With increased degradation of natural resources due to land use decisions and the subsequent loss of biodiversity across large spatial scales, there is a need for a Spatial Decision Support System (SDSS) which showcases the impacts of developments on terrestrial and aquatic ecosystems. The Gap Analysis Program (GAP) and a Bayesian Belief Network (BBN) were used to assess the impacts of an impoundment in the Bienville National Forest, Smith County, Mississippi on landcovers, threatened and endangered species, species richness and fish populations. A test impoundment site was chosen on Ichusa Creek and using GAP data, landcovers, species and species richness were compared with those of Bienville National Forest, Smith County, Mississippi. For the aquatic analysis, a BBN model was developed for each fish so that population probabilities could be calculated using a given configuration of available habitats and compared to current fish population.

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Abstract. BIM (Building Information Model) and GIS (Geographic Information System) have been rapidly developed in recent years due to their respective strengths in projects. But these two systems are totally different on focus, reference systems and data storage. With the increasing discussion about integrated BIM-GIS and technologies development, application fields, solutions and challenges are continuously updated and developed. However, the actual application of BIM and GIS integration has not been better implemented because it is restricted to certain extent by different regions, different projects and certain technical constraints. To better explore the integration of BIM and GIS, this paper reviews the development progress of BIM and GIS integration, the exiting integration methods at data level, process level and application level, and the remaining integrated challenges through the studies of 43 relevant research articles, and analyzes the actual situation of integration application through the results of questionnaire. Based on the literature review and a questionnaire, there are still technical problems in BIM-GIS integration including transformation accuracy, semantic simplification and geometric information filtering and so on, and integrated BIM-GIS is currently rarely used in the AEC industry. But due to the benefits of the integration, there is no doubt that integrated BIM-GIS system can bring significant value to the AEC industry.

Disasters, whether natural or man-made have become an issue of mounting concern all over the world. Natural disasters such as floods, earthquakes, landslides, cyclones, tsunamis and volcanic eruptions are yearly phenomena that have devastating effect on infrastructure and property and in most cases, results in the loss of human life. Floods are amongst the most prevalent natural disasters. The frequency with which floods occur, their magnitude, extent and the cost of damage are escalating all around the globe. Accra, the capital city of Ghana experiences the occurrence of flooding events annually with dire consequences. Past studies demonstrated that remote sensing and geographic information system (GIS) are very useful and effective tools in flood risk assessment and management.  This thesis research seeks to demarcate flood risk areas and create a flood risk map for the Greater Accra Metropolitan Area using remote sensing and Geographic information system. Multi Criteria Analysis (MCA) is used to carry out the flood risk assessment and Sentinel-1A SAR images are used to map flood extend and to ascertain whether the resulting map from the MCA process is a close representation of the flood prone areas in the study area.  The results show that the multi-criteria analysis approach could effectively combine several criteria including elevation, slope, rainfall, drainage, land cover and soil geology to produce a flood risk map. The resulting map indicates that over 50 percent of the study area is likely to experience a high level of flood.  For SAR-based flood extent mapping, the results show that SAR data acquired immediately after the flooding event could better map flooding extent than the SAR data acquired 9 days after.  This highlights the importance of near real-time acquisition of SAR data for mapping flooding extent and damages.  All parts under the study area experience some level of flooding. The urban land cover experiences very high, and high levels of flooding and the MCA process produces a risk map that is a close depiction of flooding in the study area.  Real time flood disaster monitoring, early warning and rapid damage appraisal have greatly improved due to ameliorations in the remote sensing technology and the Geographic Information Systems.

