Our country is a risky position in terms of natural disasters. In the long run, preferentially settlement areas were selected to ensure maximum benefits in terms of both economic and security aspects, other criteria is not taken account when selection of sites. The main purpose of this study is to examine and compare the properties of settlement location based on natural hazard and environmental constraints to be able to understand the interaction between the settlements and natural conditions at the regional scale of YeSilirmak Basin. A MCDA was set up with 10 different data layers in two data domains (environmental and natural hazards domains), are evaluated. The results of the MCDA scores are then transferred to settlement databases in order to evaluate the number of existing settlements in different environmental and natural hazard related suitability classes. It is found that almost 29% of YeSilirmak catchment is environmentally favorable for settlement, and in coherence with that 41% of all existing settlements are located in this zone, indicating a clear preference among the perception of environmentally better places to be settled in. On the other hand with respect to the natural hazards dataset, the locations of the settlements fail to create any preference, as 73,32% of the area is used by 73,50% of existing settlements, which indicates that the perception of natural hazards are low and do not effect settlement criteria, while the acceptable risk of community is high.

Protected area site selection is generally carried out using biodiversity data as surrogates. However, reliable and complete biodiversity data is rarely available due to limited resources, time and equipment. Instead of drawing on inadequate biodiversity data, an alternative is to use environmental diversity (ED) as a surrogate in conservation planning. However, there are few studies that use environmental diversity for site selection or that evaluates its efficiency / unfortunately, no such example exists for Turkey, where biodiversity is high but our knowledge about it is unsatisfactory. Hence, this study was carried out to investigate the efficiency of environmental surrogates and the utility of different biological taxa in conservation planning. The objective was to find out the most efficient surrogates, either environmental or biological, for conservation planning, so that limited resources can be used more efficiently to establish an effective protected areas network. The study was carried out in northeastern Turkey, within the Lesser Caucasus ecoregion. The taxonomic groups considered include large mammals, breeding birds, globally threatened reptiles and amphibians, butterflies, highly threatened plants, and ecological communities. The distribution data was taken from a previous study, while climate and topographical data were obtained from various sources and produced through spatio-statistical techniques. Complementarity-based site selection was carried out with Marxan software, where the planning unit was the 100 sq.km. UTM grid square. Various statistical methods, including geographically weighted regression, principal components analysis, and p-median algorithm, were used to determine ED across the units. Performance of different approaches and different sets of surrogates were tested by comparing them to a random null model as well as representation success. Results indicate that endemic or non-endemic highly threatened plant species, butterfly species and ecological communities represent biodiversity better than other taxa in the study area. As such, they can be used on their own as efficient biodiversity surrogates in conservation area planning. Another finding is that highly threatened plant species are required to be used in the site selection process if they need to be represented well / in other words, they are their own surrogates. It was demonstrated that while ED alone can be used as a surrogate to represent biodiversity of an area, they are not as good as biodiversity surrogates themselves. It is also suggested that using species taxa with smaller distributional ranges or taxa that complement each other due to ecological differences as surrogates provide better results. On the other hand, ED might be a more suitable surrogate if resources are very limited or field work is impossible. In such cases, using ED in conjunction with one of the better biodiversity surrogates is probably the best solution.

In urbanized areas, building and transportation systems generally comprise the majority of greenhouse gas (GHG) emissions and energy consumption. Realization of global environmental sustainability depends upon efficiency improvements of building and transportation systems in the built environment. The selection of efficient buildings and locations can help to improve the efficient utilization of transportation and building systems. Green building design and rating frameworks provide some guidance and incentive for the development of more efficient building and transportation systems. However, current frameworks are based primarily on prescriptive, component standards, rather than performance-based, whole-building evaluations. This research develops a commercial building/site evaluation framework for the minimization of GHG emissions and energy consumption of transportation and building systems through building/site selection. The framework examines, under uncertainty, multiple dimensions of building/site operation efficiencies: transportation access to/from a building site; heating, ventilation, air conditioning, and domestic hot water; interior and exterior lighting; occupant conveyances; and energy supply. With respect to transportation systems, the framework leverages regional travel demand model data to estimate the activity associated with home-based work and non-home-based work trips. A Monte Carlo simulation approach is used to quantify the dispersion in the estimated trip distances, travel times, and mode choice. The travel activity estimates are linked with a variety of existing calculation resources for quantifying energy consumption and GHG emissions. With respect to building systems, the framework utilizes a building energy simulation approach to estimate energy consumption and GHG emissions. The building system calculation procedures include a sensitivity analysis and Monte Carlo analysis to account for the impacts of input parameter uncertainty on estimated building performance. The framework incorporates a life cycle approach to performance evaluation, thereby incorporating functional units of building/site performance (e.g energy use intensity). The evaluation framework is applied to four case studies of commercial office development in the Atlanta, GA metropolitan region that represent a potential range of building/site alternatives for a 100-employee firm in an urbanized area. The research results indicate that whole-building energy and GHG emissions are sensitive to building/site location, and that site-related transportation is the major determinant of performance. The framework and findings may be used to support the development of quantitative performance evaluations for building/site selection in green building rating systems and other efficiency incentive programs designed to encourage more efficient utilization and development of the built environment.

