Geovisualization Using HTML5 : a case study to improve animations of historical geographic data

Popular science Visualize geographic data Using HTML5 The Scanian Economic-Demographic Database (SEDD) has been assembled by the Centre for Economic Demography (CED), Lund University. It contains demographic and economic information of Scania from the 17th century until the present. The SEDD database has been integrated with geographic data, which are digitized from four independent historical maps. To help the users well understand these data, a web mapping application called SEDD Map has been developed and tested. The previous version of SEDD Map is constructed using Silverlight plugin. It cannot run on most popular portable devices. As Hypertext Markup Languages (HTML) continue to develop, a recent version, HTML5, was published in 2012. It aims to support the latest multimedia formats and reduce the need for plugins. So, to improve the compatibility of SEDD Map, this work using HTML5 to developed a new version of SEDD Map. Before we constructed the new version of SEDD Map, a set of web mapping applications and programs were evaluated. From this evaluation and comparison, we found that SEDD Map could be improved in many area, such as improving the animation of historical geographic data. Animation is a useful tool when presenting historical data. The geographic data in SEDD Map are taken from four independent historical maps. To visualize geographic data as an animation, we need to create a time sense sequential dataset. In this study, we used linear interpolation and the four historical maps as start years and end years to simulate 159 maps to visualize the geographic data as animations. From this study, we found that: The commonly used web mapping applications for investigating demographic data contain functions, such as interactive visualization, statistical graphics, basic map tools, animations, etc; HTML5 can replace (and improve) the used of Silverlight for web mapping; Animations can be generated (filling in what is missing is to improve the data sets).The Scanian Economic-Demographic Database (SEDD) has been assembled by the Centre for Economic Demography (CED), Lund University. It contains information about the demographic and economic conditions of people that have lived in 5 parishes in Scania from the 17th century until the present. The SEDD database has been integrated with geographic data, which are digitized from four independent historical maps. To visualize and analyze these data, a GIS based web mapping application called SEDD Map has been developed and tested. The previous version of SEDD Map is constructed using Silverlight. As a result, it only can be used on computers which have installed the Silverlight plugin. As Hypertext Markup Languages (HTML) continue to develop, a recent version, HTML5, was published in 2012. It aims to support the latest multimedia formats and reduce the need for plugins. In this study, we use HTML5, Cascading Style Sheets (CSS3), JavaScript and the ArcGIS API for JavaScript to create a new version of SEDD Map to visualize data stored in the SEDD database. Before we constructed the new version of SEDD Map, a set of web mapping applications and programs were evaluated by the requirements which were needed to create the new version of SEDD Map. From this evaluation and comparison, we found that SEDD Map could be improved in many area, such as improving the animation of historical geographic data. Animation is a useful tool when presenting historical data. The geographic data in SEDD Map are taken from four independent historical maps. To visualize geographic data as an animation, we need to create a time sense sequential dataset, which is done in a parallel project. In this study, we evaluate techniques for data animation. We used linear interpolation and the four historical maps as start years and end years to simulate 159 maps to visualize the geographic data as animations. The conclusions are as follows: 1) The commonly used web mapping applications for investigating demographic data contain functions, such as interactive visualization, statistical graphics, basic map tools, animations, etc. 2) HTML5 can replace (and improve) the used of Silverlight for web mapping. 3) Animations can be generated (filling in what is missing is to improve the data sets)

Finding the Essence in Geographic Statistics – Promoting Informed Decision Making

