O número e a intensidade dos desastres naturais têm aumentado em todo o mundo devido às mudanças climáticas. Atualmente, as inundações representam a maior parte dos desastres naturais e causam mais danos, mortes e impactos econômicos do que qualquer outro tipo de fenômeno natural. No Brasil, as inundações se intensificam principalmente no período de chuvas, entre os meses de Dezembro e Março, ocasionando dezenas de mortes, além de impactos econômicos, sociais e ambientais. Assim, prevenir esse tipo de desastre tem se tornado um fator importante para minimizar os impactos por ele provocados. Para isso, são necessárias informações atualizadas, completas e precisas sobre o atual estado das variáveis ambientais. Nesse contexto, as informações voluntárias estão sendo utilizadas como fonte de dados complementar para a gestão de risco de inundação, devido ao número elevado de voluntários que atuam como \"sensores\". Contudo, outras informações relacionadas a inundação estão dispersas em diferentes fontes de dados, dificultando as ações de resposta das agências de emergência. Neste trabalho e proposta uma abordagem que visa apoiar a gestão de risco de inundação, fornecendo mecanismos para a obtenção de informações voluntárias para esse contexto e permitindo a disponibilização dessas por meio de serviços geoespaciais em tempo real. Para tanto, mecanismos de interpretação foram definidos para apoiar os voluntários durante a análise e medição da altura da água, sendo essas informações fornecidas por meio de uma plataforma de crowdsourcing. Além disso, um framework foi desenvolvido a fim de disponibilizar as informações voluntárias de forma interoperável por meio de serviços geoespaciais. Ao final, foram realizados estudos experimentais para avaliar a eficácia dos mecanismos desenvolvidos para a obtenção de informações voluntárias para gestão de risco de inundação / The number and intensity of natural disasters have increased worldwide due to climate change. Currently, floods represent most natural disasters and cause more damage, deaths and economic impacts than any other natural phenomenon. In Brazil, the floods are intensified especially during the rainy season, between the months of December and March, causing dozens of deaths, as well as economic, social and environmental impacts. Thus, preventing this kind of disaster has become an important factor to minimize the impacts caused by it. For this, it\'s necessary up-to-date, complete and accurate information about the current state of the environmental variable. In this context, volunteer information is being used as a complementary data source for flood risk management, due to the high number of volunteers who act as \"sensors\". However, other information related to flooding are scattered in different data sources, hindering response actions of emergency agencies. This dissertation proposes an approach to support flood risk management, providing mechanisms for obtaining volunteer information for this context and allowing the availability of these by means of geospatial services in real time. For this, interpretation mechanisms were defined to support the volunteers during the analysis and measurement of the water height, being this information provided by means of crowdsourcing platform. Additionally, a framework was developed to provide volunteer information in an interoperable way through geospatial services. Finally, experimental studies were conducted to evaluate the effectiveness of the mechanisms developed to obtaining volunteer information for flood risk management

Advances in information and communication technology and the ready availability of Global Positioning Systems (GPS) have made it possible for citizens to create information on the internet expressing their personal perceptions in the form of pictures, videos and text narratives associated with geographic locations. The term Volunteered Geographic information (VGI) was coined to describe the processes whereby non-professionals or “citizen scientists” participate directly in spatial data creation, editing and shared use. VGI offers promise as an innovative way for members of the public to participate directly in the use, production and sharing of spatial information that is relevant to issues of personal or community concern and as a means of addressing some of the issues associated with traditional public participation methods. Planners can find meaning in the heterogeneous, time-sensitive, geo-social geographic information created by citizen volunteers in a bottom-up participation process where planners give up some control over what data is collected and from whom. However, uncertainties associated with volunteered geographic information include relevance, credibility, representativeness and quality of the geographic information. This thesis investigates the opportunities and barriers to the use of volunteered geographic information as public participation in planning. A framework and methodology for collaborative quality control of VGI through multi-criteria subjective relevance ratings of the VGI by its producers and users is put forward in this thesis. The relevance rating framework for quality control of VGI is based on the use of relevance in information retrieval in information science to improve the relevance of search engine results. This concept is transferred to the quality control of VGI contributions to determine the best VGI contributions to be used in planning as public participation. A VGI web application prototype, including the subjective relevance rating system, was created and a methodology and demonstration of its use for public participation was presented.

