Philosophiae Doctor - PhD / Wetlands are highly productive systems that act as habitats for a variety of flora and fauna. Despite their ecohydrological significance, wetland ecosystems are under severe threat as a result of environmental changes (e.g. the changing temperature and rainfall), as well as pressure from anthropogenic land use activities (e.g. agriculture, rural-urban development and dam construction). Such changes result in severe disturbances in the hydrology, plant species composition, spatial distribution, productivity and diversity of wetlands, as well as their ability to offer critical ecosystem goods and services. However, wetland degradation varies considerably from place to place, with severe degradation occurring particularly in developing regions, such as sub-Saharan Africa, where Land Use and Land Cover changes impact on wetland ecosystems by affecting the diversity of plant species, productivity, as well as the wetland hydrology.

The capabilities of a number of remote-sensing techniques for biophysical mapping in the subarctic have been examined at Pen Island in northwestern Ontario. After a two week field reconnaissance, colour infrared aerial photography was studied and a detailed biophysical map of the area was produced. Using this knowledge LANDSAT satellite data of the site were investigated. In a visual analysis of the data, the majority of the units identified in the airphoto interpretation were detected, and these were distinguished primarily by their spectral characteristics. Digital analysis of the satellite data using the Bendix MAD system allowed many of the classes of the earlier studies to be delineated and also permitted the classification to be readily extended beyond the original site. In both LANDSAT analyses specific biophysical units could be mapped from the satellite data but could not be identified without the airphoto interpretation. / Thesis / Master of Science (MSc)

Infrastructural investments are crucial drivers for promoting growth and activating virtuous cycles of development. Their allocation processes and their socio-economic impact are themes of fundamental importance for development economics. The first two chapters of this thesis employ quasi-experimental methods to analyze the Road Sector Development Programme (RSDP), a large-scale infrastructural investment project implemented in Ethiopia between 1998-2016. The first chapter investigates whether road investment decisions have been influenced by ethnic favoritism mechanisms benefiting the Tigray People’s Liberation Front (TPLF), the dominant component of the Ethiopian People’s Revolutionary Democratic Front (EPRDF). We find evidence of a significant misallocation of public resources towards areas inhabited by the Tigray ethnicity with respect to a suitable control group. The second chapter looks at the impact of the increase in market access due to the RSDP on the productivity of formal and informal Ethiopian firms. Given the important role of informality in Sub-Saharan Africa, it is paramount to disentangle their reaction to productivity shocks from that of formal enterprises. We detect an increase in productivity for formal firms and a decrease in the likelihood of a firm being informal, compatible with the “entry into informality” of less productive formal enterprises and with the presence of informal “survivalist” firms at lower tiers of the productivity distribution. The third chapter employs near-real time satellite data to assess the economic and environmental impact of the Covid-19 contagion containment measures enacted by a selected group of Arab countries, therefore bringing to prominence the use of large, granular, and publicly available datasets for informing crisis response.

A large portion of Earth¿s terrestrial surface is subject to arid climatic water stress. As in these regions the hydrological cycle and the vegetation dynamics are tightly interconnected, a coupled modeling of these two systems is needed to fully reproduce the ecosystems¿ behavior over time and to predict possible future responses to climate change. In this thesis, the performance of three parsimonious dynamic vegetation models, suitable for inclusion in an operational ecohydrological model, are tested in a semi-arid Aleppo pine forest area in the south-east of Spain. The first model considered, HORAS (Quevedo & Francés, 2008), simulates growth as a function of plant transpiration (T), evaluating environmental restraints through the transpiration-reference evapotranspiration ratio. The state variable related to vegetation is R, relative foliar biomass, which is equivalent to FAO crop coefficient (Allen et al., 1998), but not fixed in time. The HORAS model was then abandoned because of its unsatisfactory results, probably due to a poor simulation of evaporation and transpiration processes. As for the other two models, WUE-model and LUE-model, the state variable is the leaf biomass (Bl, kg dry mass m-2 vegetation cover). Both models simulate gross primary production (GPP), in the first case as a function of transpiration and water use efficiency (WUE), in the second case as a function of absorbed photosynthetically