Dissertation (PhD)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Made available in DSpace on 2015-03-26T13:53:16Z (GMT). No. of bitstreams: 1 texto completo.pdf: 3045713 bytes, checksum: 29d033208d3f70ac0ab24c206abd28f5 (MD5) Previous issue date: 2009-02-16 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The supervised classification of soils, especially in recent decades, is being carried out using mathematical and statistical models, amongst which the model of neural networks, stand out by greater accuracy of mapping comparing to classical models, such as Maximum Likelihood (MaxVer), helping the conventional method of mapping. Neural Networks model has been performed mostly for soil properties, with little application for soil classes. This work aimed to undertake the classification of soil using neural networks and MaxVer for an area located in Serra do Cipó, in the State of Minas Gerais. The map units was defined based on information from 55 soil profiles classified accord to the Brazilian System of Soils Classification to the fourth categorical level, whereas compound units were done with basis on the similarity of soil properties and the characteristics of physics environment. The discriminates variables used included: six scenes of Landsat satellite image sensor ETM+, four indexes derived from this image (Clay minerals, Ferrous minerals, Iron oxide and NDVI), Digital Elevation Model and derived attributes: altitude, slope, compound topographic index, aspect, solar radiation, curvature and elevation amplitude, in addiction to geological and soil maps. Several variables combinations were tested in both classifiers, selecting those that best contribute to classify the soil with high accuracy on the two supervised mapping approaches. The classification by neural networks was performed using the Stuttgart Neural Network Simulator and the backpropagation algorithm, the framework and classification parameters were selected by training and statistical tests. The results obtained with both classifiers, neural networks and MaxVer were compared using ground data as reference. The same set of reference points was used to validate the soil map obtained by the conventional method of mapping. Maps obtained by the two classifiers using the group of variables that provided the best performance to the classification showed a good accuracy index, with no statistical difference in overall accuracy of the maps. The map generated by MaxVer showed a kappa index of 0.58, while the map from neural network showed an index of 0.60. Although the accuracy of the two maps was statistically similar, the classifiers efficiency in individual discrimination of soil units differed significantly, with two units being best classified by MaxVer, three units by neural networks and four units with similar accuracies in both approach classification. The overall accuracy of soil maps made by the conventional method was 82%. The soils of the first component in mapping units agreed in 48% with reference soils. / A classificação supervisionada de solos, especialmente nas últimas décadas, vem sendo realizada com o auxílio de modelos matemáticos e estatísticos, dentre os quais destaca-se o modelo de redes neurais, o qual tem apresentado exatidão superior quando comparado com métodos clássicos, como o de Máxima Verossimilhança (MaxVer), auxiliando no método convencional de mapeamento. No entanto, na maioria dos trabalhos foram avaliadas as propriedades dos solos, sendo o estudo das classes de solos ainda incipiente. Assim, este trabalho teve como objetivo realizar a classificação de solos por redes neurais e pelo MaxVer para uma área situada na Serra do Cipó, no estado de Minas Gerais. Para tanto, utilizaram-se informações analíticas de 55 perfis de solos, classificados até o quarto nível categórico do Sistema Brasileiro de Classificação de Solos. As unidades do mapa de solos foram compostas por semelhanças entre as propriedades físicas do solo e as características do ambiente. As variáveis discriminantes avaliadas na classificação foram seis cenas da imagem do satélite Landsat, sensor ETM+; quatro índices derivados dessa imagem (Clay minerals, Ferrous minerals,Iron oxide e NDVI); modelo digital de elevação e atributos derivados: altitude, declividade, índice topográfico combinado, face de exposição, radiação solar, curvatura e amplitude altimétrica, além dos mapas geológico e pedológico. A partir desse conjunto de variáveis, identificaram-se aquelas que melhor contribuíram na discriminação dos solos, em cada uma das duas abordagens empregadas. Na classificação pelas redes neurais foram