The field of crime mapping has an extensive history, yet it has managed to remain an effective tool for policing even in modern times. This success can be attributed in part to the field’s willingness to adapt to newer technologies as they have become available. A current trend that is occurring internationally is the practice of online crime mapping. Many police services from around the world have recognized the importance of using the Internet to connect with the public that they serve. To this end, while most police services have an online presence in the form of a Web site, some have opted to go further and to publish their crime data spatially in the form of an interactive Web-based mapping application. Presently, the City of Toronto has opted not to engage in interactive Web mapping and has limited their online publications to only static maps and written crime reports. This thesis attempts to build upon the capabilities that are offered by Web GIS tools for crime mapping applications in the City of Toronto. To achieve this, two Web applications were developed to help facilitate the process of reporting crime incidents and gang-related graffiti. The services in these Web applications were developed using ArcGIS for Desktop 10.1 and hosted using ArcGIS for Server 10.1, while the Web applications themselves were developed using the ArcGIS API for JavaScript. Each application was designed to support interactive incident mapping, as well as anonymous incident reporting. In addition, the Graffiti Tagger application utilized a mobile-themed interface and image attachments to promote on-the-go graffiti incident reporting. By doing this, it was hypothesized that the overall quality and quantity of data contributed to the Toronto Police Service would increase. To test this hypothesis, a survey was developed and released to a number of participants with varying backgrounds and technical skill levels. The results of this survey showed that a public desire did exist for both of these Web applications, along with a willingness from the majority of participants to voluntarily participate in using these applications. These results suggest that adopting the use of Web mapping applications has the potential to increase the quantity, and potentially the quality, of crime data that is reported.

Recent advances in information technology such as Web mapping and location-aware mobile devices have enabled non-experts to create, use and share volumes of spatial data in an increasingly accessible fashion. Such user-generated spatial data is usually referred to as Volunteered Geographic Information (VGI). Two of the fundamental challenges associated with the exploitation of VGI relate to information overload and extraction of meaning. In order to deal with these challenges and improve the utility of VGI, this thesis investigates the potential of several interactive geovisualization techniques including filtering, dynamic spatial aggregation, linking and brushing, and tag-based visualizations. As a preliminary work to explore and structure the new research field of VGI, a framework of the different types of VGI is elaborated and followed by a review of the challenges and current solutions related to the utilization of VGI. Based on this review, a web-based prototype is developed to serve as a platform for the evaluation of selected geovisualization techniques. The prototype is then used in a series of workshops with rich citizen-generated data related to place-based community assets. The results of the case study show that the implemented geovisualization techniques enable users to find relevant subsets of information and to gain new insights on the data. Based on the potential shown by these results, future research directions are suggested.

The field of crime mapping has an extensive history, yet it has managed to remain an effective tool for policing even in modern times. This success can be attributed in part to the field’s willingness to adapt to newer technologies as they have become available. A current trend that is occurring internationally is the practice of online crime mapping. Many police services from around the world have recognized the importance of using the Internet to connect with the public that they serve. To this end, while most police services have an online presence in the form of a Web site, some have opted to go further and to publish their crime data spatially in the form of an interactive Web-based mapping application. Presently, the City of Toronto has opted not to engage in interactive Web mapping and has limited their online publications to only static maps and written crime reports. This thesis attempts to build upon the capabilities that are offered by Web GIS tools for crime mapping applications in the City of Toronto. To achieve this, two Web applications were developed to help facilitate the process of reporting crime incidents and gang-related graffiti. The services in these Web applications were developed using ArcGIS for Desktop 10.1 and hosted using ArcGIS for Server 10.1, while the Web applications themselves were developed using the ArcGIS API for JavaScript. Each application was designed to support interactive incident mapping, as well as anonymous incident reporting. In addition, the Graffiti Tagger application utilized a mobile-themed interface and image attachments to promote on-the-go graffiti incident reporting. By doing this, it was hypothesized that the overall quality and quantity of data contributed to the Toronto Police Service would increase. To test this hypothesis, a survey was developed and released to a number of participants with varying backgrounds and technical skill levels. The results of this survey showed that a public desire did exist for both of these Web applications, along with a willingness from the majority of participants to voluntarily participate in using these applications. These results suggest that adopting the use of Web mapping applications has the potential to increase the quantity, and potentially the quality, of crime data that is reported.

