No description available.

Nationell infrastruktur för geografiska data (NSDI) har blivit en viktig pusselbit för varje nation när det gäller socio-ekonomisk utveckling och miljöförvaltning. Den nyligen antagna lagen The Lands Rights Act (2018) och inrättandet av Liberia Land Authority (LLA) visar att Liberia står på randen till en seriös utveckling och visar vägen genom att inrätta ett välfungerande system för markförvaltning och en pålitlig markförvaltning. Infrastruktur för geografiska data (SDI) är viktigt för att hantera och möjliggöra utbyte, delning, tillgänglighet och användning av rumsliga data. FN:s expertkommitté för global hantering av geospatial information (UN-GGIM) och Världsbanken har utvecklat Integrated Geospatial Information Framework (IGIF) för att främja hållbar utveckling och tillhandahålla riktlinjer för nationer att följa när de utvecklar en robust NSDI. Syftet med denna studie är att bedöma Liberia´s NSDI från ett data och standardperspektiv för att identifiera landets svagheter och styrkor inom detta område. Den kommer också att belysa de utmaningar och möjligheter som Liberia står inför när landet utvecklar sitt NSDI. Data samlades in genom en litteraturgenomgång och frågeformulär som fylldes i med NSDI-intressenter vid flera statliga organisationer och en internationell organisation i Liberia. Resultaten visade att Liberia´s NSDI för närvarande är underutvecklat. NSDI anses vara svagt ur ett data och standardperspektiv. Dataperspektivet anses dock vara mer gediget. En generell lägesbedömning som täcker alla nio aspekter av ett NSDI var också genomförd, detta i syfte att sätta de två specifika perspektiven i kontext. Bristen på nationella standarder, institutionell samordning och en rättslig ram för hantering av geografiska data är de främsta problemen och utmaningarna. LLA bör ta ledning i utvecklingen av Liberia´s NSDI. I studien föreslås också att Liberia bland annat ska bilda en kommitté för geografiska data för att få alla relevanta intressenter involverade och engagerade i den kommande NSDI-utvecklingen. / National Spatial Data Infrastructure (NSDI) has become an important piece of the puzzle for every nation when it comes to socio-economic development and environmental stewardship. The recently passed The Land Rights Act (2018) and the establishment of the Liberia Land Authority (LLA) indicates that Liberia is on the verge of serious development, paving the way by establishing a well-functioning land administration system and trusted land governance. Spatial data infrastructure is important in order to manage and enable the exchange, sharing, accessibility and use of spatial data. United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) and the World Bank has developed the Integrated Geospatial Information Framework (IGIF) to promote sustainable development and provide guidelines for nations to follow when developing a robust NSDI. The objectives of this paper is to assess Liberia's NSDI from a data and standards perspective to identify its weaknesses and strengths within that area. It will also shed light on the challenges and opportunities that Liberia faces as it develops its NSDI. The data was collected through a literature review and questionnaires were completed by NSDI stakeholders from multiple governmental organizations and one international organization in Liberia. The findings revealed that Liberia's NSDI is currently underdeveloped. The NSDI is considered weak from a data and standards perspective. However, the data perspective is considered as more solid. A general baseline assessment covering all aspects of an NSDI was also carried out to set the two specific perspectives into context. Overall, weak national standards, institutional coordination, and legal framework for handling spatial data are the primary concerns and challenges. LLA is suggested to take the lead in the development of Liberia´s NSDI. The study also suggests that Liberia form a spatial data committee in order to have all relevant stakeholders onboard and committed for the NSDI development at hand.

