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Fakultäten
- Fakultät 12 / Institut für Technologie und Ressourcenmanagement in den Tropen und Subtropen (46) (entfernen)
Against the background of a worldwide decrease in the number of gauging stations,the estimation of river discharge using spaceborne data is crucial for hydrological research, rivermonitoring, and water resource management. Based on the at-many-stations hydraulic geometry(AMHG) concept, a novel approach is introduced for estimating river discharge using Sentinel-1time series within an automated workflow. By using a novel decile thresholding method, no a prioriknowledge of the AMHG function or proxy is used, as proposed in previous literature. With arelative root mean square error (RRMSE) of 19.5% for the whole period and a RRMSE of 15.8%considering only dry seasons, our method is a significant improvement relative to the optimizedAMHG method, achieving 38.5% and 34.5%, respectively. As the novel approach is embedded intoan automated workflow, it enables a global application for river discharge estimation using solelyremote sensing data. Starting with the mapping of river reaches, which have large differences inriver width overthe year, continuous river width time series are created using high-resolution andweather-independent SAR imaging. It is applied on a 28 km long section of the Mekong River nearVientiane, Laos, for the period from 2015 to 2018.
Chagas disease is a parasitic infection endemic to America, caused by the protozoan Trypanosoma cruzi and mainly transmitted to humans by contact with insect species of the Triatominae subfamily (Hemiptera). The disease is known to affect disproportionally rural impoverished human communities where it is known to cause premature death and is considered a social and economic burden. The Mexican government has made important progress into the detection, surveillance, treatment, and prevention of the disease in the last decades, however, Chagas disease has also been reported in areas where it had not been previously reported, and there are still barriers for access to treatment. In the state of San Luis Potosi, the disease is more studied in the east, nevertheless, it has been estimated that the reported cases of the entire state have been underestimated. New approaches to detect Chagas risk areas could help prioritize locations for Chagas disease education and prevention programs, detect cases of the disease in a timely manner, and provide access to the necessary treatments. The objective of this study was to identify risk areas for the transmission of Chagas disease in San Luis Potosí using species distribution modelling to estimate vectors and reservoirs’ distributions. To do this, firstly, important vectors and one reservoir species of T. cruzi were identified by reviewing their reported infection rates in literature and the number of times reported in Mexico. Next, species distribution models were calculated for the chosen vector and reservoir species present in the state. The models were done using the Maxent algorithm. Lastly, the resulting distribution models were combined into a risk map by thresholding the model outputs to produce binary predictions and then performing an overlap spatial analysis. Vector species were found to have suitable areas in 36.08% of the state’s territory while areas suitable for both vectors and reservoir were 7.4% of the state’s total area. While this figure may look small at first glance, the analysis suggests that 30% of the rural population and 52% of the urban population of the state are living in an area suitable for vectors and reservoir and therefore at risk. Species distribution modelling can be a powerful tool for identifying human populations at risk of contracting Chagas disease. In the future, including different species of reservoirs into the analysis could help to discover new risk areas in the state.
Wetlands offer different ecosystem services that contribute to human well-being (Kovács et al., 2015). According to the Ramsar Convention Secretariat (2018) wetland located in urban areas have been threatened by several activities such as drainage, pollution, encroachment, agriculture, among others. On the other hand, wetland degradation reduces the resilience of hazards like floods and storm surges (Kumar et al., 2017). For that reason, ecosystem-based disaster risk reduction (Eco-DRR) is an important strategy which enhances the conservation and restoration of ecosystems to reduce disaster risk aiming to sustainable development and resilience (Estrella & Saalismaa, 2013). Despite international recognition of the importance of wetlands, urban wetlands have diminished their capacity to cope with flood threats (Boyer and Polasky, 2006) due to the aforementioned human impacts.
That is why this thesis aimed to identify the role of urban wetlands in Bogota, Colombia, that has an urban wetland complex that is recognised as a Ramsar site in 2018. However, wetlands in the city reduced its area from 50.000 hectares to less than 800, approximately, in less than 40 years, mainly because of urban expansion and encroachment (IDIGER, 2018). To achieve this objective, an analysis of the city’s risk management framework was conducted, as well as a stakeholder analysis based on semi-structured interviews and a spatial-temporal analysis for the period 1998-2017, for which the Jaboque wetland was used as a case study. This wetland is located near the Bogotá River and is in the area threatened by flooding.