Building facades, serving mainly to protect occupants and structural components from natural forces, require periodic inspections for the detection and assessment of building façade anomalies. Over the past years, a growing trend of utilizing camera-equipped drones for periodical building facade inspection has emerged. Building façade anomalies, such as cracks and erosion, can be detected through analyzing drone-captured video, photographs, and infrared images. Such anomalies are known to have an impact on various building performance aspects, e.g., thermal, energy, moisture control issues. Current research efforts mainly focus on the design of drone flight schema for building inspection, 3D building model reconstruction through drone-captured images, and the detection of specific façade anomalies with these images. However, there are several research gaps impeding the improvement of automation level during the processes of building façade inspection with UAV (Unmanned Aerial Vehicle). These gaps are (1) lack effective ways to store multi-type data captured by drones with the connection to the spatial information of building facades, (2) lack high-performance tools for UAV-image analysis for the automated detection of building façade anomalies, and (3) lack a comprehensive management (i.e., storage, retrieval, analysis, and display) of large amounts and multi-media information for cyclic façade inspection. When seeking inspirations from nature, the process of drone-based facade inspection can be compared with caching birds' foraging food through spatial memory, visual sensing, and remarkable memories. This dissertation aims at investigating ways to improve the management of UAV-captured data and the automation level of drone-based façade anomaly inspection with inspirations from caching birds' foraging behavior. Firstly, a 2D spatial model of building façades was created in the geographic information system (GIS) for the registration and storage of UAV-images to assign façade spatial information to each image. Secondly, computational methods like computer vision and deep learning neural networks were applied to develop algorithms for automated extraction of visual features of façade anomalies within UAV-captured images. Thirdly, a GIS-based database was designed for the comprehensive management of heterogeneous inspection data, such as the spatial, multi-spectral, and temporal data. This research will improve the automation level of storage, retrieval, analysis, and documentation of drone-captured images to support façade inspection during a building's service lifecycle. It has promising potential for supporting the decision-making of early-intervention or maintenance strategies to prevent façade failures and improve building performance. / Doctor of Philosophy / Building facades require periodic inspections and maintenance to protect occupants and structures from natural forces like the sun, wind, rain, and snow. Over the past years, a growing trend of utilizing drones for periodical building facade inspection has emerged. Building façade anomalies, such as cracks and corrosion, can be detected from the drone-captured photographs or video. Such anomalies are known to have an impact on various building performance aspects, such as moisture issues, abnormal heat loss, and additional energy consumptions. Existing practices for detecting façade anomalies from drone-captured photographs mainly rely on manual checking by going through numerous façade images and repetitively zooming in and out these high-resolution images, which is time-consuming and labor-intensive with potential risks of human errors. Besides, this manual checking process impedes the management of drone-captured data and the documentation of façade inspection activities. At the same time, the emerging technologies of computer vision (CV) and artificial intelligence (AI) have provided many opportunities to improve the automation level of façade anomaly detection and documentation. Previous research efforts have explored the image-based generation of 3D building models using computer vision techniques, as well as image-based detection of specific anomalies using deep learning techniques. However, few studies have looked into the comprehensive management, including the storage, retrieval, analysis, and display, of drone-captured images with the spatial coordinate information of building facades; there is also a lack of high-performance image analytics tools for the automated detection of building façade anomalies. This dissertation aims at investigating ways to improve the automation level of analyzing and managing drone-captured images as well as documenting building façade inspection information. To achieve this goal, a building façade model was created in the geographic information system (GIS) for the semi-automated registration and storage of drone-captured images with spatial coordinates by using computer vision techniques. Secondly, deep learning was applied for automated detection of façade anomalies in drone-captured images. Thirdly, a GIS-based database was designed as the platform for the automated analysis and management of heterogeneous data for drone-captured images, façade model information, and detected façade anomalies. This research will improve the automation level of drone-based façade inspection throughout a building's service lifecycle. It has promising potential for supporting the decision-making of maintenance strategies to prevent façade failures and improve building performance.

A comprehensive, distributed parameter, annual, watershed nonpoint source management system (WATNPS) was developed for land management planning. WATNPS simulates annual sediment, nitrogen (chemical and livestock organic), and phosphorus (chemical and livestock organic) yields from nonpoint sources. The system is linked to a GIS platform to reduce the input required by personnel during analysis. WATNPS predicts potential impacts of land management practices on surface water quality. Data were compiled for the Middle Fork Holston River (MFHR) drainage basin, Owl Run and Nomini Creek watersheds in Virginia. WATNPS utilizes annual screening models for the prediction of pollutant yields. Overland delivery ratio, phosphorus yield, and animal waste models were modified for use in the system. In-stream delivery ratio, and pollutant routing procedures were developed as a part of the overall system functionality. Development and calibration of individual in-stream delivery ratio parameters was performed based on single year data from Nomini Creek and Owl Run. A procedure was developed to rank individual watersheds and sites based on predicted pollutant yields during screening. Simulation results and individual watershed characteristics were used during the development of a drainage quality index (DQI). The DQI was developed using statistical analysis to link a water quality indicator to predicted yields and watershed characteristics. The DQI was developed to assess the impact of management within individual watersheds and among watersheds within a drainage basin. WATNPS was validated using observed data. During simulations WATNPS predicted sediment yields within 50% of observed values. Nutrient yields were predicted within a order of magnitude. Simulation of alternative livestock management practices in Owl Run reflected the same trends identified in the observed data. The Hutton Creek simulation was also consistent with water quality observations. A watershed ranking based on the DQI assessment was compared to one provided by local personnel to compare predicted trends to observed watershed conditions. A demonstration of WATNPS selected a single watershed based on watershed rankings. Critical sites were identified during WATNPS site assessment and BMPs were developed. Following BMP implementation the watershed was simulated to determine the impact on sediment, nitrogen, and phosphorus yields. / Ph. D.