empregados o simulador Stuttgart Neural Network Simulator e o algoritmo backpropagation, sendo a arquitetura e os parâmetros selecionados por meio de tentativas e testes de significância estatística. Os resultados obtidos por ambos os classificadores, redes neurais e MaxVer, foram comparados entre si, utilizando-se a validação dos mapas com pontos de referência terrestre. Os mesmos pontos de referência foram utilizados para validar o mapa de solos obtido pelo método convencional de mapeamento. Os mapas obtidos pelos dois classificadores, utilizando o conjunto de varáveis que proporcionou melhor desempenho do classificador, apresentaram índice de exatidão considerado bom, sem diferença estatística na exatidão global dos mapas. O mapa melhor classificado pelo MaxVer apresentou índice kappa de 0,58, enquanto que, pelas redes neurais, o maior índice foi de 0,60. Esses valores não diferiram estatisticamente, entretanto, os classificadores diferiram na discriminação das unidades de solo, sendo duas unidades melhor classificadas pelo MaxVer, três pelas redes neurais e quatro unidades com exatidão estatisticamente igual para os dois classificadores. A exatidão global do mapa obtido pelo método convencional de mapeamento foi de 82%, sendo esse índice calculado pelo somatório dos solos de referência concordantes com qualquer componente da unidade. Os solos no primeiro componente das unidades de mapeamento apresentaram 48% de concordância com solos de referência.

Ph.D. / Until recently the majority of computer aided instruction (CAl) programs available for the teaching of history, only provided elementary facilities such as drill-and-practice exercises. Some of the more advanced systems use simulation techniques to create fictitious historical situations. These simulation systems take the form of computer games where the participants have to make decisions on historical situations with which they are confronted. The initial aim of this study was to develop a CAl-system for the teaching of history in which historical field battles could be simulated, or more correctly, in which a particular field battle situation could be reconstructed. By using the system, a student could get a better understanding of the different factors which played a role during a specific battle. It soon became clear though, that the original aims were too broad and too general. The decision was therefore made to undertake a study of the dynamic interrelationships of time and space with reference to field battles. A model was developed which provides a framework for the transformation of often unstructured and diffuse time and space relationships into more specific, structured values which can be loaded into the database of a computer. Historical field battles are used as a vehicle to outline the functioning of the model. After a history teacher or historian has analysed and restructured a specific field battle into relations that can be computerized, a history student can interactively formulate his questions on the time-space relationships of the battle under study. In the field battle model, the concept of an "event" plays an important role. An event defines an action or activity which took place during a field battle. Two of the major constituents of an event are the time when the event took place, and the geographical position where it occurred. Therefore much of the work reported in this thesis covers the development of algorithms for the representation of time and space relations. Algoritmhs were developed for the interactive drawing of geographical maps of the area where the battle took place. The main building blocks of a geographical map are points, icons, lines and areas. Special attention was given to the representation of these entities. Due to the limited viewing area available on the screen of a micro computer, an area clipping algorithm was developed for the display of selected parts of the map. Time which is observed under operational conditions during a field battle is referred to as "perceived time". Perceived time is often vague and even unreliable. An algorithm was developed through which these vague time references are transformed to more specific "clock time" values. The algorithm constructs a time network, using the vague known time of occurrence of events, to sequence the events relative to each other. By solving this network, the time of occurrence of the events forming part of the network, are determined to a fair degree of accuracy. These time values and other relevant information are entered into the database of a micro computer system, to be used for instructional purposes.