It was possible to determine that national and district policies on wetlands, biodiversity, and climate change adaptation address some ecosystem functions. Still, disaster risk reduction is not strongly linked to them. Thus, based on the case study, the wetlands in Bogota have not played a decisive role in flood risk management in the city.
Urbanization processes are one of the main factors for habitat loss and fragmentation, driving global biodiversity loss and species extinction. The neotropical Atlantic forest in Brazil is considered a global key biodiversity hotspot and used to be one of the most extensive forests of the Americas. Due to substantial deforestation over centuries, its landscape was transformed into a mosaic of small forest fragments surrounded by a predominantly agricultural matrix. Urban expansion and rural urbanization have created peri-urban zones, which still can harbor natural habitat remnants,
contributing to biological diversity and thus providing essential ecosystem services to urban and rural areas. The maintenance of such ecosystem services requires an understanding of the ecological processes in the ecosystem. A prerequisite for such an in-depth insight is the quantification of the underlying ecosystem functions. The ecosystem function pest control, a trophic interaction between insectivorous birds and herbivorous arthropods, was quantified in an empirical study using artificial caterpillars as prey models. This technique allows the identification of predator groups and the assessment of their predation rates. A total of 888 plasticine caterpillars were distributed at eight sites in secondary forest fragments surrounding the university campus of the federal university of São Carlos (UFScar) in peri-urban Sorocaba, southeastern Brazil. In sixteen point counts, 72 insect-eating birds, belonging to 19 species, were identified as possible artificial caterpillar attackers. Local habitat variables were measured to describe the forest vegetation structure and the landscape context. The study aimed to assess which structural components of the
forest fragments, together with the recorded bird community variables (abundance, richness, αdiversity), best explain the estimated predation rates by birds. The mean predation rate for birds was 8.25 ± 6.3 % for a reference period of eight days, representing the first quantification of the ecosystem function pest control for the study area. The three treatments of caterpillar placement heights (ground, stem: 0.5 -1.0 m, leaf: 1.5 - 2.0 m) were the best and only estimator to explain bird
predation rates. The little dense understory and ground vegetation might have facilitated the accessibility of artificial caterpillars, especially for carnivorous arthropods and birds. The detected contrast in their foraging and predation patterns suggests that arthropods and birds complement each other in their function of pest control. Bird predation rates were found to be negatively related to the vegetation structure. Thus, more open habitats, with less understory and low tree density, but high canopy cover and including dead trees were correlated with the highest predation rates and also exhibited more specialized forest-dependent bird species. This study confirms the importance of the maintenance of forest fragments in peri-urban areas, even if they are small, to preserve forest-associated birds, to contribute to the biological diversity on a broader scale, and to prevent the loss of ecosystem functions and services, mitigating some of the adverse effects of urbanization. Further investigation of the effect among the three treatments of caterpillar
placement on the predation rates is encouraged, including comparative studies among different habitat types. For future studies, it is recommended to model the avian community variables with the vegetation structure measures to predict habitat preferences of insectivorous birds. Therefore, the sampling of more units and on a bigger scale, including over a more extended period, is necessary to improve the robustness of the results, which could provide the basis for a monetary analysis of the ecosystem service pest control by birds.