active radiation (APAR) and light use efficiency (LUE). Net primary production (NPP) is then calculated taking into account respiration. The modelling is focused particularly on simulating foliar biomass, which is obtained from NPP through an allocation equation based on the maximum leaf area index (LAI) sustainable by the system, and considering turnover. An analysis of the information offered by MODIS EVI, NDVI, and LAI products was also performed, in order to investigate vegetation dynamics in the study site and to select the best indices to be used as observational verification for models. MODIS EVI is reported in literature (Huete et al., 2002) to be highly correlated with leaf biomass. In accordance with the phenological cycle timing described for the Aleppo pine in similar climates (Muñoz et al., 2003), the EVI showed maximum values in spring and minimum values in winter. Similar results were found applying the aforementioned WUE- and LUE- models to the study area. Contrasting simulated LAI with the EVI series, the correlation coefficients rWUE = 0.45 and rLUE = 0.57 were found for the WUE-model and LUE-model respectively. Concerning NDVI, its own definition links this index to the ¿greenness¿ of the target, so that it appears highly linked to chlorophyll content and vegetation condition, but only indirectly related to LAI. Photosynthetic pigment concentrations are reported to be sensitive to water stress in Aleppo pine (Baquedano and Castillo, 2006) so, to compare the models¿ results with NDVI, the simulated LAI was corrected by plant water-stress. The resulting correlation coefficients were rWUE = 0.62 and rLUE = 0.59. Lastly, MODIS LAI and ET were found to be unreliable in the study area because very low compared to field data and to values reported in literature (e.g. Molina & del Campo, 2012) for the same species in similar climatic conditions. The performance of both WUE- and LUE- models in this semi-arid region is found to be reasonable. However, the LUE-model presents the advantages of a better performance, the possibility to be used in a wider range of climates and to have been extensively tested in literature. / Pasquato, M. (2013). Comparison of parsimonious dynamic vegetation modelling approaches for semiarid climates [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34326

[EN] Water is the foundation for all biological life on Earth and one of the basic links between the biosphere and atmosphere. It is equally fundamental for humans and nature (Tolba, 1982). In an environment of growing scarcity and competition for water, increasing the understanding of all fluxes of the water cycle lies at the heart of the scientific community's goals. Traditionally, water and vegetation have been considered as different systems. However, it is necessary to take a holistic approach which considers the question of the water cycle in an integrated manner by taking into account both: blue water and green water (Birot et al., 2011). Around this idea, the new discipline Ecohydrology emerged in the early 20th century and, from then; it has grown steadily as shown by the increasing number of research lines and scientific papers related to this new field. However, most of the current hydrological models includes the vegetation as static parameter and not as state variable. There are some exceptions taking explicitly the vegetation as state variable but in those cases, the models' complexity and parametrical requirements increase substantially. In practice, we have to deal against the 'data scarcity - high parametrical requirements' issue really often. To reduce that issue, two strategies can be applied: (1) simplification of the models' conceptual scheme and (2) increase of data availability by incorporating new sources of information. In this thesis, we explored the use of a distributed parsimonious ecohydrological modelling (with low parametrical requirements) calibrated and validated exclusively with remote sensing data. First, we used the parsimonious ecohydrological model proposed by Pasquato et al. (2015) in an experimental plot located in a semi-arid Mediterranean forest. The results in this previous stage suggested that the model was able to adequately reproduce the dynamics of vegetation as well as the soil moisture variations. In other words, it has been shown that a parsimonious model with simple equations can achieve good results in general terms. But, as long as we applied the model at plot scale, the challenging task to reproduce the spatial variation of the vegetation and water cycle remained. To explore the spatio-temporal variation of the vegetation and the water cycle, the distributed version of the parsimonious ecohydrological model used previously was applied in a basin located in Kenya, concretely in the Upper Ewaso Ngiro River basin. In order to explore the potential applicability of the satellite data, we calibrated the model using exclusively the NDVI provided by NASA. First of all, we had to deal with the fact that we were not calibrating the model with only one temporal series such as historical streamflow as usual. In fact, satellite data is composed by one temporal series per pixel. We