The concept of proximity is an important aspect of human reasoning. Despite the diversity of applications that require proximity measures, the most intuitive notion is that of spatial nearness. The aim of this thesis is to investigate the underpinnings of the notion of nearness, propose suitable formalisations and apply them to the processing of GIS data. More particularly, this work offers a framework for spatial proximity that supports the development of more intuitive tools for users of geographic data processing applications. Many of the existing spatial reasoning formalisms do not account for proximity at all while others stipulate it by using natural language expressions as symbolic values. Some approaches suggest the association of spatial relations with fuzzy membership grades to be calculated for locations in a map using Euclidean distance. However, distance is not the only factor that influences nearness perception. Hence, previous work suggests that nearness should be defined from a more basic notion of influence area. I argue that this approach is flawed, and that nearness should rather be defined from a new, richer notion of impact area that takes both the nature of an object and the surrounding environment into account. A suitable notion of nearness considers the impact areas of both objects whose degree of nearness is assessed. This is opposed to the common approach of only taking one of both objects, seen as a reference to assess the nearness of the other to it, into consideration. Cognitive findings are incorporated to make the framework more relevant to the users of Geographic Information Systems (GIS) with respect to their own spatial cognition. GIS users bring a wealth of knowledge about physical space, particularly geographic space, into the processing of GIS data. This is taken into account by introducing the notion of context. Context represents either an expert in the context field or information from the context field as collated by an expert. In order to evaluate and to show the practical implications of the framework, experiments are conducted on a GIS dataset incorporating expert knowledge from the Touristic Road Travel domain.

L'imagerie hyperspectrale, grâce à un nombre élevé de bandes spectrales très fines et contigües, est capable d'associer àchaque pixel d'une image une signature spectrale caractéristique du comportement réflectif du matériau ou du mélange dematériaux présents dans ce pixel. La plupart des algorithmes de classification tirent profit de cette grande profusiond'information spectrale mais exploitent très peu l'information contextuelle existant entre les pixels appartenant à un mêmevoisinage. L'objectif de cette thèse est de réaliser de nouveaux algorithmes utilisant simultanément les informations spectraleet spatiale à des fins de classification et d'étudier la complémentarité de ces deux types d'information dans divers contextes.Dans cette optique nous avons développé trois scénarios de classification sensiblement différents, chacun étant adapté à untype d'application particulier.Nous avons tout d'abord développé un procédé d'extraction puis de classification vectorielle d'un ensemble de caractéristiquesspectrales et spatiales. Les caractéristiques spectrales sont extraites au moyen de méthodes visant à réduire la dimension desimages hyperspectrales tout en conservant une majorité de l'information utile. Les caractéristiques spatiales sont quant àelles produites par l'intermédiaire d'outils de caractérisation de la texture (matrices de co-occurrence et spectres de texture)ou de la forme (profils morphologiques). Nous nous sommes ensuite intéressés à la modélisation markovienne et avonsentrepris d'adapter un algorithme de classification de type Conditional Random Field à un contexte hyperspectral. Notretroisième et dernière approche s'appuie sur une segmentation préalable de l'image afin de réaliser une classification parzones et non plus par pixels.L'information spectrale pure permet de regrouper efficacement des pixels présentant des signatures spectrales similaires etsuffit généralement dans le cadre de problèmes de classification ne faisant intervenir que des classes sémantiquement trèsprécises, liées à un unique type de matériau. Les classes plus générales (utilisées par exemple pour des applicationsd'aménagement des sols) se composent en revanche de plusieurs matériaux parfois communs à plusieurs classes et agencésselon des motifs qui se répètent. Caractérisables à la fois spatialement et spectralement, ces classes sont susceptibles d'êtreplus complètement décrites par une utilisation simultanée de ces deux types d'information. Pour conclure cette étude, nousavons effectué une comparaison des trois méthodes d'intégration de l'information spatiale au processus de classification selonles trois critères sont la précision de classification, la complexité algorithmique et la robustesse / Thanks to a high number of thin and contiguous spectral bands, the hyperpectral imagery can associate to each pixel of animage a spectral signature representing the reflective behaviour of the materials composing the pixel. Most of theclassification algorithms use this great amount of spectral information without noticing the contextual information betweenthe pixels that belong to the same neighborhood. This study aims to realize new algorithms using simultaneously the spectraland spatial informations in order to classify hyperspectral images, and to study their complementarity in several contexts. Forthis purpose, we have developped three different classification scenarios, each one adapted to a particular type of application.The first scenario consists in a vectorial classification processus. Several spectral and spatial characteristics are extracted andmerged in order to form a unique data set, which is classified using a Support Vector Machine method or a Gaussian MixingModel algorithm. The spectral characteristics are extracted using dimension reduction method, such as PCA or MNF, while thespatial characteristics are extracted using textural characterization tools (co-occurrence matrices and texture spectra) ormorphological tools (morphological profiles). For the second scenario, we adapted a Conditional Random Field algorithm tothe hyperspectral context. Finally, the last scenario is an area-wise classification algorithm relying on a textural segmentationmethod as a pre-processing step.The spectral information is generally sufficient to deal with semantically simple classes, linked to a unique type of material.Complex classes (such as ground amenagment classes) are composed of several materials which potentially belong to morethan one class. Those classes can be characterized both spectrally and spatially, which means that they can be morecompletly described using both spectral and spatial informations. To conclude this study, we compared the threespectral/spatial classification scenarios using three criterions : classification accuracy, algorithmic complexity and strength.