Accurate and current land use information for urban areas is important for effective management and planning. Over the years, researchers/planners have relied heavily on aerial photographs for land use information of urban areas because of the limitations of deriving more accurate land use estimates from satellite remote sensing data. The main problem involved in producing accurate land use maps of cities and towns from satellite images is that urban areas consist of a complex assemblage of different land cover types, many of which have very similar spectral reflectance characteristics. This is because land use is an abstract concept- n amalgam of economic, social and cultural factors-that is defined in terms of functions rather than forms. The relationship between land use and the multispectral signals detected by a satellite sensor is therefore both complex and indirect. In many European cities, residential areas are characterized by a complex spatial assemblage of tile roof, slate roof, glass roof buildings, as well as tarmac, concrete and pitch roads, and gardens (comprised of grass lawns, trees and plants). In North American cities, roofing materials are more commonly composed of wood and shingles. In both settings all these "objects" together form the residential areas or residential districts of town or city, but each of them has a different spectral reflectance. So, in generating a land use map from remotely sensed image, buildings, roads, gardens, open spaces will be identified separately. Keeping this in mind, this thesis evaluates eight selected land use classification methods for the Vancouver metropolitan area, identifies the most accurate and suitable method for urban land use classification, and produces a land use map of the study area based on the most suitable method. The study area is a part of Greater Vancouver Regional District (GVRD). It includes Vancouver, Burnaby, Richmond, Delta, and parts of seven other municipalities. The whole area is highly urbanized and commercialized. Agricultural lands are present in the southern part of the study area (which includes parts of Richmond, Delta and Surrey). For this study four sources of data have been used. The 1996 Greater Vancouver regional District (GVRD) land use map is the basic source of land use information. A remotely sensed image of May 1999 (Landsat 7) has been used for the identification of land cover data, Vancouver and Fraser valley orthophotos (May/July 1995) have been used to locate sample sites, and aerial photos of May 1999 (1:30,000) have been used for ground verification. / Arts, Faculty of / Geography, Department of / Graduate

The The’wá:lí Community Digital Mapping Project is a collaborative, scholarly project for which the final product is a digital, layered map of the reserve and traditional lands of the Stó:lō (Xwélmexw) community of The’wá:lí (Soowahlie First Nation). The map, containing over 110 sites and stretching from Bellingham Bay, Washington in the west to Chilliwack Lake, B.C. in the east, is hyperlinked with audio, visual and textual media that tell stories about places of importance to this community. The map is intended to give voice to many different senses of and claims to place, and their intersections, in the The’wá:lí environment, while also exploring the histories of how these places and their meanings have changed over time. It expresses many, often conflicting, ways of understanding the land and waterways in this environment, and presents an alternative to the popular, colonial narrative of the settlement of the Fraser Valley. Thus, the map, intended ultimately for The’wá:lí’s use, is also meant to engage a local, non-Indigenous audience, challenging them to rethink their perceptions about where they live and about the peoples with whom they share their histories and land. The essay that follows is a discussion of the relationship-building, research, writing and map-building processes that have produced the The’wá:lí Community Digital Map. / Graduate / 2017-08-21 / 0740 / 0509 / 0366 / sabinatrimble@gmail.com