had to identify how to use spatio-temporal (and not only temporal) data during models' calibration and validation. In that sense, unfortunately, there is still a deep lack in literature. A methodology based on the use of Empirical Orthogonal Function analysis was proposed and successfully applied. This experience provided amazing and promising results. The obtained results demonstrated that: (1) satellite data of vegetation dynamics contains an extraordinary amount of information that can be used to implement ecohydrological models in scarce data regions; (2) the proposed semi-automatic calibration methodology works satisfactorily and it allows to incorporate spatio-temporal data in the model parameterization and (3) the model calibrated only using satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet point. It is important to highlight the positive consequences of this last result particularly in ungauged basins where the use of satellite data could be an alternative in order to obtain a proxy of the streamflow at outlet point. / [ES] El agua es la base de toda vida biológica en la Tierra y uno de los enlaces básicos entre la biosfera y la atmósfera. Es igualmente fundamental para los seres humanos y la naturaleza (Tolba, 1982). Tradicionalmente, el agua y la vegetación se han considerado como sistemas diferentes pero es claramente necesario tomar un enfoque holístico que considere la cuestión del ciclo del agua de una manera integrada, teniendo en cuenta tanto el agua azul como el agua verde (Birot et al., 2011). Alrededor de esta idea surgió la nueva disciplina llamada Ecohidrología a principios del siglo XX y desde entonces, no ha dejado de crecer tal y como demuestran el creciente aumento de líneas de investigación y publicaciones científicas relacionadas con este nuevo campo. Sin embargo, la mayoría de los modelos hidrológicos actuales incluye la vegetación como un parámetro estático y no como una variable de estado. Hay algunas excepciones que toman explícitamente la vegetación como variable de estado, pero en esos casos, la complejidad y el número de parámetros a determinar de los modelos aumentan sustancialmente. En la práctica, tenemos que hacer frente a la temible combinación de "escasez de datos - alto número de parámetros a determinar" con mucha frecuencia. Para reducir este problema, se pueden aplicar dos estrategias: (1) simplificar la complejidad conceptual de los modelos y así reducir el número de parámetros a calibrar, y/o (2) aumentar la disponibilidad de datos mediante la incorporación de nuevas fuentes de información. En esta tesis, hemos explorado el uso de un modelo ecohidrológico distribuido y parsimonioso (con pocos parámetros a determinar) que ha sido completamente calibrado y validado exclusivamente con datos de teledetección. En primer lugar, se utilizó el modelo ecohidrológico parsimonioso propuesto por Pasquato et al. (2015) en una parcela experimental situada en un bosque mediterráneo semiárido. Los resultados obtenidos en esta primera etapa de la tesis sugirieron que el modelo era capaz de reproducir adecuadamente la dinámica de la vegetación, así como las variaciones de humedad del suelo. En otras palabras, se pudo demostrar que un modelo parsimonioso con ecuaciones simples puede lograr buenos resultados en términos generales. Pero, como el modelo había sido aplicado a escala de parcela, todavía quedaba como tarea pendiente reproducir la variación espacial de la vegetación y del ciclo hidrológico. Para explorar la variación espacio-temporal de la vegetación y del ciclo del agua, se aplicó la versión distribuida del modelo ecohidrológico y parsimonioso utilizado previamente en una cuenca situada en Kenia. Con el fin de explorar la posible aplicabilidad de los datos de satélite, calibramos el modelo utilizando exclusivamente el NDVI proporcionada por la NASA. Se aplicó con éxito una metodología basada en el uso de la identificación de las funciones ortogonales empíricas (EOF por sus siglas en inglés). Esta última prueba proporcionó resultados prometedores: (1) los datos de satélite contienen una cantidad extraordinaria de información que puede ser usado para implementar modelos ecohidrológicos en regiones donde no se dispone de tal cantidad de información; (2) la metodología de calibración propuesta funciona satisfactoriamente y permite incorporar datos espacio-temporales en el proceso de parametrización del modelo, y (3) el modelo calibrado sólo con datos de satélite es capaz de reproducir tanto la dinámica espacio-temporal de la vegetación así como el caudal observado en el punto de desagüe de la cuenca. Es importante destacar las consecuencias positivas de este último resultado sobre todo en cuencas no aforadas, donde el uso de datos de satélite podría ser una alternativa para obtener una aproximación del recurso en el punto de desagüe. / [CA] L'aigua és la base de tota vida biològica a la Terra i un dels enllaços bàsics entre la biosfera i l'atmosfera. És igualment fonamental per als éssers humans i la naturalesa (Tolba, 1982). Tradicionalment, l'aigua i la vegetació s'han considerat com a sistemes diferents però és clarament necessari prendre un enfocament holístic que