Neste trabalho foram pesquisados os métodos e procedimentos utilizados na execução de obras das redes subterrâneas da infra-estrutura urbana, desde a demarcação até a elaboração da planta do levantamento de como construído. Os equipamentos utilizados na execução de obras, tanto os não destrutivos, como os destrutivos e aqueles de localização de dutos e cabos enterrados. São também apresentados e detalhados os procedimentos à luz das normas técnicas, para o devido georreferenciamento das redes de infra-estrutura subterrânea. Foram inclusive analisados os resultados obtidos para o posicionamento das redes, conforme apresenta o estudo de casos, em obras com a utilização de equipamentos para a localização de cabos e dutos enterrados. Finalmente são sugeridas propostas para o georreferenciamento das redes de infra-estrutura urbana com a finalidade de constituição de um cadastro único. / This study investigates the methods and procedures used in the urban infrastructure underground network, from the demarcation to the production of the as-built survey plant. The equipments used in the execution of services, as far as non destructive, destructive as well as in the localization of underground pipe and cables are concerned, are presented and the procedures are detailed for underground infrastructure network georeferencing, considering the standard norms. The results of the network positioning with the utilization of equipments for underground pipes and cables equipments are analysed, as shown in the case study. Finally, proposals for the urban underground network georeferencing are presented in order to build a unique cadastre.

Object detection is a prominent area of research within computer vision. While object detection based on infrared videos holds great practical significance, the majority of mainstream methods are primarily designed for visible datasets. This thesis investigates the enhancement of object detection accuracy on infrared datasets by leveraging temporal and spatial information. The Memory Enhanced Global-Local Aggregation (MEGA) framework is chosen as a baseline due to its capability to incorporate both forms of information. Based on the initial visualization result from the infrared dataset, CAMEL, the noisy characteristic of the infrared dataset is further explored. Through comprehensive experiments, the impact of temporal and spatial information is examined, revealing that spatial information holds a detrimental effect, while temporal information could be used to improve model performance. Moreover, an innovative Dual Frame Average Aggregation (DFAA) framework is introduced to address challenges related to object overlapping and appearance changes. This framework processes two global frames in parallel and in an organized manner, showing an improvement from the original configuration. / Objektdetektion är ett framträdande forskningsområde inom datorseende. Även om objektdetektering baserad på infraröda videor har stor praktisk betydelse, är majoriteten av vanliga metoder i första hand utformade för synliga datauppsättningar. Denna avhandling undersöker förbättringen av objektdetektionsnoggrannhet på infraröda datauppsättningar genom att utnyttja tids- och rumslig information. Memory Enhanced Global-Local Aggregation (MEGA)-ramverket väljs som baslinje på grund av dess förmåga att införliva båda formerna av information. Baserat på det initiala visualiseringsresultatet från den infraröda datamängden, CAMEL, utforskas den brusiga karaktäristiken för den infraröda datamängden ytterligare. Genom omfattande experiment undersöks effekten av tids- och rumslig information, vilket avslöjar att den rumsliga informationen har en skadlig effekt, medan tidsinformation kan användas för att förbättra modellens prestanda. Dessutom introduceras en innovativ Dual Frame Average Aggregation (DFAA) ramverk för att hantera utmaningar relaterade till objektöverlappning och utseendeförändringar. Detta ramverk bearbetar två globala ramar parallellt och på ett organiserat sätt, vilket visar en förbättring från den ursprungliga konfigurationen.

Despite considerable research, the effects of common types of noise on verbal and spatial information processing are still relatively unknown. Three experiments, using convenience sampling were conducted to investigate the effect of auditory interference on the cognitive performance of 24 adult men and women during the Stroop test, perception of object recognition and spatial location tasks, and the perception of object size, shape, and spatial location tasks. The data were analyzed using univariate analysis of variance and 1-way multivariate analysis of variance. The Experiment 1 findings indicated reaction time performance for gender and age group was affected by auditory interference between experimental conditions, and recognition accuracy was affected only by experimental condition. The Experiment 2a results showed reaction time performance for recognizing object features was affected by auditory interference between age groups, and recognition accuracy by experimental condition. The Experiment 2b results demonstrated reaction time performance for detecting the spatial location of objects was affected by auditory interference between age groups. In addition, reaction time was affected by the type of interference and spatial location. Further, recognition accuracy was affected by interference condition and spatial location. The Experiment 3 findings suggested reaction time performance for assessing part-whole relationships was affected by auditory interference between age groups. Further, recognition accuracy was affected by interference condition between experimental groups. This study may create social change by affecting the design of learning and workplace environments, the neurological correlates of auditory and visual stimuli, and the pathologies of adults such as attention deficit hyperactivity disorder.