Until recently, transit data lacked a common data format that could be used to share and integrate information among multiple agencies. In 2005, however, Google worked with Tri-Met in Oregon to create the General Transit Feed Specification (GTFS), an open data format now used by all transit agencies that participate in Google Maps. GTFS feeds contain data for scheduled transit service including stop and route locations, schedules and fare information. The broad adoption of GTFS by transit agencies has made it a de facto standard. Those agencies using it are able to participate in a host of traveler services designed for GTFS, most notably transit trip planners. Still, analysts have not widely used GTFS as a data source for transit planning because of the newness of the technology. The objectives of this project are to demonstrate that GTFS feeds are an efficient data source for calculating key transit service metrics and to evaluate the validity of GTFS feeds as a data source. To demonstrate GTFS feeds’ analytic potential, the author created a tool called GTFS Reader, which imports GTFS feeds into a database using open-source products. GTFS Reader also includes a series of queries that calculate metrics like headways, route lengths and stop-spacing. To evaluate the validity of GTFS feeds, annual vehicle revenue miles and hours from the National Transit Database (NTD) are compared to the calculated values from agencies whose GTFS feeds are available. The key finding of this work is that well-formed GTFS feeds are an accurate representation of transit networks and that the method of aggregation presented in this research can be used to effectively and efficiently calculate metrics for transit agencies. The daily aggregation method is more accurate than the weekly aggregation method, both introduced in this thesis, but practical limitations on processing time favor the weekly method. The reliability of GTFS feed data for smaller agencies is less conclusive than that of larger agencies because of discrepancies found in smaller agencies when their GTFS-generated metrics were compared to those in the NTD. This research will be of particular interest to transit and policy analysts, researchers and transit planners.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The requirement for quantitative soil information has increased as a consequence of the global scenarios. The digital soil mapping (DSM) seeks to produce consistent data with the current needs through the generation of functional soil maps in multi-scales. The aim of this study was to evaluate the altimetry quality and limitations of digital elevation model (DEM) in order to assist in choosing the most suitable DEM to derive terrain attributes (TA) to develop spatial prediction functions to be applied to digital mapping of soil organic carbon (SOC) of farm scale in the Plateau of the state of Rio Grande do Sul (RS). The study was conducted on a 937 ha area located in the municipality of Giruá, RS, Brazil. They collected 243 sampling points in the 0-5 cm layer and an accomplished planialtimetric survey (PS) considered in this study the truth of the ground of altitude values. DEM evaluated were: DEM-PS (generated from the PS), DEM-LETTER (generated by interpolating the level of topographic map curves), DEM-ASTER, DEM- SRTM and DEM-TOPODATA. The DEM were evaluated for precision altimetry through statistical test value of the square root of the mean square error (RMSE) and application of the Brazilian Cartographic Standard for defining the scale of each DEM based on the accuracy of the altitude. TA derived from each DEM were faced with the AT derived from the DEM-PS. The results showed that the DEM-PS presented the best quality of elevation data (RMSE = 1.93 m), followed by DEM-SRTM (RMSE = 5.95 m), DEM- (RMSE = 8.28 m), DEM-TOPODATA (RMSE = 9.78 m) and DEM-ASTER (RMSE = 15.57 m). The size of the area and gently rolling relief were the main factors that influenced the results. The DEM-PS is suited in scale 1: 10,000 Class D, while DEM-LETTER and DEM-SRTM are suited in scale 1: 50,000 class B, the DEM-TOPODATA the scale 1: 50,000 class D and the DEM-ASTER scale 1: 100,000 Class B. With regard to TA, the DEM-SRTM and DEM-TOPODATA present results closer to the DEM-PS and smaller RMSE values for each TA assessed. The prediction function constructed from the DEM-PS derived from the TA and vegetation index Landasat-7 obtained images explained only 16% of the variance in SOC area. The small spatial resolution of DEM-PS and images associated with the use only of these predictors were the main factors that influenced the results. Based on these results, the DEM-SRTM and DEM-TOPODATA can be used in DSM semi-detailed soil classes. In the case of the SOC DSM suggest the use of these DEM associated with field control points to verify the precision altimetry and the inclusion of variables related to soil management practices. / A demanda por informações quantitativas de solos em nível detalhado de bacias