Recent advances in information technology such as Web mapping and location-aware mobile devices have enabled non-experts to create, use and share volumes of spatial data in an increasingly accessible fashion. Such user-generated spatial data is usually referred to as Volunteered Geographic Information (VGI). Two of the fundamental challenges associated with the exploitation of VGI relate to information overload and extraction of meaning. In order to deal with these challenges and improve the utility of VGI, this thesis investigates the potential of several interactive geovisualization techniques including filtering, dynamic spatial aggregation, linking and brushing, and tag-based visualizations. As a preliminary work to explore and structure the new research field of VGI, a framework of the different types of VGI is elaborated and followed by a review of the challenges and current solutions related to the utilization of VGI. Based on this review, a web-based prototype is developed to serve as a platform for the evaluation of selected geovisualization techniques. The prototype is then used in a series of workshops with rich citizen-generated data related to place-based community assets. The results of the case study show that the implemented geovisualization techniques enable users to find relevant subsets of information and to gain new insights on the data. Based on the potential shown by these results, future research directions are suggested.

Advances in information and communication technology and the ready availability of Global Positioning Systems (GPS) have made it possible for citizens to create information on the internet expressing their personal perceptions in the form of pictures, videos and text narratives associated with geographic locations. The term Volunteered Geographic information (VGI) was coined to describe the processes whereby non-professionals or “citizen scientists” participate directly in spatial data creation, editing and shared use. VGI offers promise as an innovative way for members of the public to participate directly in the use, production and sharing of spatial information that is relevant to issues of personal or community concern and as a means of addressing some of the issues associated with traditional public participation methods. Planners can find meaning in the heterogeneous, time-sensitive, geo-social geographic information created by citizen volunteers in a bottom-up participation process where planners give up some control over what data is collected and from whom. However, uncertainties associated with volunteered geographic information include relevance, credibility, representativeness and quality of the geographic information. This thesis investigates the opportunities and barriers to the use of volunteered geographic information as public participation in planning. A framework and methodology for collaborative quality control of VGI through multi-criteria subjective relevance ratings of the VGI by its producers and users is put forward in this thesis. The relevance rating framework for quality control of VGI is based on the use of relevance in information retrieval in information science to improve the relevance of search engine results. This concept is transferred to the quality control of VGI contributions to determine the best VGI contributions to be used in planning as public participation. A VGI web application prototype, including the subjective relevance rating system, was created and a methodology and demonstration of its use for public participation was presented.

Les plateformes de crowdsourcing spatial (PCS) sont des systèmes qui permettent à des personnes, appelées commanditaires, de publier des tâches spatiales afin de trouver la main-d’œuvre pour les exécuter. Ces tâches spatiales exigent que leurs exécutants soient à un endroit donné, souvent dans une fenêtre de temps donnée, pour être accomplies. Quelques exemples de PCS sont Uber et TaskRabbit. Les PCS suscitent beaucoup d’intérêt dans la recherche, mais des pistes de recherche sont encore à explorer.Doan et al. [2011] a soutenu que l’objectif réside maintenant dans “la construction de plateformes générales de crowdsourcing qui peuvent être utilisées pour développer rapidement ces systèmes”. Depuis, peu de travaux ont porté sur la conception technique des PCS. En outre, il existe un écart entre ce qui est mis en oeuvre par les PCS de l’industrie et les propositions que l’on trouve dans la littérature scientifique. Nous proposons GENIUS-C, une architecture générique pour les PCS. Nous fournissons une implémentation de référence (IR) pour GENIUS-C, fonctionnant comme un cadre pour le développement de PCS. GENIUS-C et son IR sont destinés à combler les écarts entre le monde académique et industriel, et faciliter la compréhension et le développement rapide de PCS.Nous étudions également l’important problème de l’appariement des exécutants et des tâches d’un PCS. Comment peut-on trouver une ou plusieurs tâches adaptées à un exécutant (et vice versa)? Certains utilisent des techniques de système de recommandation, d’autres des approches d’optimisation. La plupart d’entre eux ne tiennent pas compte des dimensions spatio-temporelles des tâches et des exécutants. Ceux qui en tiennent compte ignorent les préférences des exécutants, des commanditaires ou du système lui-même. Dans ce contexte, nous identifions et modélisons le problème réel et récurrent suivant: une fois que l’exécutant est prêt à accomplir des tâches, quelle est la meilleure séquence de tâches à suivre en respectant ses contraintes spatio-temporelles? Comment cette séquence peut-elle être obtenue en tenant compte des préférences de l’exécutant, des commanditaires, du système lui-même ou d’une combinaison de ceux-ci? Nous nommons cette situation le Problème de la Recommandation de Trajectoire, auquel nous proposons une solution optimale, et étudions des heuristiques d’approximation pour le résoudre. / Spatial Crowdsourcing Platforms (SCP) are systems that allow people, called requesters, to publish spatial tasks in order to find suitable workforce to perform it. These spatial tasks require workers to be at a given location, usually within a given time window, to be accomplished. Some examples of SCPs are: Uber, BlaBlaCar and TaskRabbit. SCPs are source of much interest for academy, however several research opportunities remain.Doan et al. [2011] argued that the race is now on “toward building general crowdsourcing platforms that can be used to develop such systems quickly". Since then, little has been done to investigate the technical design of SCPs precisely. Also, there is a gap between what is done in commercial platform and in scientific literature. We propose GENIUS-C, a generic architecture for SPCs. We provide a reference implementation (RI) for GENIUS-C, that works as a framework for the development of SCPs. GENIUS-C and its RI are meant to fill the gap between the academic and industry world, and facilitate the understanding and the quick development of new SCPs.We also study the important problem of matching workers and tasks. How can we find one or more tasks suitable for a worker (and vice versa)? Some tackle this issue using recommender system techniques, others optimization approaches. Most of them do not take into account the spatiotemporal dimensions of tasks and workers. Others take it into account, but to ignore the preferences of either workers, requesters or the system itself. In this context, we identify and model the following common real-life problem: once a worker is willing to spend sometime accomplishing tasks, what is the best sequence of tasks to be followed respecting their spatiotemporal constraints? How can this sequence be obtained taking into account the preferences of the worker, the requesters, the system itself, or a combination of them? We name this situation the Trajectory Recommendation Problem (TRP), propose a feasible exact solution and study approximation heuristics for it.