Habitat loss due to land use and land cover change (LUCC) has been identified as the main cause of global environmental change, responsible for biodiversity decline and the deterioration of ecological processes. Habitat loss and fragmentation have been driven by
processes of LUCC such as deforestation, agricultural expansion and intensification, urbanization, and globalization. The objective of this research was to determine the effects of LUCC on the process of habitat loss and the patterns of fragmentation in the surrounding landscape of the Pacuare Reserve (PR) in the Caribbean lowlands of Costa Rica. The PR is a protected area of 800 ha surrounded by an agricultural landscape with a history of over 150 years of bananas monocultures. Landsat satellite images from 1978 to 2020 were used to conduct a temporal analysis of LUCC around the PR. Patterns of change were explored using landscape metrics from the land classification images. To explore potential connectivity routes, the least cost path analysis was used to connect the PR to other protected areas. Overall, forest cover decreased in the study area at a rate of -4.8% per year during the period of 1992-1997. In the year 2001 it reached its lowest cover and then increased at a mean annual rate of 1.6%. A mean overall accuracy of 92% was obtained for the land classification process. A clear fragmentation process was observed, as shown by a decreased in forest mean patch area and largest patch index and by the increase in patch density. Although forest cover increased in the last decade, fragmentation metrics suggest this recover happened in a spatially scattered manner, due to agricultural land abandonment. Connectivity maps showed the importance of forest fragments and of the already established biological corridors for the movement of species to and from the PR, however it also evidenced the lack of connectivity between the coastal forest fragments and further inside the country located protected areas, as well as the need to promote reforestation projects, particularly between fragments of the corridors identified.
This research analyzes the effects that eco-labels have on the demand for organic (Bio) and Fairtrade (FT) food products. The thesis also discusses the individual determinants and motivations behind those effects. The analysis builds on data obtained from a self-programmed and self-conducted survey, with a sample of 869 students from different universities of Cologne, Germany. The Bio/FT preference is measured experimentally by randomly assigning individuals to treatment and control groups. The experiment simulates life decisions using actual pictures and prices of four products: packed and processed spaghetti, fresh tomatoes, packed raw meat, and packed orange juice.
The existence, size, and direction of statistically significant eco-label effects were obtained with two sample tests of proportions. The results prove that the FT label has a positive differential effect on consumer’s demand. The presence of the FT label makes the purchase of this juice 9.1% higher than other juices not labeled as FT. This finding confirms the hypothesis that eco-labels have a positive effect on sustainable consumption. A surprising finding is that the presence of the Bio label lowers the purchase of organic pasta and tomatoes 7.7% and 9.4% respectively. This finding is interesting because it suggests that Bio labels are not driving the demand for sustainable tomatoes or pasta for this population. Regional and cheaper alternatives are preferred by consumers in this cases.
The motivations behind consumer choices of different options were thoroughly analyzed. Binomial logistic regressions and qualitative text analysis show that the variance in the intention to consume eco-labeled food is explained mainly by price concerns and attitudes about value for money, but also by the influence of life partners as shopping referents, and the perceived behavioral controls of time and ability to monitor compliance of label standards, thus trust them.
The final remarks support the use of the Fairtrade eco-label as a market-based instrument to guide sustainable food consumption among young adults in this context, and propose changes that could make the Bio label more attractive for the targeted population. The thesis demonstrates which individual factors should be inevitably considered when implementing labeling to foster sustainable consumption. Hence, it is useful for evaluations of public and private certification schemes, and for companies that support sustainable food markets. Projects looking to understand and drive sustainable production and consumption decisions should consider this reading.
Water security is a major concern for water-scarce cities that face dynamic water challenges due to limited water supply, climate change and increasing water demand. Framing urban water security is challenging due to the complexity and uncertainties of the definitions and assessment frameworks concerning urban water security. Several studies have assessed water security by granting priority indicators equal weight without considering or adapting to the local conditions. This study develops a new urban water security assessment framework with application to the water-scarce city
of Madaba, Jordan. The study applies the new assessment framework on the study area and measures urban water security using the integrated urban water security index (IUWSI) and the analytic hierarchy process (AHP) as a decision management tool to prioritise and distinguish indicators that affect the four dimensions of urban water security: drinking water, ecosystems, climate change and water-related hazards, and socioeconomic aspects (DECS). The integrated urban water security index (IUWSI) highlights the state of water security and intervention strategies in Madaba. The study reveals that urban water security in Madaba is satisfactory to meet basic needs, with shortcomings in some aspects of the DECS. However, Madaba faces poor security in terms of managing climate- and water-related risks. The IUWSI framework assists with a rational and evidence-based decision-making process, which is important for enhancing water resources management in water-scarce cities.