considere la qüestió del cicle de l'aigua d'una manera integrada, tenint en compte tant l'aigua blava com l'aigua verda (Birot et al., 2011). Al voltant d'aquesta idea va sorgir la nova disciplina anomenada Ecohidrología a principis del segle XX i des de llavors, no ha deixat de créixer tal com demostren el creixent augment de línies de recerca i publicacions científiques relacionades amb aquest nou camp. No obstant això, la majoria dels models hidrològics actuals inclou la vegetació com un paràmetre estàtic i no com una variable d'estat. Hi ha algunes excepcions que prenen explícitament la vegetació com a variable d'estat, però en aquests casos, la complexitat i el nombre de paràmetres a determinar dels models augmenten substancialment. En la pràctica, hem de fer front a la temible combinació de "escassetat de dades - alt nombre de paràmetres a determinar" amb molta freqüència. Per reduir aquest problema, es poden aplicar dues estratègies: (1) simplificar la complexitat conceptual dels models i així reduir el nombre de paràmetres a calibrar, i/o (2) augmentar la disponibilitat de dades mitjançant la incorporació de noves fonts d'informació. En aquesta tesi, hem explorat l'ús d'un model ecohidrològic distribuït i parsimoniòs (amb pocs paràmetres a determinar) que ha estat completament calibrat i validat exclusivament amb dades de teledetecció. En primer lloc, es va utilitzar el model ecohidrològic i parsimoniòs proposat per Pasquato et al. (2015) en una parcel·la experimental situada en un bosc mediterrani semi-àrid. Els resultats obtinguts en aquesta primera etapa de la tesi van suggerir que el model era capaç de reproduir adequadament la dinàmica de la vegetació, així com les variacions d'humitat del sòl. En altres paraules, es va poder demostrar que un model parsimoniòs amb equacions simples pot aconseguir bons resultats en termes generals. Però, com el model havia estat aplicat a escala de parcel·la, encara quedava com a tasca pendent reproduir la variació espacial de la vegetació i del cicle hidrològic. Per explorar la variació espai-temporal de la vegetació i del cicle de l'aigua, es va aplicar la versió distribuïda del model ecohidrològic i parsimoniòs utilitzat prèviament en una conca situada a Kenya. Al mateix temps, amb la finalitat d'explorar la possible aplicabilitat de les dades de satèl·lit, calibrem el model utilitzant exclusivament el NDVI proporcionat per la NASA. Es va aplicar amb èxit una metodologia basada en l'ús de la identificació de les funcions ortogonals empíriques (EOF per les seues sigles en anglès). Aquesta última prova va proporcionar resultats sorprenents i prometedors. De fet, els resultats obtinguts van demostrar que: (1) les dades de satèl·lit contenen una quantitat extraordinària d'informació que pot ser usada per implementar models ecohidrològics en regions on no es disposa de tal quantitat d'informació; (2) la metodologia de calibratge proposat funciona satisfactòriament i permet incorporar dades espai-temporals en el procés de parametrització del model, i (3) el model calibrat només amb dades de satèl·lit és capaç de reproduir tant la dinàmica espai-temporal de la vegetació així com el cabal observat en el punt de desguàs de la conca. És important destacar les conseqüències positives d'aquest últim resultat sobretot en conques no aforades, on l'ús de dades de satèl·lit podria ser una alternativa per obtenir una aproximació del recurs en el punt de desguàs. / Ruiz Pérez, G. (2016). On the use of satellite data to calibrate a parsimonious ecohydrological model in ungauged basins [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/72639

Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. The methods are trained with examples instead of explicitely designing the appearance of the visualization. This approach is exemplified using two applications. In the fist the problem to compute an image of the sky for dynamic weather, that is taking account of the current weather state, is addressed. It is a complicated problem to tie the appearance of the sky to a weather state. The method is trained with weather data sets and images of the sky to be able to synthesize a sky image for arbitrary weather conditions. The method has been trained with various kinds of weather and images data. The results show that this is a possible method to construct weather visaualizations, but more work remains in characterizing the weather state and further refinement is required before the full potential of the method can be explored. This approach would make it possible to synthesize sky images of dynamic weather using a fast and efficient empirical method. In the second application the problem of computing synthetic satellite images form numerical forecast data sets is addressed. In this case a mode is trained with preclassified satellite images and forecast data sets to be able to synthesize a satellite image representing arbitrary conditions. The resulting method makes it possible to visualize data sets from numerical weather simulations using synthetic satellite images, but could also be the basis for algorithms based on a preliminary cloud classification. / Report code: LiU-Tek-Lic-2004:66.