Prior to using hydraulic and spatially distributed modelling softwares, the theory of the unit hydrograph was a commonly used tool for modelling of surface and runoff water. While distributed models often provide detailed results from extensive calculation durations, the unit hydrograph have been questioned for simplifying the physical characteristics of the watershed modelled. Typically, the unit hydrograph theory does not explicitly take the flow paths of the watershed in consideration during calculation. With the rise of geographical information systems, methods of deriving spatially distributed unit hydrographs have been developed. The aim of these have commonly been to find a spatially varied form of hydrological modelling, while still keeping the computation times low. The method is commonly built by calculating the travel time to the watershed outlet along the flow path. In this study, spatially distributed unit hydrographs are derived separately for the watershed’s pervious and impervious surfaces in a Python script using map algebra and the Esri’s Python wrapper module Arcpy. The travel times are generated from a velocity field calculated using Maidment and Olivera’s velocity equation. The velocity equation contains three unknown parameters; one for an average velocity and two calibration parameters. The excess precipitation is calculated of a 100 year return period Chicago Design Storm hyetograph using the SCS-CN method. The direct runoff hydrographs are calculated over three semi-urban watersheds in Smedby in southern Sweden, and the results are compared to MIKE 21 hydrograph data of each corresponding watershed and rain input. The result obtained showed to replicate the hydrograph response quite well, but only if the unknown parameters in the velocity equation were calibrated to match the MIKE 21 data. The unknown parameters of the velocity equations produces uncertainties of using the method without calibration data, which implies that the script is not well adapted to use for modelling predictions. It may be of interest to calculate the travel times of the locations within the watershed using a different formula. The script tool could be tested using different design storms as input, and areas of different characteristics compared to Smedby could be tested. / Innan det blev vanligt att använda hydrauliska och rumsliga modellerings- mjukvaror användes ofta teorin bakom enhetshydrografen för modellering av avrinning. Medan de rumsliga mjukvarorna ofta erbjuder detaljerade resultat till priset av långa beräkningstider, har enhetshydrografen ifrågasatts för att förenkla den fysiska karaktären av avrinningsområdet. Typiskt sett tar inte enhetshydrografen avrinningsområdets flödesvägar direkt i hänseende vid beräkning. Utveckling och ökad tillgänglighet av geografiska informations- system förenklade möjligheterna att utveckla beräkning av enhetshydrografer som tar hänsyn till avrinningsområdets karaktär, typiskt sett genom att beräkna rinntiden från varje läge i avrinningsområdet, längs rinnvägarna och till utloppet. I den här studien beräknas spatiala enhetshydrografer separat för avrinningsområdets hårdgjorda och icke hårdgjorda ytor, genom att utveckla ett Python skript med hjälp av karalgebra och Esri’s wrapper modul ArcPy. Rinntiderna från olika lägen i avrinningsområdet beräknas med Maidments och Oliveras formel för hastighet, vilken innehåller okända parametrar för en uppskattad medelhastighet samt två kalibreringsparametrar. Effektivt regn från ett Chicago Design Storm regn med en återkomsttid på 100 år beräknas med hjälp av SCS-CN metoden. Hydrograferna för direkt avrinning faltas för tre semi-urbana avrinningsområden i Smedby i södra Sverige för att sedan jämföras mot MIKE 21 genererad hydrograf data för respektive motsvarade avrinningsområde. Hydrografdata producerat av MIKE 21 har tagits fram med lika CDS-regn data som input. Resultatet visar att hydrografer snarlika MIKE 21 hydrograferna kan tas fram med Maidments spatialt fördelade enhetshydrograf, om de okända parametrarna i Maidments formel kalibrerades mot MIKE 21 data. Utan kalibreringsdata för att bestämma de okända parametrarna kan resultatet anses vara mycket osäkert, vilket antyder att Python skriptet ej bör användas för använda metoden för att förutspå responser av regnevent. Andra beräkningar än Maidments ekvation kan vara av intresse att implementera. Olika typer av regninput samt spatial data över andra platser än Smedby kan vara av intresse att testa Python skriptet för.