Proper satellite-based crop monitoring applications at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions Sentinel 2 (ESA) and Landsat 7/8 (NASA) provides this unprecedented opportunity at a global scale; however, this is rarely implemented because these procedures are data demanding and computationally intensive. This study developed a robust stream processing for the harmonization of Landsat 7, Landsat 8 and Sentinel 2 in the Google Earth Engine cloud platform, connecting the benefit of coherent data structure, built-in functions and computational power in the Google Cloud. The harmonized surface reflectance images were generated for two agricultural schemes in Bekaa (Lebanon) and Ninh Thuan (Vietnam) during 2018–2019. We evaluated the performance of several pre-processing steps needed for the harmonization including the image co-registration,
Bidirectional Reflectance Distribution Functions correction, topographic correction, and band adjustment. We found that the misregistration between Landsat 8 and Sentinel 2 images varied from 10 m in Ninh Thuan (Vietnam) to 32 m in Bekaa (Lebanon), and posed a great impact on the quality of the final harmonized data set if not treated. Analysis of a pair of overlapped L8-S2 images over the Bekaa region showed that, after the harmonization, all band-to-band spatial correlations were greatly improved. Finally, we demonstrated an application of the dense harmonized data set for crop mapping and monitoring. An harmonic (Fourier) analysis was applied to fit the detected unimodal, bimodal and trimodal shapes in the temporal NDVI patterns during one crop year in Ninh Thuan province. The derived phase and amplitude values of the crop cycles were combined with max-NDVI as an R-G-B false composite image. The final image was able to highlight croplands in bright colors (high phase and amplitude), while the non-crop areas were shown with grey/dark (low phase and amplitude). The harmonized data sets (with 30 m spatial resolution) along with the Google Earth Engine scripts used are provided for public use.
Ecosystems provide a wide range of goods, services or ecosystem services (ES) to society. Estimating the impact of land use and land cover (LULC) changes on ES values (ESV) is an important tool to support decision making. This study used remote sensing and GIS tools to analyze LULC change and transitions from 2001 to 2016 and assess its impact on ESV in a tropical forested landscape in the southern plains of Nepal. The total ESV of the landscape for the year 2016 is estimated at USD 1264 million year−1. As forests are the dominant land cover class and have high ES value per hectare, they have the highest contribution in total ESV. However, as a result of LULC change (loss of forests, water bodies, and agricultural land), the total ESV of the landscape has declined by USD 11 million year−1. Major reductions come from the loss in values of climate regulation, water supply, provision of raw materials and food production. To halt the ongoing loss of ES and maintain the supply and balance of different ES in the landscape, it is important to properly monitor, manage and utilize ecosystems. We believe this study will inform policymakers, environmental managers, and the general public on the ongoing changes and contribute to developing effective land use policy in the region.
Life cycle assessment is a crucial tool in evaluating systems performances for sustainability and decision-making. This paper provided environmental impact of integrating renewable energy systems to the utility-grid based on a baseline optimized energy production data from “HOMER” for renewable systems modelling of a site in northern Nigeria. The ultimate goal was to ascertain the best hybrid option(s) in sustaining the environment. Different assumptions and scenarios were modelled and simulated using Ganzleitlichen Bilanz (GaBi). Uncertainty analysis was ensured to the impact data based on pedigree-matrix and Excel-program, as well as overall policy relevance. The results of the impact categories revealed first scenario (i.e., conventional path-based) with the highest impacts on global warming potential (GWP), acidification potential (AP), human toxicity potential (HTP), and abiotic depletion potential (ADP fossils). The lowest impacts arise in
the renewable-based scenarios for all the considered categories except the Ozone-layer depletion potential Category where the highest contribution falls in the third scenario (i.e., photovoltaic (PV)/biomass-biogas system) although all values being infinitesimal. In quantitative terms, the reduction in the GWP from the highest being the first scenario to the lowest being the fourth scenario (i.e., wind/biomass-biogas system) was 96.5%. Hence, with the outstanding contributions of the hybrid renewable systems, adopting them especially the lowest impact scenarios with expansions is relevant for environmental sustainability.