, spatial and temporal information on groundwater are often scarce induced by the facts that groundwater is given a low priority in many national budgets and numerous (semi-) arid regions in the world encompass large and inaccessible areas. Hence, there is an urgent need to provide low-cost alternatives that in parallel cover large spatial and temporal scales to gain information on the groundwater system. Remote sensing holds a tremendous potential to represent this alternative. The main objective of this thesis is the improvement of existing and the development of novel remote sensing applications to infer information on the scarce but indispensable resource groundwater at the example of the Dead Sea. The background of these de-velopments relies mainly on freely available satellite data sets. I investigate 1) the pos-sibility to infer potential groundwater flow-paths from digital elevation models, 2) the applicability of multi-temporal thermal satellite data to identify groundwater discharge locations, 3) the suitability of multi-temporal thermal satellite data to derive information on the long-term groundwater discharge behaviour, and 4) the differences of thermal data in terms of groundwater discharge between coarse-scaled satellite data and fine-scaled airborne data including a discharge quantification approach. 1) I develop a transparent, reproducible and objective semi-automatic approach us-ing a combined linear filtering and object based classification approach that bases on a medium resolution (30 m ground sampling distance) digital elevation model to extract lineaments. I demonstrate that the obtained lineaments have both, a hydrogeological and groundwater significance, that allow the derivation of potential groundwater flow-paths. These flow-paths match results of existing groundwater flow models remarkably well that validate the findings and shows the possibility to infer potential groundwater flow-paths from remote sensing data. 2) Thermal satellite data enable to identify groundwater discharge into open water bodies given a temperature contrast between groundwater and water body. Integrating a series of thermal data from different periods into a multi-temporal analysis accounts for the groundwater discharge intermittency and hence allows obtaining a representa-tive discharge picture. I analyse the constraints that arise with the multi-temporal anal-ysis (2000-2002) and show that ephemeral surface-runoff causes similar thermal anomalies as groundwater. To exclude surface-runoff influenced data I develop an au-tonomously operating method that facilitates the identification. I calculate on the re-maining surface-runoff uninfluenced data series different statistical measures on a per pixel basis to amplify groundwater discharge induced thermal anomalies. The results reveal that the range and standard deviation of the data series perform best in terms of anomaly amplification and spatial correspondence to in-situ determined spring dis-charge locations. I conclude on the reason that both mirror temperature variability that is stabilized and therefore smaller at areas where spatio-temporal constant groundwater discharge occurs. 3) The application of the before developed method on a thermal satellite data set spanning the years 2000 to 2011 enables to localise specific groundwater discharge sites and to semi-quantitatively analyse the temporal variability of the thermal anomalies (termed groundwater affected area - GAA). I identify 37 groundwater discharge sites along the entire Dead Sea coastline that refine the so far coarsely given spring areas to specific locations. All spatially match independent in-situ groundwater discharge observations and additionally indicate 15 so far unreported discharge sites. Comparing the variability of the GAA extents over time to recharge behaviour reveals analogous curve progressions with a time-shift of two years. This observation suggests that the thermally identified GAAs directly display the before only assumed groundwater discharge volume. This finding provides a serious alternative to monitor groundwater discharge over large temporal and spatial scales that is relevant for different scientific communities. From the results I furthermore conclude to observe the before only assumed and modelled groundwater discharge share from flushing of old brines during periods with an above average Dead Sea level drop. This observation implies the need to not only consider discharge from known terrestrial and submarine springs, but also from flushing of old-brines in order to calculate the total Dead Sea water budget. 4) I present a complementary airborne thermal data set recorded in 01/2011 over the north-western part of the Dead Sea coast. The higher spatial resolution allows to refine the satellite-based GAA to 72 specific groundwater discharge sites and even to specify the so far unknown abundance of submarine springs to six sites with a share of <10 % to the total groundwater discharge. A larger contribution stems from newly iden-tified seeping spring type (24 sites) where groundwater emerges diffusively either ter-restrial or submarine close to the land/water interface with a higher share to the total discharge than submarine springs provide. The major groundwater contribution origi-nates from the 42 identified terrestrial springs. For this spring type, I demonstrate that 93 % of the discharge volume can be modelled with a linear ordinary least square re-gression (R2=0.88) based on the thermal plume extents and in-situ measured discharge volumes from the Israel Hydrological Service. This result implies the possibility to determine discharge volumes at unmonitored sites along the Dead Sea coast as well that can provide a complete physically-based picture of groundwater discharge magni-tude to the Dead Sea for the first time.:1 Introduction 1.1 Remote sensing applications on groundwater 1.1.1 Classical aspects 1.1.2 Modern aspects 1.2 Motivation and main objectives 1.3 Why the western catchment of the Dead Sea? 1.4 Overview 2 The western catchment of the Dead Sea 2.1 Geological and Structural Overview 2.2 Groundwater system 2.3 Groundwater inputs 2.4 Dead Sea 3 Groundwater flow-paths 3.1 Prologue 4 Method development for groundwater discharge identification 4.1 Prologue 5 Localisation and temporal variability of groundwater discharge 5.1 Prologue 6 Qualitative and quantitative refinement of groundwater discharge 6.1 Prologue 7 Conclusion and Outlook 7.1 Main results and implications 7.2 Outlook References Appendix