The adoption of Geographic Information System (GIS) technology in social studies classroom practices has helped accelerate the achievement of educational goals. However, despite the value that GIS possesses for supporting student learning skills, few schools have adopted it so far. A reason for this deficiency lies in the absence of specific instructional models that demonstrate possible methods for incorporating GIS into class curriculum. This study sought to address this problem, tailored specifically for Kuwaiti social studies classrooms, with the design, development, and validation of a GIS Instructional Model to facilitate AIW. The study employed a design and development research methodology, comprised of five major phases, (i) selection of model components and theoretical foundation, (ii) analysis and development, (iii) formative feedback, (iv) revision, and (v) usability evaluation. In phase one, the Inquiry Design Model (IDM) format and components with AIW framework were selected to provide basic guidelines for the GIS Instructional Model. In phase two, following a comprehensive review of relevant academic literature, and in combination with personal experience, the researcher developed a preliminary GIS Instructional Model. In phase three, two expert reviewers evaluated the model, delivering their opinions by completing an online survey and taking part in follow-up interviews. The expert reviewers were primarily tasked with determining the model's ability to facilitate AIW in a social studies classroom, and providing suggestions for improving its performance. In phase four, the details gleaned from this formative feedback phase were then used to revise the model and enhance its effectiveness. In the last phase, six Kuwaiti expert reviewers assessed this updated version of the GIS Instructional Model to determine what barriers it might face regarding its implementation in the Kuwaiti educational system. They completed an online survey as part of this process and provided possible solutions to address perceived barriers. The data gained from expert reviewer feedback in these formative and usability evaluation phases were analyzed using qualitative methodologies. This step-by-step procedure helped to validate the model. As a result, a ready-to-implement teaching model, with all necessary teaching materials and instructions, was developed for Kuwaiti social studies classrooms. This model is proposed to enable social studies teachers to better understand how to integrate GIS into their classrooms to support AIW. Recommendations are provided for Kuwaiti educational policymakers and stakeholders to help overcome perceived obstacles that may hinder model implementation; suggestions for future research are also included. / Doctor of Philosophy / Geographical Information Systems (GIS) are software-based technologies which simplify the gathering, storing and manipulation of spatially-related data in ways which allow users to visually represent complex geographic phenomena more easily, bringing greater understanding for the world around us. As a result, the integration of GIS technology into social studies classroom practices has assisted student learning and achievement. However, despite the value which GIS possesses, few schools have integrated this technology so far. A significant reason for this limitation is the lack of clear guidelines or models which demonstrate how to employ this technology in the classroom. To help address the problem, this study developed a GIS Instructional Model for Kuwaiti social studies teachers to facilitate student authentic intellectual work, i.e. the student's demonstration of their deeper understanding for the knowledge and skills they are learning. The study employed a design and developmental research methodology, comprised of five major phases, (i) selection of model components and theoretical foundation, (ii) analysis and development, (iii) formative feedback, (iv) revision, and (v) usability evaluation. Phase one involved the selection of the study's theoretical foundation. In phase two, following a comprehensive review of relevant academic literature and, in combination with personal experience, the researcher developed a preliminary GIS Instructional Model. Two expert reviewers evaluated the model in phase three, delivering their opinions by completing an online survey and taking part in follow-up interviews. This feedback was analyzed in phase four, leading to revisions in the GIS Instructional Model to improve its quality for supporting student learning. In the final phase, six Kuwaiti expert reviewers assessed the newly-updated model to determine what barriers it might face regarding its implementation in the Kuwaiti educational system. They completed an online survey as part of this process and provided possible solutions to address these perceived obstacles. This step-by-step procedure helped to validate the model. The overall result was the development of a ready-to-implement teaching model, with all necessary educational materials and instructions, for employing GIS technology in Kuwaiti social studies classrooms to support student authentic intellectual work. In addition, recommendations were provided for Kuwaiti educational policymakers and stakeholders to help overcome perceived obstacles that may hinder model implementation; suggestions for future research are also included.