The Southeastern Lower Coastal Plain wet pine flats include thousands of acres of jurisdictional wetlands that are economically, socially, and environmentally important. These highly productive forests have been intensively managed as pine plantations for the past few decades. More recently, harvesting and site preparation practices have become a concern among natural resource managers because intensive forestry practices may alter soil physical properties and site hydrology. These alterations could decrease seedling survival, growth, and future site productivity. However, the effects of soil disturbance on long-term site productivity and the effects of amelioration techniques on site hydrology are uncertain. The overall objectives of this study were (1) to characterize disturbed forest soil morphology and physical properties, (2) to assess their impact on the processes that control site hydrology and site productivity, (3) to determine effects of harvesting and site preparation on site hydrology, specifically on the overall hydrological balance and on spatial and temporal patterns of surface water storage. The study site is located in an intensively managed loblolly pine (Pinus taeda L.) plantation in the lower coastal plain of South Carolina. This study was established in winter 1991, and dry- and wet-weather harvesting treatments were installed in summer 1993 and winter 1994, respectively. Bedding and mole channel/bedding treatments were installed in both dry- and wet-harvested plots in fall 1995. Soil profiles were described for a recently disturbed, deeply-rutted area, and 2-year-old deeply-rutted and churned areas, bedded and undisturbed areas. Intact soil core samples and composite loose soil samples were collected from each morphological section for soil physical characterizations. Automated weather station and wells were used to collect continuous climatic and surface water level data since 1996. Surface water levels were monitored monthly on a 20 x 20 m grid of 1-m wells since 1992. Total groundwater heads were determined from differential piezometer measurements at high and low elevation places in each treatment plot. Soil profile descriptions and soil physical property measurements indicated that significant amounts of organic debris were incorporated into the surface horizons, and subsurface soil horizons showed significant soil structural changes and increased redoximorphic features caused by soil disturbance. The disturbed soil layers in recently created traffic ruts consisted of exposed and severely disturbed subsurface soils, but this layer was naturally ameliorated 2 years after the disturbance. Bedding site preparation had little amelioration effects on the physical properties of surface soil horizons because the surface horizons already had some incorporation of organic debris. Overall, the main consequence of bedding in a disturbed wet site was to increase the aerated soil volume. The bedding appeared to have little effect on disturbed subsurface horizons. Groundwater head in the study site was constantly higher than -25 cm during the study period, which caused groundwater inflow when the surface water level was low. Frequent fluctuation of the surface water level and constant water supply from the groundwater probably explain the high productivity of the study site. Results of the annual water balance showed that surface soil water storage changes were very small, and annual precipitation and potential evapotranspiration were approximately equal. Silvicultural practices and minor topography on the study site had significant effects on the water balance because they influenced surface water level. Surface water hydraulic gradient evaluation and multivariate cluster analysis indicated that micro-site hydrology and water flow patterns were significantly altered by wet-weather harvesting and bedding site preparation, but overall site hydrology was not altered. Evaluation of predicted surface water level indicated that micro-topography and precipitation patterns had significant influences on surface water levels during the site establishment period. These results revealed that the hydrologic components of wetland delineation are complex in the wet pine flatwoods. / Ph. D.

Made available in DSpace on 2016-06-02T19:06:05Z (GMT). No. of bitstreams: 1 5287.pdf: 3924606 bytes, checksum: 935b5a09df26eb1b41df901a189a6e2a (MD5) Previous issue date: 2013-05-29 / Universidade Federal de Sao Carlos / Geographic information systems with the aid of spatial databases store and manage crisp spatial data (or exact spatial data), whose shapes (boundaries) are well defined and have a precise location in space. However, several spatial data do not have precisely known boundaries or have an uncertain location in space, which are called vague spatial data. The boundaries of a given vague spatial data may shrink or extend, therefore, may have a minimum and maximum extension. Clouds of pollution, deforestation, fire outbreaks, route of an airplane, habitats of plants and animals are examples of vague spatial data. In the literature, there are currently vague spatial data models, such as Egg-Yolk, QMM and VASA. However, according to our knowledge, they focus only on the formal aspect of the model definition. Thus, real or synthetic vague spatial data is not available for use. The main objective of this master thesis is the development of algorithms for the generation of synthetic vague spatial data based on the crisp models of spatial data vague Egg-Yolk, QMM and VASA. It was also implemented a tool, called