Obtaining an accurate estimate of a land-cover classifier's performance over a wide geographic area is a challenging problem due to the need to generate the ground truth that covers the entire area that may be thousands of square kilometers in size. The current best approach constructs a testing dataset by drawing samples randomly from the entire area --- with a human supplying the true label for each such sample --- with the hope that the selections thus made statistically capture all of the data diversity in the area. A major shortcoming of this approach is that it is difficult for a human to ensure that the information provided by the next data element chosen by the random sampler is non-redundant with respect to the data already collected. In order to reduce the annotation burden, it makes sense to remove any redundancies from the entire dataset before presenting its samples to a human for annotation. This dissertation presents a framework that uses a combination of clustering and compression to create a concise-set representation of the land-cover data for a large geographic area. Whereas clustering is achieved by applying Locality Sensitive Hashing (LSH) to the data elements, compression is achieved through choosing a single data element to represent a given cluster. This framework reduces the annotation burden on the human and makes it more likely that the human would persevere during the annotation stage. We validate our framework experimentally by comparing it with the traditional random sampling approach using WorldView2 satellite imagery.

Understanding the quality of the air we breathe is critical in quantifying the impact that atmospheric chemistry has on health. Poor air quality increases the risk of heart and lung diseases as well as having a detrimental effect on climate, ecology and the built environment. The burning of fossil fuels and plant matter (biomass burning) creates large quantities of gases and particulate matter that impact air quality and the air we breathe. Biomass burning is estimated to contribute 400 Tg of non-methane organic compounds, 40 Tg of methane and 7.1 Tg of nitrogen oxides to the atmosphere each year. This thesis aims to better understand the role of biomass burning on air quality and tropospheric chemistry. The in depth analysis presented here addresses of the impact of boreal biomass burning in North America on air quality, in particular, carbon monoxide (CO) and ozone (O3). By using a number of different modelling techniques along with data collected from a field campaign and satellites the transport and chemistry of biomass burning emissions were analysed and quantified. The first research chapter of the thesis used the GEOS-Chem atmospheric chemistry transport model to interpret aircraft measurements of CO in biomass burning outflow taken during the 2011 BORTAS-B campaign over Canada. The model has some skill reproducing the observed variability, but has a positive bias for observations < 100 ppb and a negative bias for observations > 300 ppb. It was found that observed CO variations are largely due to fires over Ontario, with smaller and less variable contributions from fossil fuel combustion from eastern Asia and NE North America. To help interpret observed variations of CO an effective physical age of emissions (¯A) metric was developed. It was found that during BORTAS-B the age of emissions intercepted over Halifax, Nova Scotia is typically 4–11 days, and on occasion as young as two days. The analysis shows that ¯A is typically 1–5 days older than the associated photochemical ages inferred from co-located measurements of different hydrocarbons. It is argued that a robust observed relationship between CO and black carbon aerosol during BORTAS-B (r² > 0.7), form the basis of indirect evidence that aerosols co-emitted with gases during pyrolysis markedly slowed down the plume photochemistry during BORTAS-B with respect to photochemistry at the same latitude and altitude in clear skies. The second research chapter focuses on O3 production downwind from boreal biomass burning. Using the GEOS-Chem model, the O3 chemistry within a biomass burning plume from a fire on 17 July 2011 in mid-Canada was examined. The model shows a significant positive bias (~20 ppb) in reproducingO3 mixing ratios over North America for July 2011 when compared to observations. Reducing NO emissions from lightning and fossil fuel by 50% and 54% respectively reduced this bias to ~10 ppb. The cause of the remaining bias is uncertain. Using a novel technique with the model, the centre of the biomass burning plume was tracked and O3 concentrations and chemistry was extracted from the centre of the plume. The biomass burning enhanced O3 concentrations throughout the plume by between 1 – 20 ppb when compared with the same plume path with no biomass burning. The plume was characterised as being NOx-rich for the initial four days of transport. The sensitivity of the O3 chemistry to different emissions was calculated and it was found that the O3 is initially highly sensitive to NO emissions from biomass burning and then to NO emissions from fossil fuels as it travels across an urban area surrounding Quebec City. The O3 net production was found to initially decrease with an increase in NO but increase further downwind. The final research chapter of the thesis uses long-term satellite observations to evaluate natural variability in CO concentrations over the North Atlantic. 