A forced landing for an Unmanned Aerial Vehicle (UAV) is required if there is an emergency on board that requires the aircraft to land immediately. Piloted aircraft in the same scenario have a human on board that is able to engage in the complex decision making process involved in the choice of a suitable landing location. If UAVs are to ever fly routinely in civilian airspace, then it is argued that the problem of finding a safe landing location for a forced landing is an important unresolved problem that must be addressed. This thesis presents the results of an investigation into the feasibility of using machine vision techniques to locate candidate landing sites for an autonomous UAV forced landing. The approach taken involves the segmentation of the image into areas that are large enough and free of obstacles; classification of the surface types of these areas; incorporating slope information from readily available digital terrain databases; and finally fusing these maps together using a high level set of simple linguistic fuzzy rules to create a final candidate landing site map. All techniques were evaluated on actual flight data collected from a Cessna 172 flying in South East Queensland. It was shown that the use of existing segmentation approaches from the literature did not provide the outputs required for this problem in the airborne images encountered in the gathered dataset. A simple method was then developed and tested that provided suitably sized landing areas that were free of obstacles and large enough to land. The advantage of this novel approach was that these areas could be extracted from the image directly without solving the difficult task of segmenting the entire image into the individual homogenous objects. A number of neural network classification approaches were tested with the surface types of candidate landing site regions extracted from the aerial images. A number of novel techniques were developed through experimentation with the classifiers that greatly improved upon the classification accuracy of the standard approaches considered. These novel techniques included: automatic generation of suitable output subclasses based on generic output classes of the classifier; an optimisation process for generating the best set of input features for the classifier based on an automated analysis of the feature space; the use of a multi-stage classification approach; and the generation of confidence measures based on the outputs of the neural network classifiers. The final classification result of the system performs significantly better than a human test pilot's classification interpretation of the dataset samples. In summary, the algorithms were able to locate candidate landing site areas that were free of obstacles 92.3 ±2.6% (99% confidence in the result) of the time, with free obstacle candidate landing site areas that were large enough to land in missed only 5.3 ±2.2% (99% confidence in the result) of the time. The neural network classification networks developed were able to classify the surface type of the candidate landing site areas to an accuracy of 93.9 ±3.7% (99% confidence in the result) for areas labelled as Very Certain. The overall surface type classification accuracy for the system (includes all candidate landing sites) was 91.95 ±4.2% (99% confidence in the result). These results were considered to be an excellent result as a human test pilot subject was only able to classify the same data set to an accuracy of 77.24 %. The thesis concludes that the techniques developed showed considerable promise and could be used immediately to enhance the safety of UAV operations. Recommendations include the testing of algorithms over a wider range of datasets and improvements to the surface type classification approach that incorporates contextual information in the image to further improve the classification accuracy.

No description available.