Abstract Official statistics have great potential to generate knowledge and serve as basis for decisions taken by many actors in society; however, the potential is grossly under-utilised because many people do not know about statistics, do not care about them and do not understand them. This paper highlights an innovative tool for exploring geographic statistics, which has been developed by the University of Linköping, Sweden. The paper demonstrates how the tool has been implemented in Denmark as a powerful enabler to different categories of users of statistics, who wish to understand the geographic dimension of societal phenomena and find the facts hidden in the data. The scope of the tool spans from leading edge regional researchers, through local and regional planners and news media, to the general public, e.g. citizens who want to understand what goes on in their community. Consequently, the tool allows for many different ways of presenting itself and the data, and it is applied to many different levels of geographical detail. It will be demonstrated how eXplorer can be used by an advanced user to explore geographic statistics, uncover hidden structures and relationships in the statistics; how an analyst can present her findings and stories to a broad audience; and how users “from the outside” can insert their own data in the tool, investigate new theories and communicate them to colleagues

Architektur eines Open Source BI Systems mit Geo-Erweiterung

In diesem Paper wird die Kombination von einer Open Source BI Lösung mit geo-bezogener Analyse und Visualisierung adressiert. Im Fokus stehen dabei die Architektur des Gesamt-systems sowie die Kommunikation der BI und Geo-Visualisierungsbezogenen Komponenten. Ziel ist es, eine Widget-basierte Architektur als Best-Practice Ansatz vorzustellen und aufzuzei-gen, welche Vorteile diese in der Nutzung bietet. Die Evaluierung des vorgestellten Ansatzes erfolgt in einem Anwendungsfall aus dem Gesundheitswesen

Geographic knowledge discovery from sparse GPS-data : Revealing spatio-temporal patterns of Amazonian river transports