hidrográficas vêm aumentado em decorrência dos cenários globais. O mapeamento digital de solos (MDS) visa gerar dados compatíveis com essas necessidades por meio da geração de mapas funcionais de solos em multi-escalas. O objetivo desse trabalho foi avaliar a qualidade altimétrica e limitações de MDE com a finalidade de auxiliar na escolha do MDE mais adequados para derivar atributos do terreno (AT) para desenvolver funções de predição espacial para serem aplicadas ao mapeamento digital do carbono orgânico do solo em escala de propriedade rural no Planalto do Estado do Rio Grande do Sul (RS). O estudo foi realizado em uma área de 937 ha localizada no município de Giruá, RS, Brasil. Foram coletados 243 pontos amostrais na camada de 0-5 cm e realizado um levantamento planialtimétrico (LP) considerado neste estudo a verdade do terreno dos valores de altitude. Os MDE avaliados foram: MDE-LP (gerado a partir do LP), MDE-CARTA (gerado pela interpolação das curvas de nível da carta topográfica), MDE-ASTER, MDE-SRTM e MDE-TOPODATA. Os MDE foram avaliados quanto à precisão altimétrica por meio de teste estatísticos, valor da raiz quadrada do erro médio quadrático (RMSE) e aplicação da Norma Brasileira de Cartografia para definição da escala de cada MDE com base na precisão da altitude. Os AT derivados de cada MDE foram confrontados com os AT derivados do MDE-LP. Os resultados mostraram que o MDE-LP apresentou a melhor qualidade dos dados de altitude (RMSE = 1,93 m), seguido dos MDE-SRTM (RMSE = 5,95 m), MDE-CARTA (RMSE = 8,28 m), MDE-TOPODATA (RMSE = 9,78 m) e MDE-ASTER (RMSE = 15,57 m). O tamanho da área e relevo suave ondulado foram os principais fatores que influenciaram nos resultados. O MDE-LP se adequou na escala 1:10.000 classe D, enquanto os MDE-CARTA e MDE-SRTM se adequaram na escala 1:50.000 classe B, o MDE-TOPODATA a escala 1:50.000 classe D e o MDE-ASTER escala 1:100.000 classe B. Em relação aos AT, os MDE- SRTM e MDE-TOPODATA apresentam resultados mais próximos do MDE-LP e os menores valores de RMSE para cada AT avaliado. A função de predição construída a partir dos AT derivados do MDE-LP e índice de vegetação obtido de imagens Landasat-7 explicou apenas 16% da variância do COS na área. A resolução espacial pequena do MDE-LP e das imagens associado ao uso apenas dessas variáveis preditoras foram os principais fatores que influenciaram nos resultados. Com base nesses resultados, os MDE- SRTM e MDE-TOPODATA podem ser utilizados no MDS semidetalhado de classes de solos. No caso do MDS do COS sugere-se o uso desses MDE associado com pontos de controle de campo para verificação da precisão altimétrica e a inclusão de variáveis relacionadas a práticas de manejo do solo.

Submitted by Biblioteca de Pós-Graduação em Geoquímica BGQ (bgq@ndc.uff.br) on 2018-03-06T16:22:51Z No. of bitstreams: 1 TESE_SANDRA_FERNANDES_ANDRADE.pdf: 6238564 bytes, checksum: c11933fcb48773bb165ea782a4942d4e (MD5) / Made available in DSpace on 2018-03-06T16:22:51Z (GMT). No. of bitstreams: 1 TESE_SANDRA_FERNANDES_ANDRADE.pdf: 6238564 bytes, checksum: c11933fcb48773bb165ea782a4942d4e (MD5) / Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / Universidade Federal Fluminense. Instituto de Química. Programa de Pós-Graduação em Geoquímica, Niterói, RJ / O Mapeamento Digital de Solo (DSM) está evoluindo muito nas últimas décadas, desde a fase de investigação até a produção de mapas em diversas escalas, abrangendo países, regiões e bacias hidrográficas. A predição de classes e propriedades de solos no mapeamento digital fundamenta-se nas relações existentes entre os fatores e processos de formação dos solos. O conhecimento dos atributos químicos dos solos é um fator de grande relevância, visando a utilização racional de corretivos e fertilizantes. O trabalho objetivou realizar a modelagem solo-paisagem de variáveis químicas de fertilidade do solo, a saber, pH em água, Pass(mg/kg), K+(cmolc/kg), C(g/kg), CTC(cmolc/kg), V% e Al(m)%, usando como preditoras as variáveis ambientais Plano de Curvatura, Perfil de Curvatura, Índice de Umidade, Aspecto, Declividade, Tipos de Solo, NDVI, Imagens Landsat 7 (bandas 2, 4 e 7) e Litologia. A área de estudo compreende as regiões mais produtivas do Estado do Rio de Janeiro: Norte, Noroeste e Serrana, entre as coordenadas 43°22´35´´; 40°57´27´´WG, e 20°45´47´´; 22°34´21´´S, com 22.043 km2. Os dados de solos foram extraídos de um banco de dados maior, cedido pela Embrapa Solos. A análise exploratória dos dois bancos de dados identificou valores extremos, que foram expurgados, para