Are decision-makers, and public ones in particular, considering the spatial characteristics of territories when they are making decisions? Which elements should be included in computer-based systems supporting such decisions? These two questions summarise the issues geographic information system scientists are addressing. They also constitute the starting point of this investigation on the theme of errors and uncertainty in spatial decision support systems. While decision theories, methodologies and techniques abound, none are peculiar to spatial issues. At best, they are using spatial data and in a few cases they are applied to helping solve spatial problems. It has been recognised that spatial data need distinct management systems. Should it be the same for spatial decisions? By postulating that spatial decision is a specific field requiring its own treatise, this author initiates an original reflexion. Following a holistic approach, this theoretical work develops a conceptual decision model: the 'decisional fountain'. This model gives a coherent and integrated view on the various fields of decision-making. Based on the postulate and on the model developed, several theories and techniques are revisited in a truly spatial perspective. The ontology of spatial decision has been enriched by a variety of experiences. Dealing with drought at the European level, allocating water resources from the field scale to the country scale, regional spatial planning, performing strategic environmental assessment, conceptualising the parking of a vehicle, developing the spatial abilities of children, all have fed this conceptual research. Some of them are illustrating this manuscript. Taking a spatial information science perspective, this manuscript leads you towards a 'spatial decision' theory.

This thesis presents the results from a comparative study of travel patterns among residents of four suburban residential areas in metropolitan Adelaide. Using existing datasets together with inventory data of urban environment characteristics from original fieldwork, this research examines to what extent there are associations between various attributes of a particular urban location as they relate to travel behaviour and household socio-economics. The findings derived from quantitative and qualitative methods suggest that urban form/design must be taken into consideration in policy making for mobility reduction.

This research found that Geospatial Information Systems (GIS) or spatial mapping provides the potential for significantly improving asset management flexibility. Space relates everything to everything else so spatial relationships can replace technically constructed relationships found in typical databases. This means that the effort associated with database re-design in the face of change is significantly reduced, or removed.

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A sustainable society is a society that satisfies its resource requirements without endangering the sustainability of these resources. The mineral endowment on the African continent is estimated to be the first or second largest of world reserves. Therefore, it is recognised that the African continent still heavily depends on mineral exports as a key contributor to the gross domestic product (GDP) of various countries. These mining activities, however, do introduce primary and secondary environmental degradation factors. They attract communities to these mining areas, light and heavy industrial establishments occur, giving rise to artisanal activities. This study focussed on satellite RS products as an aid to a mine’s operations and the monitoring of its environment. Effective operational mine management and control ensures a more sustainable and profitable lifecycle for mines. Satellite based RS holds the potential to observe the mine and its surrounding areas at high temporal intervals, different spectral wavelengths and spatial resolutions. The combination of SAR and optical information creates a spatial platform to observe and measure the mine’s operations and the behaviour of specific land cover and land use classes over time and contributes to a better understanding of the mining activities and their influence on the environment within a specific geographical area. This study will introduce an integrated methodology to collect, process and analyse spatial information over a specific targeted mine. This methodology utilises a medium resolution land cover base map, derived from Landsat 8, to understand the predominant land cover types of the surrounding area. Using very high resolution mono- and stereoscopic satellite imagery provides a finer scale analysis and identifies changes in features at a smaller scale. Combining these technologies with the synthetic aperture radar (SAR) applications for precise measurement of surface subsidence or upliftment becomes a spatial toolbox for mine management. This study examines a combination of satellite remote sensing products guided by a systematic workflow methodology to integrate spatial results as an aid for mining operations and environmental monitoring. Some of the results that can be highlighted is the successful land cover classification using the Landsat 8 satellite. The land cover that dominated the Kolomela mine area was the “SHRUBLAND/GRASS” class with a 94% coverage and “MINE” class of 2.6%. Sishen mine had a similar dominated land cover characteristic with a “SHRUBLAND/GRASS” class of 90% and “MINE” class of 4.8%. The Pléiades time-series classification analysis was done using three scenes each acquired at a different time interval. The Sishen and Kolomela mine showed especially changes from the bare soil class to the asphalt or mine class. The Pléiades stereoscopic analysis provided volumetric change detection over small, medium, large and recessed areas. Both the Sishen and Kolomela mines demonstrated height profile changes in each selected category. The last category of results focused on the SAR technology to measure within millimetre accuracy the subsidence and upliftment behaviour of surface areas over time. The Royal Bafokeng Platinum tailings pond area was measured using 74 TerraSAR-X scenes. The tailings wall area was confirmed as stable with natural subsidence that occurred in its surrounding area due to seasonal changes of the soil during rainy and dry periods. The Chuquicamata mine as a large open pit copper mine area was analysed using 52 TerraSAR-X scenes. The analysis demonstrated significant vertical surface movement over some of the dumping sites. It is the wish of the researcher that this dissertation and future research scholars will continue to contribute in this scientific field. These contributions can only assist the mining sector to continuously improve its mining operations as well as its monitoring of the primary as well as the secondary environmental impacts to ensure improved sustainability for the next generation. / Environmental Sciences / M. Sc. (Environmental Science)