VagueDataGeneration, to assist in the process of generation such data. For both the algorithms and the tool, the user is able to set the properties related to the data type of model, such as size, shape, volume, complexity, location and spatial distribution. By using the proposed algorithms and the VagueDataGeneration tool, researchers can generate large samples of vague spatial data, enabling new research, such as testing indexes for vague spatial data or evaluating query processing over data warehouses that store vague spatial data. The validation of the vague spatial data generation was conducted using a case study with data from vague rural phenomena. / Sistemas de informação geográfica com o auxílio de bancos de dados espaciais armazenam e gerenciam dados espaciais exatos, cujas formas (fronteiras) são bem definidas e que possuem uma localização exata no espaço. Entretanto, vários dados espaciais reais não possuem os seus limites precisamente conhecidos ou possuem uma localização incerta no espaço, os quais são denominados dados espaciais vagos. Os limites de um dado espacial vago podem encolher ou estender, portanto, podem ter uma extensão mínima e máxima. Nuvens de poluição, desmatamentos, focos de incêndios, rota de um avião, habitats de plantas e de animais são exemplos de dados espaciais vagos. Na literatura, atualmente existem modelos de dados espaciais vagos, tais como Egg-Yolk, QMM e VASA. No entanto, segundo o nosso conhecimento, estes enfocam apenas no aspecto formal da definição do modelo. Com isso, dados espaciais vagos reais ou sintéticos não estão disponíveis para uso. O principal objetivo deste trabalho de mestrado consiste no desenvolvimento de algoritmos para a geração de dados espaciais vagos sintéticos baseados nos modelos exatos de dados espaciais vagos Egg-Yolk, QMM e VASA. Também foi implementada uma ferramenta, chamada VagueDataGeneration, para auxiliar no processo de geração desses dados. Nos algoritmos propostos e na ferramenta desenvolvida, o usuário define as propriedades referentes ao tipo de dado de um modelo, tais como tamanho, formato, volume, complexidade, localização e distribuição espacial dos dados espaciais vagos a serem gerados. Por meio do uso dos algoritmos propostos e da ferramenta VagueDataGeneration, os pesquisadores podem gerar grandes amostras de dados espaciais vagos, possibilitando novas pesquisas, como exemplo, testar índices para dados espaciais vagos ou testar técnicas de processamento de consultas em Data Warehouses que armazenam dados espaciais vagos. A validação da geração de dados espaciais vagos foi efetuada usando um estudo de caso com dados de fenômenos rurais vagos.

Foreign Direct Investment (FDI) in the United States, which predominately occurs in the manufacturing sector, remains critically important for a strong regional and local economy, due to the resulting increase in employment, wages, and tax revenue. Traditionally, local economic development strategies have focused on attracting external manufacturing plants or facilities as the primary route to economic growth, through the expansion of the tax base and/or an increase in employment. In comparison, Sustainable Local Economic Development (SLED) emphasizes the establishment of a minimum standard of living for all and an increase in this standard over time; a reduction in the steady growth in inequality among people; a reduction in spatial inequality; and the promotion and encouragement of sustainable resource use and production (Blakely & Leigh, 2010). These essential SLED principles motivate this study, which will seek to develop a better understanding of whether and how FDI contributes to SLED in terms of its spatial patterns and its impact on middle class earnings. By selecting Georgia as a case study area, this research specifically examines whether and how the location of manufacturing FDI has reduced (or increased) spatial inequality at the intra-state and intra-metropolitan levels. It also identifies whether and how manufacturing FDI has reduced (or increased) inequality among people, focusing on its impact on middle class earnings. This study finds a strong spatial concentration of manufacturing FDI employment in metropolitan areas, particularly in a large metropolitan area, at the intra-state spatial pattern analysis. The results of panel regression analysis suggest that presence of agglomeration economies in metropolitan areas has positively influenced the location of manufacturing FDI jobs. The study also finds a suburbanization pattern of manufacturing FDI employment in the intra-metropolitan spatial pattern analysis. This intra-metropolitan suburbanization of FDI in manufacturing jobs is associated with loss of urban industrial land in the central areas within a large metropolitan area. These uneven distribution patterns of manufacturing FDI jobs indicate increased spatial inequality at both intra-state and intra-metropolitan levels, but the implications of this finding are mixed. Using individual earnings data from the American Community Survey Public Use Microdata Sample files, this study also conducts a quantile regression to estimate the earnings distribution effects that a concentration of manufacturing FDI may have on different earnings groups. The findings both from place-of-work and place-of-residence earnings analysis suggest that manufacturing FDI generally has reduced inequality among people. The concentration of manufacturing FDI in a certain area show the largest distribution effects on area workers in the lower earnings group and residents in the middle earnings group.