The lack of safe drinking water worldwide has drawn the attention of decision makers to riverbank filtration (RBF) for its many advantages in purifying surface water. This study provides an overview of the hydrogeologic, fluvial, and environmental influences on the performance of RBF systems and aims to develop a model for RBF site selection. Using multi-attribute utility theory (MAUT), this study structured the RBF siting problem and assessed a multiplicative utility function for the decision maker. In a case study, geostatistical methods were used to acquire the necessary data and geographic information systems (GIS) were used to screen sites suitable for RBF implementation. Those suitable sites were then evaluated and ranked using the multi-attribute utility model. The result showed that sites can be identified as most preferred among the selected suitable sites based on their expected utility values. This study definitively answers the question regarding the capability of MAUT in RBF site selection. Further studies are needed to verify the influences of the attributes on the performance of RBF systems.:Abstract iii Zusammenfassung iv Acknowledgments v Table of Contents vi List of Tables viii List of Figures x Definition of terms xiii 1. Abbreviations xiii 2. Symbols xiii Part I Introduction 1 1. Introduction 2 2. Statement of purpose 2 3. Research questions 3 4. Overview of methodology 3 5. Organization of the dissertation 3 Part II Fundamentals and Literature Review 5 1. The definition of bank filtration 6 2. The Significance of RBF 7 2.1 RBF in drinking water supply 7 2.2 Benefits of RBF for China 14 3. RBF Site Selection 19 3.1 RBF site selection model 20 3.2 Definition of successful RBF sites 24 4. Factors Affecting RBF Site Selection 26 4.1 River hydrology/hydraulics 27 4.2 Geology 28 4.3 Land cover 36 4.4 Well field location 36 4.5 Water quality 37 4.6 Aquifer properties 38 4.7 Distance to river 41 4.8 Riverbed characteristics 43 5. Effect of Clogging on Yield 46 6. Summary 51 Part III Developing a Multi-attribute Utility Model for RBF Site Selection 53 1. Introduction 54 2. Objectives and Attributes 54 3. Assessment of the Utility Function 57 3.1 Investigation of the qualitative preference structure 58 3.2 Assessment of component utility function 62 3.3 Assessment of the scaling constants 63 4. Results 67 5. Discussion 69 6. Summary 74 Part IV Case Study 75 1. Introduction 76 2. Materials and Methods 78 2.1 GIS data collection 78 2.1.1 Geologic data 79 2.1.2 Land cover data 79 2.1.3 Groundwater quality data 80 2.1.4 Aquifer properties data 80 2.1.5 Surface water area data 80 2.1.6 Surface water quality data 81 2.1.7 Streambed material data 81 2.2 Kriging the saturated thickness 91 2.3 Aggregation of all constraint maps 103 3. Results 105 3.1 Kriging 105 3.2 Suitable sites 105 4. Discussion 109 4.1 A discussion of the kriging results 109 4.2 A discussion of the multi-attribute utility model results 117 5. Summary 122 Part V Conclusions and Recommendations 123 1. Conclusion and Recommendation 124 Appendix 1 Environmental quality standards for surface water (GB 3838-2002) 125 Appendix 2 Quality standard for groundwater (GB14848-93) 127 Appendix 3 Explanation to Germany’s RBF site location data 130 Appendix 4 Layer information of drillings 133 Appendix 5 Streambed materials used by Schälchli (1993) 141 Appendix 6 Interview and questionnaires 143 Appendix 7 Surface water area of Jilin City 150 Bibliography 152

Insular fauna face disproportionate risks of extinction owing to direct human perturbation and intrinsic factors that are enhanced at small population sizes. Currently, our understanding of the processes that promote long-term persistence of naturally small populations and the cryptic processes that may contribute to accelerating their decline is limited by lack of empirical investigations across the range of natural conditions. Implementing effective protections for rare and understudied taxa requires the identification and examination of factors that limit recruitment at critical life stages. Predicting population health outcomes of future perturbations further necessitates an understanding a taxon’s behavioral ecology. Finally, cryptic threats to viability, such as inbreeding depression, must be investigated with an appreciation for taxon-specific life history, as these attributes can alter the context in which severe fitness reductions are expressed. In this project I enlist integrative and cross-disciplinary approaches to study the behavioral ecology and conservation genetics of a critically endangered West Indian Rock Iguana, Cyclura nubila caymanensis, on Little Cayman Island. I demonstrate how coastal communal nesting areas, a critical limiting resource on the island, serve a diverse population demographic and contribute to significantly enhanced nesting outcomes. These data emphasize the importance of expanding protections for major sites, as aggregative nesting appears to be perpetuated by both habitat suitability and adaptive fitness benefits. I next evaluate the possibility of evolved inbreeding avoidance strategies, including natal dispersal, non-assortative mate choice, and genetic bet-hedging. I conclude that the contribution of pre-reproductive dispersal to inbreeding avoidance likely outweighs that of active mate choice. Importantly, observed patterns of siring success imply constrained female choice and sexual conflict over genetic mating outcomes – a pattern that may extend to many territorial, male-driven mating systems and therefore should be an important consideration in genetic management. Finally, I investigate age-dependent inbreeding effects and the degree to which inbreeding depression may limit recruitment to the breeding population. I fail to reveal significant correlations of multi-locus heterozygosity with hatchling fitness; however, negative effects of parental inbreeding on fecundity and hatching success imply fitness consequences of inbreeding depression could be felt at other life stages.

The Swedish Red Cross (SRK) plays an important humanitarian role by selling donated clothes in order to collect more money to help people in need. An extended network of 251 second-hand stores is built nationwide, where donors leave their clothes and buyers can buy them at competitive prices. However, an amount of these clothes remain unsold and ends up being shipped to textile recycling centers. The organization plans to build some Regional Sorting Facilities, where a careful sorting will take place and the clothes will be stored, until they will be redistributed to other stores within thecountry.This project aims to find the optimal number and location of these facilities in a way that the transportation cost from stores to facilities is minimized. SRKs Logistics Department operationalizes this aim to the following objective: place a minimum number of facilities such that at least 50% of the stores or 50% of the produced revenues are reached in less than 90 minutes of driving time. Thus, modern GIS software is used in a Location-Allocation analysis to solve the p-median problem. The core of the methodology in this thesis is the well known Vertex Substitution heuristic algorithm (Teitz & Bart).Empirical evaluations of seven (7) scenarios comprised of optimally placing an increasing number of facilities from one (1) to seven (7) reveal that five (5) facilities is sufficient to meet the operational objective with the minimal number of resources/facilities. The solutions for all scenarios are analyzed in terms of statistics (Key Performance Indicators) and are illustrated on maps.