manter as características de fertilidade natural e a homogeneidade da amostra, preparando a análise por regressão linear múltipla (RLM). Os parâmetros estatísticos analisados para avaliação dos modelos de RLM foram: AIC, RMSE, Cp, R2 ajustado, F e a probabilidade de F. Aos resultados da RLM, foram adicionados os resultados de krigagem dos resíduos da regressão, uma técnica de DSM conhecida como R+K, que se mostrou um método adequado para o mapeamento digital de propriedades do solo, neste trabalho. Os solos analisados apresentam baixo pH e altos níveis de saturação por Al, bem como baixas concentrações de fósforo assimilável. Os valores de CTC e V(%) estão dentro do intervalo considerado bom para a fertilidade do solo, segundo dados da literatura. O carbono apresentou níveis considerados bons para a fertilidade do solo, principalmente, nas áreas de baixada da região Norte. Não foi possível realizar uma síntese de fertilidade do solo considerando simultaneamente todas as variáveis estudadas, pois elas não se distribuem espacialmente dentro dos critérios de boa fertilidade preconizados na literatura. Entretanto, foi possível a realização de dois mapas-sínteses, aproveitando a boa correlação entre CTC e K+ e entre pH e V%. O primeiro mapa-síntese, com as variáveis K+ e CTC, identificou, na região da baixada Norte fluminense uma faixa considerada boa para a fertilidade do solo. O segundo mapa-síntese, com as variáveis pH e V%, mostra que as regiões com boa fertilidade do solo coincidem com as regiões de médio e alto valores de V% e com valores também mais elevados de pH, o que ocorre, principalmente, na região Noroeste. As regiões que foram consideradas de baixa fertilidade coincidem com regiões de pH ácido, principalmente nas regiões Serrana e Norte. / Soil Digital Mapping (DSM) has been evolving over the past decades, from the investigation period to the production of maps in several scales, covering countries, regions and hydrographic basins. The prediction of classes and properties of the soils at the digital mapping is based on the existing relations between the factors and processes on the soil formation. The knowledge of the chemical qualities of the soil is a key point, aiming the rational use of correctives and fertilizers. This thesis had the objective of modeling the chemical variables of soil fertility, namely:pH in water, Pass(mg/kg), K+(cmolc/kg), C(g/kg), CEC(cmolc/kg), V% and Al(m)%, using as predictors the curvature plan and curvature profile, , aspect and declivity of the slopes, types of soil and its humidity level, NDVI, Landsat 7 images (2,4 and 7 bands) and litology. The area of study encompasses the most productive regions of Rio de Janeiro State: North, Northwest and Mountaineous, at 43°22´35´´; 40°57´27´´WG, e 20°45´47´´; 22°34´21´´S, covering 22,043 km2. Soil idata was taken from a wider database, provided by Embrapa Solos. The exploratory analyses of the two databases identified extreme values, that were discarded, to keep the characteristics of natural fertility and homogeneity of the sample, preparing the analyses by multiple linear regression (MLR). The statistic parameters analyzed by MLR models were: AIC, RMSE, Cp, adjusted R2, F and F probability. The results of the MLR were added to the results of the krigage of regression residue, a DSM technic known as R+K, that seemed to be an adequate method for digital mapping of soil properties, at this work. The analyzed soils showed low pH and high levels of Al saturation, as well as low concentrations of assimilative phosphorus. The CEC and V (%) values are on a good range to soil fertility, according to literature data. Carbon showed good levels for soil fertility, especially at the low terrains of the North region. It was not possible to achieve a synthesis of the soil fertility considering simultaneously all the studied varieties, since they are not homogeneous spatially. However, it was possible to make two synthesis-maps, using the good correlation between CEC and K+ and between pH and V%. The first synthesis-map, with the variegated K+ and CEC, identified, at the area of low lands of North of Rio de Janeiro State a lane considered good for soil fertility. The second synthesis-map, with the variegated pH and V%, shows that the areas with good soil fertility are the same of the areas of medium and high values of V% and with higher values of pH, which happens mainly at the Northwest. The areas that were considered with low fertility are the same with acid pH, specially the North and Mountaineous areas.