O Brasil é considerado o país da megadiversidade por abrigar diversas espécies de flora e fauna. Dessa forma preservar essa diversidade é extremamente importante, pois a vida no planeta depende dos muitos ecossistemas que compõem essa biodiversidade. Atualmente, vários estudos sobre formas de recuperar e acessar informações sobre biodiversidade vem sendo discutidos na comunidade científica. Muitas instituições importantes têm disponibilizado gratuitamente seus registros de coletas disponíveis abertamente em repositórios online. No entanto, os dados disponibilizados nesses repositórios contêm informações geográficas imprecisas ou ausentes. Isso acarreta vários problemas como, por exemplo, a inviabilidade da realização de planos sistemáticos para preservar áreas para conservação de espécies ameaçadas. O problema principal para a realização desse plano é determinar com precisão a distribuição dessas espécies. Nesse contexto, o problema de pesquisa identificado é a necessidade de melhorar as informações geográficas contidas em dados sobre biodiversidade disponíveis em repositórios online. Para atacar esse problema, o SWI Gazetteer foi desenvolvido. Ele usa tecnologias da Web Semântica r técnicas de Recuperação de Informação Geográfica para associar coordenadas geográficas a nomes de lugares. Quando procuram por lugares, usuários podem realizar buscas semânticas que conseguem melhores resultados (em relação à precisão e cobertura de dados) que buscas tradicionais por palavras chaves. O Gazetteer também permite a difusão de suas informações usando formatos dos padrões Linked Open Data. Os resultados dos experimentos mostram que o SWI Gazetteer é capaz de aumentar, em até 102%, o número de registros com coordenadas geográficas em amostras representativas de repositórios de dados sobre biodiversidade bem conhecidos (como GBIF e SpecielLink). / Brazil is considered a mega-diversity country for harboring various species of flora and fauna. Therefore preserve this diversity is extremely important, because the life on the planet depends on the many ecosystems that comprise this biodiversity. Currently, several studies on how to recover and access biodiversity information are being discussed within the academic community. Various important institutions have made their biological collection records openly available in online repositories. However, the data available in these repositories contain inaccurate or missing geographic information. This leads to various problems, such as the impossibility of carrying out systematic plans to preserve areas for endangered species. The main problem in realizing these plans is to accurately determine the geographic distributions for these species. In this context, the identified research problem is the need to improve geographic information contained in biodiversity data available in the online repositories. To tackle this problem, the SemanticWeb Interactive Gazetteer (SWI Gazetteer) was developed. It uses Semantic Web technologies and Geographic Information Retrieval techniques to associate geographic coordinates to place names. When searching for places, users can perform semantic searches that achieve better results (in terms of accuracy and data coverage) than traditional keyword search. The gazetteer also allows the dissemination of its information using standard Linked Open Data formats. Experiment results shown that the SWI Gazetteer is able to increase, in up to 102%, the amount of records with geographical coordinates in representative data samples from well know biodiversity sites (such as GBIF and SpeciesLink).