No description available.

The Kittlitz's murrelet (Brachyramphus brevirostris) is a rare member of the seabird family Alcidae that breeds in coastal areas of Alaska and Beringian Russia. The species belongs to the genus Brachyramphus, an unusual seabird taxon in which all three extant species nest non-colonially, situating their nests up to 75 km inland from coastal marine waters. This nesting strategy is different from that of most seabird species, which tend to nest colonially on remote islands or sea cliffs, where terrestrial predators are generally absent or cannot easily access nests. Within the genus Brachyramphus, Kittlitz's murrelet is notable because a majority of the global population appears to nest on the surface of the ground in rocky alpine habitat near inland or tidewater glaciers, foraging in adjacent marine waters influenced by glacial outflows. The unusual nesting habits of Kittlitz's murrelet have made the study of its nesting ecology difficult, and gaps therefore exist in our understanding of the species' breeding biology. Kittlitz's murrelet populations have declined substantially in core areas of its range, causing the U. S. Fish and Wildlife Service to designate the species as a candidate for protection under the Endangered Species Act. A better understanding of Kittlitz's murrelet nesting ecology is crucial for determining potential causes of these declines and for future management of the species. To this end, I studied Kittlitz's murrelet breeding ecology and nest site selection during 2008-2011 on Kodiak Island, Alaska, in an unglaciated area that was recently found to have large numbers of accessible nests. I and my colleagues found 53 active Kittlitz's murrelet nests in inland scree-dominated habitats and placed remote, motion-sensing cameras at 33 nests. Adults exchanged incubation duties at the nest every 24 or 48 h, almost exclusively during early morning twilight. Following hatching of eggs, parents provisioned their single nestling with an average of 3.9 to 4.8 fish per day, depending on the year. Parental visits to the nest during chick-rearing occurred primarily after sunrise in the early to mid-morning hours, and during evening twilight. Fish were delivered singly to the chick, and Pacific sand lance (Ammodytes hexapterus), a high-lipid forage fish, accounted for about 92% of all identifiable chick meal deliveries. Chick growth rates were high relative to confamilial species, consistent with the high quality of chick diets; the logistic growth rate constant (K) was 0.291, greater than that for any other semi-precocial alcid. Chicks fledged an average of 24.8 d after hatching and asymptotic chick body mass averaged about 135.5 g, approximately 58% of adult body mass. Age at fledging, asymptotic chick body mass (% adult mass), and the number of meal deliveries required to fledge a chick were all lower than or as low as any other species of semi-precocial alcid. The average estimated nest survival rate during 2008-2011 was 0.093 (95% CI = 0.01–0.30), which is extremely low compared to other species in the family Alcidae, and is almost certainly insufficient to sustain a stable population. The primary causes of nest failure were depredation (47% of total nest fates), mostly by red foxes (Vulpes vulpes), and unexplained nestling mortality on the nest (21% of nest fates). Saxitoxin and/or pathogenic endoparasite burdens were observed in five of six necropsied chick carcasses, suggesting possible causes for chick mortality not directly attributable to predation. Habitat characteristics of Kittlitz's murrelet nest sites differed significantly from unused sites at several scales. At a small scale (within 5 m of the nest), nest sites had a lower percent coverage of vegetation and higher percent coverage of intermediate-sized rocks (5–30 cm diameter), compared to randomly selected unused sites. Nest sites were also located on steeper, more north-facing slopes compared to randomly selected sites. Nest sites also had a lower percent coverage of vegetation than randomly-selected sites at larger scales (within 25 m and 50 m of the nest site). Nest sites were located significantly farther from the edge of densely-vegetated habitats than random sites. There was no evidence that nest sites were different from randomly-selected sites in terms of elevation, proximity to ridgelines, or proximity to the open ocean, although a low degree of variation within the study area for these habitat characteristics may have precluded detection of potential differences. Nest survival rates did not co-vary with slope, percent vegetation coverage, distance from vegetated edges, or percent cover of intermediate-sized rocks; however, this result may be an artifact of a limited sample size. The results of this thesis will provide managers with a better understanding of the factors that may limit Kittlitz's murrelet nesting success, such as nest predation and forage fish availability, as well as factors that may influence the quality and distribution of Kittlitz’s murrelet nesting habitat in the future, given on-going and progressive climate change. / Graduation date: 2013