This study set out to develop a framework within which the use of Geographical Information Technologies (GITs) can be enhanced in Road Infrastructure Maintenance (RIM) in Uganda. Specifically it was guided by 3 objectives; 1. To assess the gaps in the use of GITs for RIM in Uganda and the limitations to accessing these technologies, 2. To develop a methodological framework to enhance the use of GITs in RIM and 3. To develop a Geographical Information Systems for Transportation (GIS-T) data model based on the road maintenance data requirements. A participatory approach through a series of interviews, focus group discussions, workshop & conferences, document reviews, field observations & measurements and GIS analysis were employed. Based on the Spatial Data Infrastructure (SDI) concept and the principle of Causality, the gaps and limitations were established to mainly be concerned with data and organisational constraints as opposed to technical issues. They were classified to include; inadequate involvement of GITs in organisational activities, inappropriate institutional arrangements, absence of data sharing frameworks, budget constraints, insufficient geospatial capacity, digital divide in the perception, adoption & affordability of GITs among the stakeholders and the absence of a road maintenance Spatial Data Infrastructure (SDI). A methodological framework, comprising of 6 strategic components was developed to enhance the use of GITs in RIM. This included enactment of relevant policy components to guide GIT use, continuous capacity building, establishment of a road maintenance SDI, fostering collaboration and spatial data sharing frameworks, budgetary allocation based on defined activities inclusive of GIT initiatives, and adoption of a dynamic segmentation data model. Conceptual and logical data models were developed and proposed for the Sector. The conceptual model, presented using an entity relationship diagram, relates the road network to the point and line events occurring on it. The logical object relational model developed using the ESRI provided template represents the road and the point and line events in a total of 19 object classes. The Study concludes that in order to ground GIT benefits in the sector; technical, data and organisational concerns involved in GIT undertakings should be accorded equal emphasis. Institutionalisation and diffusion of GITs as aspects of the component strategies are regarded capacity building mechanisms earmarked to boost success in GIT initiatives. Further research on diffusion and funding models for GIT initiatives is recommended. It is suggested that aspects of the proposed model be considered when establishing GIT standards for the sector. The RIM sector is encouraged to embrace Science and Technology and to participate in Research and Development and particularly to adopt the culture of innovation considering the ready availability of off the shelf equipment, freeware and open source software that can foster informed decision making.

Aquesta tesi està dedicada al disseny i a l'anàlisi d'estructures de dades multidimensionals, és a dir, estructures de dades que serveixen per emmagatzemar registres $K$-dimensionals que solen representar-se com a punts en l'espai $[0,1]^K$. Aquestes estructures tenen aplicacions en diverses àrees de la informàtica com poden ser els sistemes d'informació geogràfica, la robòtica, el processament d'imatges, la world wide web, el data mining, entre d'altres. Les estructures de dades multidimensionals també es poden utilitzar com a indexos d'estructures de dades que emmagatzemen, possiblement en memòria externa, dades més complexes que els punts.Les estructures de dades multidimensionals han d'oferir la possibilitat de realitzar operacions d'inserció i esborrat de claus dinàmicament, a més de permetre realitzar cerques anomenades associatives. Exemples d'aquest tipus de cerques són les cerques per rangs ortogonals (quins punts cauen dintre d'un hiper-rectangle donat?) i les cerques del veí més proper (quin és el punt més proper a un punt donat?).Podem dividir les contribucions d'aquesta tesi en dues parts: La primera part està relacionada amb el disseny d'estructures de dades per a punts multidimensionals. Inclou el disseny