D. Tech. (Department of Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / Simultaneous Localization and Mapping (SLAM) is a significant problem that has been extensively researched in robotics. Its contribution to autonomous robot navigation has attracted researchers towards focusing on this area. In the past, various techniques have been proposed to address SLAM problem with remarkable achievements but there are several factors having the capability to degrade the effectiveness of SLAM technique. These factors include environmental noises (light intensity and shadow), dynamic environment, kidnap robot and computational cost. These problems create inconsistency that can lead to erroneous results in implementation. In the attempt of addressing these problems, a novel SLAM technique Known as DIK-SLAM was proposed. The DIK-SLAM is a SLAM technique upgraded with filtering algorithms and several re-modifications of Monte-Carlo algorithm to increase its robustness while taking into consideration the computational complexity. The morphological technique and Normalized Differences Index (NDI) are filters introduced to the novel technique to overcome shadow. The dark channel model and specular-to-diffuse are filters introduced to overcome light intensity. These filters are operating in parallel since the computational cost is a concern. The re-modified Monte-Carlo algorithm based on initial localization and grid map technique was introduced to overcome the issue of kidnap problem and dynamic environment respectively. In this study, publicly available dataset (TUM-RGBD) and a privately generated dataset from of a university in South Africa were employed for evaluation of the filtering algorithms. Experiments were carried out using Matlab simulation and were evaluated using quantitative and qualitative methods. Experimental results obtained showed an improved performance of DIK-SLAM when compared with the original Monte Carlo algorithm and another available SLAM technique in literature. The DIK-SLAM algorithm discussed in this study has the potential of improving autonomous robot navigation, path planning, and exploration while it reduces robot accident rates and human injuries.

Thesis (MScAgric (Agricultural Economics))—University of Stellenbosch, 2005. / The study broadly assesses the usefulness of available digital spatial land resource data as a source for agritourism and ecotourism information by comparing the inventory of available spatial data sets for South Africa and the SADC region, with the needs for spatial data as derived from a literature study of travel motivations and demand determinants. Spatial land resource data have been collected, processed and stored for agricultural planning purposes, like land suitability assessment, agricultural production and infrastructural planning. Given a) the growth in agritourism and ecotourism, b) the more detailed information required by tourists to aid them during decision making processes like destination selection and c) the progress in information technology rendering access of information via the internet easier; the question arose whether the available land resource digital data can be processed to provide relevant tourism information on internet websites. Four tasks had to be done, namely: a) identifying tourists’ needs by means of a literature study on travel motivations and demand determinants; b) identifying the land resource data sets that could be processed into information to meet these identified needs; c) determining the accessibility of spatial information on internet tourism websites to potential agritourists and ecotourists, and d) exploring opportunities for adding value by looking at what information existing websites are offering in comparison with what can be obtained from repackaging the land resource data. Common ground was found between the spatial tourist information needs and the available spatial land resource data. This, coupled with the ability of combining meteorological and other humanmade environmental data in GIS modelling, suggests that repackaging land resource data seems to have the potential to offer useful tourism information in correspondence with confirmed tourist information needs.