Este trabalho apresenta uma nova proposta metodológica de previsão de enchentes: o Modelo de Alerta Hidrológico com Base Participativa (MAHP). O MAHP consiste em um modelo de previsão de enchentes em bacias urbanas que integra Informações Geográficas Voluntárias (VGI) e redes de sensores sem fio (WSN). A principal contribuição deste modelo é o uso de dados de fontes heterogêneas (sensores aliados a dados fornecidos por voluntários) com o objetivo de reduzir a incerteza na previsão de enchentes. O modelo MAHP foi dividido em módulos, cada um deles é responsável por uma atividade no processo de previsão de enchentes. Embora o modelo possua diversos módulos auxiliares, pode-se resumir o modelo MAHP em três módulos principais: aquisição de dados; previsão de precipitações e, por fim, o módulo responsável pela previsão das enchentes. Para o módulo de aquisição de dados foram desenvolvidas metodologias para uso de dados voluntários de nível da água e sensores medidores de nível foram instalados para a composição da rede de sensores sem fio em pontos estratégicos nos canais fluviais da cidade. No módulo de previsão da precipitação do modelo MAHP foram desenvolvidos dois softwares de previsão, sendo um modelo de previsão da precipitação conceitual e um empírico. Para o funcionamento do módulo responsável pela previsão das enchentes foi feita a modelagem da bacia urbana de São Carlos no modelo SWMM (Storm Water Management Model). As simulações chuva-vazão realizadas com a bacia modelada apresentaram ajustes satisfatórios quando comparadas com eventos de enchente reais. Como o uso de informações voluntárias na previsão de enchentes é um conceito bastante novo, outra importante contribuição do trabalho foi propor parâmetros espaço-temporais que influenciam na qualidade da previsão ocasionada pelo uso de dados VGI. Existem vários cenários e combinações de uso de informações voluntárias que podem influenciar na previsão de enchentes. Neste trabalho foi considerada apenas uma destas combinações. Devido à ausência de dados VGI reais em eventos de enchente recentes foram utilizados dados de nível medidos por sensores para simular dados voluntários. Foram levantadas diversas hipóteses para que a inserção de dados voluntários no modelo MAHP tenham maior influência na redução da incerteza na previsão de enchentes. / This work presents a new approach forflood forecasting: Hydrological Alert Model with Participatory Base (HAMPB). The HAMPB consists of a flood forecasting model applied to urban basins integrating Volunteered Geographic Information (VGI) and Wireless Sensor Networks (WSN). The main contribution of this model is the use of heterogeneous data sources (convencional sensors and volunteered data) aiming to reduce the uncertainty in the flood forecasting. The HAMPB model was divided in modules, which are responsible for the forecasting process activities. Although the model has multiple auxiliary modules, we can summarize the HAMPB model in three modules: data acquisition; rainfall forecasting and, finally, the module responsible for flood forecasting. Telemetric water level sensors were installed at strategic points in river channels of the city to create the WSN. In order to use the volunteered information, a methodology was proposed tdevelop the acquisition module. The rainfall forecasting module consists of two forecasting models: an empirical model and a conceptual model. The conceptual prediction model presented closest predictions of observed rainfall compared to the forecast of the empirical model. In order to apply the flood forecasting methodology, we modelled the urban basin of São Carlos using SWMM model. The rainfall-runoff simulations performed with the basin model showed satisfactory adjustments compared with actual flood events. Since the use of voluntary information on flood forecasting is a fairly new concept, another important contribution of this work was the proposition of spatiotemporal parameters that influence on the forecast caused by the use of VGI data. There are many scenarios and combinations which using volunteered information can be helpful in the flood forecasting. In this work we consider only one combination. Due to absence of real volunteered data, we use sensor data to simulate VGI data. Several hypotheses have been raised to the inclusion of volunteers in HAMPB data model to produce more relevant results than using traditional methods of forecasting.