d'arbres binaris $K$-dimensionals al·leatoritzats (Randomized $K$-d trees), el d'arbres quaternaris al·leatoritzats (Randomized quad trees) i el d'arbres multidimensionals amb punters de referència (Fingered multidimensional trees).La segona part analitza el comportament de les estructures de dades multidimensionals. En particular, s'analitza el cost mitjà de les cerques parcials en arbres $K$-dimensionals relaxats, i el de les cerques per rang en diverses estructures de dades multidimensionals. Respecte al disseny d'estructures de dades multidimensionals, proposem algorismes al·leatoritzats d'inserció i esborrat de registres per als arbres $K$-dimensionals i per als arbres quaternaris. Aquests algorismes produeixen arbres aleatoris, independentment de l'ordre d'inserció dels registres i desprès de qualsevol seqüència d'insercions i esborrats. De fet, el comportament esperat de les estructures produïdes mitjançant els algorismes al·leatoritzats és independent de la distribució de les dades d'entrada, tot i conservant la simplicitat i la flexibilitat dels arbres $K$-dimensionals i quaternaris estàndard. Introduïm també els arbres multidimensionals amb punters de referència. Això permet que les estructures multidimensionals puguin aprofitar l'anomenada localitat de referència en cerques associatives altament correlacionades.I respecte de l'anàlisi d'estructures de dades multidimensionals, primer analitzem el cost esperat de las cerques parcials en els arbres $K$-dimensionals relaxats. Seguidament utilitzem aquest resultat com a base per a l'anàlisi de les cerques per rangs ortogonals, juntament amb arguments combinatoris i geomètrics. D'aquesta manera obtenim un estimat asimptòtic precís del cost de les cerques per rangs ortogonals en els arbres $K$-dimensionals aleatoris. Finalment, mostrem que les tècniques utilitzades es poden estendre fàcilment a d'altres estructures de dades i per tant proporcionem una anàlisi exacta del cost mitjà de cerques per rang en estructures de dades com són els arbres $K$-dimensionals estàndard, els arbres quaternaris, els tries quaternaris i els tries $K$-dimensionals. / Esta tesis está dedicada al diseño y al análisis de estructuras de datos multidimensionales; es decir, estructuras de datos específicas para almacenar registros $K$-dimensionales que suelen representarse como puntos en el espacio $[0,1]^K$. Estas estructuras de datos tienen aplicaciones en diversas áreas de la informática como son: los sistemas de información geográfica, la robótica, el procesamiento de imágenes, la world wide web o data mining, entre otras.Las estructuras de datos multidimensionales suelen utilizarse también como índices de estructuras que almacenan, posiblemente en memoria externa, datos complejos.Las estructuras de datos multidimensionales deben ofrecer la posibilidad de realizar operaciones de inserción y borrado de llaves de manera dinámica, pero además deben permitir realizar búsquedas asociativas en los registros almacenados. Ejemplos de búsquedas asociativas son las búsquedas por rangos ortogonales (¿qué puntos de la estructura de datos están dentro de un hiper-rectángulo dado?) y las búsquedas del vecino más cercano (¿cuál es el punto de la estructura de datos más cercano a un punto dado?).Las contribuciones de esta tesis se dividen en dos partes:La primera parte está dedicada al diseño de estructuras de datos para puntos multidimensionales, que incluye el diseño de los árboles binarios $K$-dimensionales aleatorios (Randomized $K$-d trees), el de los árboles cuaternarios aleatorios (Randomized quad trees), y el de los árboles multidimensionales con punteros de referencia (Fingered multidimensional trees).La segunda parte contiene contribuciones al análisis del comportamiento de las estructuras de datos para puntos multidimensionales. En particular, damos el análisis del costo promedio de las búsquedas parciales en los árboles $K$-dimensionales relajados y el de las búsquedas por rango en varias estructuras de datos multidimensionales.Con respecto al diseño de estructuras de datos multidimensionales, proponemos algoritmos aleatorios de inserción y borrado de registros para los árboles $K$-dimensionales y los árboles cuaternarios que producen árboles aleatorios independientemente del