During the urbanization process, vehicles quantity increase with expansion in population. Under this situation, bus transportation system also suffers from bus delay. Bus delay could be caused by a series of factors, for instance, overload passengers, traffic jam, traffic accident and other unpredictable situations. Therefore, choosing crucial elements to efficiently evaluate bus delay is a complex problem in bus delay researches and operation management. The thesis propose an approach to evaluate and explain bus delay by two elements: traffic congestion and passengers’ waiting time. Those two elements would represent the action of external and internal factors on bus operation. This approach could be adaptive to explain the reasons for bus delays, thus to help the optimization of bus lines and give useful information for decision making of transportation company. To achieve the research aim, a GIS-T database was created by combining the GIS database and TIS database. Spatial data as well as attribute data are combined in the database to represent the crucial information for bus delay. Based on GIS-T the database, the impact of traffic congestion and passengers’ waiting time was calculated using the bus line simulation. By implementing the above steps, the main cause of bus delay was studied. A case study application of this method is narrated; focusing on optimize the bus system of Guiyang city, South China. Different methods are used to find out the problem of system and the reason for delay. Moreover, optimization suggestion is proposed according to result. Compared with other methods, the two-factor method has the advantage of locating the reason of delay for each station. The time performance is not superior to other methods. By comparing the situation of adjacent station, the proportion of traffic congestion and overload passenger in bus delay was determined. The two-factor method is applicable for other transit system in different cities which has similar structure as Guiyang. However, for cities with other structure, a feasibility should be made to select an appropriate model.

Urbanisering i kombination med miljöfarliga utsläpp från fordonstrafiken ställer högre krav på bostadsplaneringen i städer. Studiens syfte är att öka förståelsen för hur multikriterieanalyser inom geografiska informationssystem kan tillämpas i den översiktliga planeringen för att bidra till ett hållbarare samhälle. En effektivare strategisk bostadsplanering med anslutning till befintliga samhällsfunktioner kan bidra till att miljövänligare transportalternativ prioriteras före bilen. Med hjälp av intervjuer från två tjänstemän inom offentlig och privat sektor har ett antal kriterier tagits fram till analysen. Utifrån befintliga samhällsfunktioner var målet med studien att lokalisera nya områden för bostadsutveckling med hjälp av en multikriterieanalys. Detta kan bidra till att miljövänligare transportmedel kan prioriteras före bilen eftersom avstånden till samhällsfunktionerna blir kortare. Utöver detta var även målet att undersöka hur politiska intressen skiljer sig åt med hjälp av en rangordning utifrån de framtagna kriterierna. Resultatet visar att representanterna från de två största politiska partierna i en svensk småstad rangordnar kriterierna olika gällande vilka samhällsfunktioner som bör finnas i närhet till nya bostadsområden. Däremot visar slutresultatet att de lokaliserade områdena för bostadsutveckling inte skiljer sig nämnvärt mycket ifrån varandra, trots politikernas varierande bostadspolitik. Studien kan bidra till en effektivare politisk hantering av ärenden eftersom politiska skiljaktigheter i slutändan inte alltid visar skillnader i vilka aktiviteter eller objekt som bör placeras var. / Urbanization combined with toxic emissions from motor traffic calls forhigher demands when house planning in cities. The purpose of this study is toincrease understanding about how to apply multi criteria analyses whenmaster planning to contribute to a more sustainable society. A more effectivehouse planning connected to existing societal functions might add to the usageof more sustainable transportation alternatives rather than that of cars. Using the input from interviews with representatives from both the privateand the public sector, a number of criterias have been developed for theanalysis. Considering existing societal functions, this study was intended toidentify new areas for housing development using a multi criterial analysis.This might contribute to more sustainable transportation because of thedistance to the societal functions. In addition to this, the intention extended tothe investigation of how political interests differs from one another, using aranking system based on the developed criterias. The results show that representatives from the two largest political parties in asmall town in Sweden rank the criterias different when it comes to whatsocietal functions a new housing area should have in close proximity. On theother hand, the end results show that the areas chosen for housingdevelopment have similar qualities, in spite of varying housing politics amongthe politicians. This study might contribute to a more effective politicalhandling of business, since political differences does not ultimately showdifferences in where activities or objects should be placed.