15 years of MOPITT CO column observations were used along with modelled CO from the GEOS-Chem model. The model was evaluated against the MOPITT overpass and shows a negative bias of between -8% and -24% over the northern mid-latitudes with the largest bias seen in spring. The model has a large positive bias (8% – 40%) over the Amazon,West Africa and Indonesia through all seasons. Using Empirical Orthogonal Function (EOF) analysis on the MOPITT and GEOS-Chem CO columns shows the largest mode of variability seen in the North Atlantic to be the oxidation of methane for winter and spring, biomass burning during summer and fossil fuel combustion from East Asia during autumn.

To predict the performance of an electro-optical sensor system (EO-system) requires taking the weather situation into consideration. The possibility to use weather data from satellites instead of ground – and flight stations has been investigated. Nearly 170 satellites (about 10% of the functional satellites in orbit) were found to have atmosphere and weather monitoring. A method to select satellite data has been created based on three criteria: (1) the satellite should have a least one payload that measure a weather parameter for EO-system, (2) it should be possible to download data, free of charge, from the specified payload and (3) the satellite should cover geographical areas of interest for a potential user. The investigated performance property is the range, which is affected by many weather parameters, and focus has been on aerosols. The mean value for the aerosol extinction coefficient, for day- and nighttime conditions in December 2016, from the satellite CALIPSO’s lidar instrument Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) has been downloaded from www.earthdata.nasa.gov and implemented in a new developed application to predict the range for an EO-system. In the satellite data, from December 2016, it could be seen that the presence of aerosols, on a global scale, appears below 5 km and that the concentration of aerosols for nighttime condition is higher in local areas. For the test wavelength band of 0.9–2.5 µm, the application showed that the aerosol impact reduced the range by nearly 87%, if the EO-system was in a layer with aerosols. The application for the range prediction of EO-systems is on an early stage and need further development, especially its weather and scene parameters, to become a successful tool for a potential user in the future. / Att förutsäga prestandan hos ett elektro-optiskt sensorsystem (EO-system) kräver att man tar hänsyn till bland annat förhållandet i atmosfären. Möjligheten att använda väderdata från satelliter istället för mark- och flygstationer har undersökts. Det hittades nästan 170 satelliter (cirka 10% av de fungerande satelliterna i omloppsbana) med inriktning på atmosfär- och väderövervakning. En metod för att välja ut satellitdata har skapats som baseras på tre kriterier: (1) satelliten ska ha minst ett instrument som mäter en väderparameter för EO-system, (2) man ska, från internet, kunna ladda ner mätdata från det specifika instrumentet och (3) satelliten ska passera över ett område som är av intresse för en potentiell användare. Den prestandaegenskap som har undersökts är räckvidden, som påverkas av flera väderparametrar, där fokus har legat på inverkan från aerosoler. Medelvärdet för extinktionskoefficienten av aerosoler, för dag och natt i december 2016, från satelliten CALIPSO’s lidarinstrument Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) laddades ner från www.earthdata.nasa.gov och användes i en nyutvecklad applikation för att förutsäga räckvidden hos ett EO-system. Från satellitens mätningar i december 2016 kunde man se att förekomsten av aerosoler mestadels befann sig, globalt sett, uppdelat i olika lager under 5 km höjd och att koncentrationen av aerosoler är högre på natten i lokala områden. Applikationens beräkningar visade att förekomsten av aerosoler påverkade räckvidden för exempel våglängdsbandet 0.9–2.5 µm med en försämring upp till 87% när EO-systemet befann sig i ett skikt av aerosoler. Applikationen för att förutsäga räckvidden hos EO-system är i dess begynnelse och kräver vidareutveckling av både väder- och scenparametrar för att det ska bli ett framgångsrikt verktyg.