orden de inserción de los registros y después de cualquier secuencia de inserciones y borrados intercalados. De hecho, con la aleatorización garantizamos un buen rendimiento esperado de las estructuras de datos resultantes, que es independiente de la distribución de los datos de entrada, conservando la flexibilidad y la simplicidad de los árboles $K$-dimensionales y de los árboles cuaternarios estándar. También proponemos los árboles multidimensionales con punteros de referencia, una técnica que permite que las estructuras de datos multidimensionales exploten la localidad de referencia en búsquedas asociativas que se presentan altamente correlacionadas.Con respecto al análisis de estructuras de datos multidimensionales, comenzamos dando un análisis preciso del costo esperado de las búsquedas parciales en los árboles $K$-dimensionales relajados. A continuación, utilizamos este resultado como base para el análisis de las búsquedas por rangos ortogonales, combinándolo con argumentos combinatorios y geométricos. Como resultado obtenemos un estimado asintótico preciso del costo de las búsquedas por rango en los árboles $K$-dimensionales relajados. Finalmente, mostramos que las técnicas utilizadas pueden extenderse fácilmente a otras estructuras de datos y por tanto proporcionamos un análisis preciso del costo promedio de búsquedas por rango en estructuras de datos como los árboles $K$-dimensionales estándar, los árboles cuaternarios, los tries cuaternarios y los tries $K$-dimensionales. / This thesis is about the design and analysis of point multidimensional data structures: data structures that store $K$-dimensional keys which we may abstract as points in $[0,1]^K$. These data structures are present in many applications of geographical information systems, image processing or robotics, among others. They are also frequently used as indexes of more complex data structures, possibly stored in external memory.Point multidimensional data structures must have capabilities such as insertion, deletion and (exact) search of items, but in addition they must support the so called {em associative queries}. Examples of these queries are orthogonal range queries (which are the items that fall inside a given hyper-rectangle?) and nearest neighbour queries (which is the closest item to some given point?).The contributions of this thesis are two-fold:Contributions to the design of point multidimensional data structures: the design of randomized $K$-d trees, the design of randomized quad trees and the design of fingered multidimensional search trees;Contributions to the analysis of the performance of point multidimensional data structures: the average-case analysis of partial match queries in relaxed $K$-d trees and the average-case analysis of orthogonal range queries in various multidimensional data structures.Concerning the design of randomized point multidimensional data structures, we propose randomized insertion and deletion algorithms for $K$-d trees and quad trees that produce random $K$-d trees and quad trees independently of the order in which items are inserted into them and after any sequence of interleaved insertions and deletions. The use of randomization provides expected performance guarantees, irrespective of any assumption on the data distribution, while retaining the simplicity and flexibility of standard $K$-d trees and quad trees.Also related to the design of point multidimensional data structures is the proposal of fingered multidimensional search trees, a new technique that enhances point multidimensional data structures to exploit locality of reference in associative queries.With regards to performance analysis, we start by giving a precise analysis of the cost of partial matches in randomized $K$-d trees. We use these results as a building block in our analysis of orthogonal range queries, together with combinatorial and geometric arguments and we provide a tight asymptotic estimate of the cost of orthogonal range search in randomized $K$-d trees. We finally show that the techniques used apply easily to other data structures, so we can provide an analysis of the average cost of orthogonal range search in other data structures such as standard $K$-d trees, quad trees, quad tries, and $K$-d tries.