Dados de gravimetria e de altimetria por satélite foram usados como subsídio à análise morfoestrutural na região da Bacia de Pelotas-RS. Na abordagem gravimétrica foi usado o modelo geopotencial EGM2008 através das anomalias Bouguer e na abordagem batimétrica foi usado o modelo global DTU10BAT. Através dos mapas de anomalias Bouguer e perfis gravimétricos gerados, verificou-se que as anomalias Bouguer aumentam positivamente da costa em direção às maiores profundidades oceânicas, o que caracteriza um progressivo afinamento crustal associado à deriva continental. O comportamento das anomalias Bouguer obtidas por dados satelitais evidenciaram a presença de uma ruptura conhecida como Charneira Albo-aptiana na plataforma continental. A incidência de valores de anomalias significativamente positivas na região do Baixo de Mostardas sugere a presença de uma massa de maior densidade nesta região. A resolução dos dados gravimétricos utilizados não permitiu evidenciar a presença de paleocanais na região, sendo necessária uma maior resolução espacial, associada a outros métodos de investigação. O uso de dados de altimetria por satélite (modelo DTU10BAT) permitiu a análise batimétrica da plataforma continental e a investigação da configuração morfológica da região, que foi dividida em três faixas: Torres- Farol Solidão, Farol Solidão-Farol da Conceição e Farol da Conceição-Farol Sarita. Foi gerado um modelo teórico e comparado com o modelo DTU10BAT na geração do mapa de anomalias batimétricas. Os eixos de anomalias batimétricas negativas identificados estão frequentemente associados à direção de paleodrenagens, assim como as anomalias positivas tem relação com linhas de paleoestabilizações do nível do mar ou altos estruturais. Foi definida uma sequência de descontinuidades na altura do Farol da Conceição que apresentou expressiva coincidência com paleocanais delineados na mesma região através de outros estudos. Todos os dados foram processados e integrados em um sistema de informações geográficas. Os dados gravimétricos e batimétricos oriundos de missões satelitais são uma grande ferramenta nos estudos regionais para áreas que envolvam aplicações geológicas e mesmo oceanográficas. / Data from satellite altimetry and gravity were used to the morphostructural analysis in the Pelotas Basin-RS region. The EGM2008 geopotential model through the Bouguer anomalies was used in the gravimetric approach and the DTU10BAT global model was used in the bathymetric approach. Through the Bouguer anomalies maps and the gravimetric profiles that were generated, it was observed that Bouguer anomalies increase positively from coast towards to the major ocean depths, what characterizes a progressive crustal thinning associated with the continental drift. The behavior of the Bouguer anomalies obtained from satellite data showed the presence of a rupture, known as Charneira Albo-Aptiana, on the continental shelf. The incidence of significant positive anomalies values on the Baixo de Mostardas region suggests the presence of a higher-density mass in this region. Because of the resolution of the gravimetric data used in this research was not enough, it was not possible to show the presence of paleochannels in the region, requiring a greater spatial resolution data, associated with other methods of investigation. The use of satellite altimetric data (model DTU10BAT) allowed the bathymetric analysis of the continental shelf and the research of morphological configuration of the region, which was divided into three areas: Torres- Solidão Lighthouse, Solidão Lighthouse-Conceição Lighthouse and Conceição Lighthouse-Sarita Lighthouse. A theoretical model was generated and it was compared with the DTU10BAT model in the generation of the bathymetric anomalies map. The axes of negative bathymetric anomalies identified are often associated with the direction of paleochannels, as well as the positive anomalies are related to lines of sea level paleostabilizations or structural highs. It was defined a sequence of discontinuities at the Conceição Lighthouse proximities which presented a significant coincidence with paleochannels that were delineated in the same region through other studies. The data were processed and integrated in a geographic information system. Gravimetric and bathymetric data from satellite missions are an important tool in regional studies for areas that involve geological and oceanographic applications.