空間認知(Spatial Cognition)指出人所理解的空間複雜度，也就是人與環境互動的過程中，經由記憶與感官經驗，透過內化與重建產生物體在空間的關係認知。認知圖(Cognitive Map)是最常被使用在評估空間認知。分析學生所畫的認知圖有助於老師們瞭解學生的空間認知能力，進而擬定適當的地理教學設計。我們視空間認知發展的學習歷程檔案是由這些認知圖所構成。隨著數位學習科技的進步，我們可以透過探勘認知圖的方式，探討空間認知發展的學習歷程檔案。因此，我們藉由透過圖像的空間資料探勘，分析學生空間認知發展的學習歷程。 空間資料探勘(Spatial Data Mining)主要是從空間資料庫或圖像資料庫中找出有趣且有意義的樣式。在論文中，我們介紹一種空間樣式(Spatial Co-orientation Pattern)探勘以提供空間認知發展學習歷程的分析。Spatial Co-orientation Pattern是指圖像資料庫中，具有共同相對方向關係的物體(Object)常一起出現。例如，我們可以從圖像資料庫中發現物體P常出現在物體Q的左邊，我們利用二維字串(2D String)來表示物體分佈在圖像中的空間方向關係。我們透過Pattern-growth的方法探勘此種空間樣式，藉由實驗結果呈現Pattern-growth的方法與過去Apriori-based的方法[14]之優缺點。 我們延伸Spatial Co-orientation Pattern的概念至時空資料庫(Spatio-temporal Database)，提出從時空資料庫中，探勘Temporal Co-orientation Pattern。Temporal Co-orientation Pattern是指Spatial Co-orientation Pattern隨著時間的變化。論文中，我們提出兩種此類樣式，即是Coarse Temporal Co-orientation Pattern與Fine Temporal Co-orientation Pattern。針對此兩種樣式，我們提出三階段(three-stage)演算法，透過實驗分析演算法的效率。 / Spatial cognition means how human interpret spatial complexity. Cognitive maps are mostly used to test the spatial cognition. Analyzing cognitive maps drawn by students is helpful for teachers to understand students’ spatial cognitive ability and to draft geography teaching plans. Cognitive maps constitute the portfolios of spatial cognitive development. With the advance of e-learning technology, we can analyze portfolios of spatial cognitive development by spatial data mining of cognitive images. Therefore, we can analyze portfolios of spatial cognitive development by spatial data mining of images. Spatial data mining is an important task to discover interesting and meaningful patterns from spatial or image databases. In this thesis, we investigate the spatial co-orientation patterns for analyzing portfolios of spatial cognitive development. Spatial co-orientation patterns refer to objects that frequently occur with the same spatial orientation, e.g. left, right, below, etc., among images. For example, an object P is frequently left to an object Q among images. We utilize the data structure, 2D string, to represent the spatial orientation of objects. We propose the pattern-growth approach for mining co-orientation patterns. An experimental evaluation with synthetic datasets shows the advantages and disadvantages between pattern-growth approach and Apriori-based approach proposed by Huang [14]. Moreover, we extend the concept of spatial co-orientation pattern to that of temporal patterns. Temporal co-orientation patterns refer to the change of spatial co-orientation patterns over time. Two temporal patterns, the coarse temporal co-orientation patterns and fine temporal co-orientation patterns are introduced to be extracted from spatio-temporal databases. We propose the three-stage algorithms, CTPMiner and FTPMiner, for mining coarse and fine temporal co-orientation patterns, respectively. An experimental evaluation with synthetic datasets shows the performance of these algorithms.

The importance of managing and conserving cultural heritage can not be overemphasised. It is this realisation that has prompted the United Nations Educational, Scientific and Cultural Organisation (UNESCO) to declare identified sites of cultural importance as World Heritage Sites. The uKhahlamba-Drakensberg Park (UDP) was declared such a site in 2000, with its natural properties and cultural heritage as the criteria for inscription. The cultural heritage centres on the vast quantity of rock art that is renowned for its quality and diversity of subject. It is an important consideration for future generations to have the opportunity to view and understand this rich history and culture. There are increasing human and natural impacts on this non-renewable resource and to minimise these impacts and thus ensure the longevity of the resource it is necessary to develop a multi faceted selection of management and conservation tools. This realisation led the Programme of Geornatics, University of KwaZulu-Natal to conceptualise a project to develop a web-based Geographical Information System (GIS) specifically aimed at assisting in the management and conservation of rock art sites for the Valley of Pools in the Cathedral Peak Conservation Area of the UDP. Data for the project was captured in the field using Global Positioning System (GPS), digital camera and video camera as well as conventional hardcopy documentation. Existing digital spatial data and descriptive data were also collected from relevant stakeholders and a commercial organization. A pilot spatial database was then developed using ArcGIS@9 and Microsoft Access@, and later tested using a set of integrated simulated queries reflective of routine questions that users may request. Upon obtaining satisfactory responses to the queries, the integrated database was migrated and authored in ArcIMS®9 where it was further tested, and subsequently access was given to selected external professionals, both nationally and internationally, from various backgrounds, for evaluation purposes. Feedback from this process was favourably obtained. / Thesis (M.Env.Dev.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.