A vast amount of spatio-temporal data has become available with the fast development of information technology and different monitoring systems over the last two decades. Position-aware devices are one of the most dominant sources for collecting movement data. Spatio-temporal information that is derived from the tracking devices enable to build movement patterns from the targets, and to calculate measurable motion parameters such as speed, change of speed or the direction of movement. This study utilized a specific pilot GPS-based monitoring system called Amazonian Riverboat Observation System (AROS) that was built to collect movement data of the local riverboats on the departments of Loreto and Ucayali in Peruvian Amazonia. AROS provides real-time GPS-data with coordinates and timestamp that indicate where and when the collaborating vessels are navigating. As an outcome of this thesis a specific analytical tool called Trajectory Reconstruction and Analysis Tool (TRAT) was developed. TRAT utilizes variety of geographic knowledge discovery methods to extract knowledge from movement data provided by AROS. Also spatio-temporal transportation characteristics in the study area were analyzed based on AROS data from the year 2012 and utilizing TRAT. This thesis focused on studying if there is seasonal and directional variation in transportation characteristics along the Amazonian rivers, and if river morphology affects the navigation. Also connection between water height of the rivers and travel speed of individual journeys was studied. Results of the thesis suggest that navigation along the rivers has seasonal and directional variation, and also the river morphology seems to affect the movement patterns of the vessels. On navigation route that was mostly meandering by river morphology, the downstream navigation was over 40% faster than upstream navigation during high water and intermediate, but during low water there was no difference between navigation directions. Seasonal variation was over 30% faster during high water compared to low water (on downstream direction). On upstream direction the navigation was fastest during low water but seasonal differences were considerably lower compared to downstream navigation. On navigation route that was mostly anastomosing by river morphology, the downstream navigation was approximately 20 % faster during the entire year. Results suggest that there is no seasonal difference in navigation characteristics along the larger and wider rivers, since the travel speeds were quite similar throughout the year. Fitting simple regression model between average travel speed of the journeys and water levels of the river revealed that there seems to be strong connection between travel speed and river height on the route along Ucayali river when travelled downstream (R2=0.73). On other cases that were studied, the results suggest that there is not connection between travel speed characteristics and river height. Comparing the results with earlier studies implied that the results of this thesis seemed to be fairly accurate. However, it is necessary to validate the results by doing cross-validations between data from different years observed with AROS. Transportation is in a key role when trying to find the factors affecting on development of a certain location. Thus transportation as means of accessibility has significant role in variety of contexts such as conversation, land use changes and deforestation. Results of this study could provide more accurate data for studies focusing on previously mentioned topics in the study area. Also utilization of TRAT in other contexts, such as studying global transportation patterns of professional vessels, could be possible by making few modifications to the tool.Informaatioteknologian ja erilaisten seurantajärjestelmien nopea kehitys viimeisten kahden vuosikymmenen aikana on mahdollistanut massiivisten spatio-temporaalisten tietovarantojen keräämisen. Paikannusteknologioilla varustetut laitteet ovat keskeisimpiä datalähteitä spatio-temporaalisen liikkumistiedon keräämiseen, ja tällainen data mahdollistaa erilaisten kohteiden (liikennevälineet, ihmiset jne.) liikkumisrakenteiden tutkimisen sekä erilaisten liikkumisparametrien kuten nopeuden, ja nopeuden sekä kulkusuunnan muutoksen laskemisen. Tässä tutkimuksessa hyödynnetään eristyistä pilotti-seurantajärjestelmää (AROS), joka on kehitetty keräämään jokilaivojen liikkumisdataa Loreton ja Ucayalin seuduilla Perun Amazoniassa. AROS mahdollistaa reaaliaikaisten laivojen sijantitietojen (koordinaatit) sekä aikatiedon (aikaleima) keräämisen. Tässä tutkimuksessa kehitettiin erityinen liikkumistiedonlouhintaan tarkoitettu analyysityökalu (TRAT), joka hyödyntää useita spatiaalisen tiedonlouhinnan menetelmiä informaation louhimiseksi AROS datasta. Tutkimuksessa tutkittiin, onko AROS datan perusteella jokinavigoinnissa nähtävissä vuodenaikaista vaihtelua vuoden 2012 aikana, ja vaikuttaako kulkusuunta sekä jokimorfologia navigointinopeuksiin. Tutkimuksessa tutkittiin myös, onko jokien vedenkorkeuksilla yhteyttä navigointinopeuksiin. Tutkimuksen tulokset osoittivat, että navigointi vaihtelee riippuen vuodenajasta sekä kulkusuunnasta, ja myös viitteitä jokimorfologian vaikutuksesta navigointiin oli paikoittain nähtävissä. Meanderoivilla jokiosuuksilla navigoiminen alavirtaan oli n. 40 % nopeampaa korkeanveden aikaan, mutta matalanveden aikaan eroa nopeuksissa ei ollut juuri nähtävissä. Vuodenaikaisvaihtelu oli selkeintä alavirtaan kuljettaessa, jolloin navigointi korkeanveden aikaan oli n. 30 % nopeampaa verrattuna matalanveden aikaan. Anastomoivilla jokiosuuksilla erot nopeuksissa eri kulkusuuntiin olivat vähäisemmät, ja navigointi oli keskimäärin 20 % nopeampaa alavirtaan (verrattuna ylävirtaan). Vuodenaikaisvaihtelua ei ollut juurikaan nähtävissä. Lineaarien regressiomalli jokikorkeuksien ja yksittäisten osareittien navigointinopeuksien välille osoitti, että yhteys oli selkeä (R2=0.73) osareiteillä, jotka kulkivat Ucayali-jokea alavirtaan. Muissa tutkituissa tapauksissa selkää yhteyttä ei löytynyt. Vertailemalla työn tuloksia aiempiin tutkimuksiin osoitti, että tulokset vaikuttavat olevan linjassa muiden tutkimusten tulosten kanssa. Työn tuloksia tulee jatkossa tosin vielä validoida vertailemalla vuoden 2012 tuloksia muiden vuosien tuloksiin AROS datan perusteella. Liikennejärjestelmät ovat keskeisiä tekijöitä, jotka vaikuttavat alueiden yleiseen kehitykseen. Yksi tapa kuvata liikennerakenteita on tarkastella paikkojen välistä saavutettavuutta, jolla on todettu olevan merkitystä lukuisiin eri yhteyksissä kuten maankäytön muutoksessa, deforestaatiossa sekä luonnonsuojelussa. Tämän tutkimuksen tulokset voivat tarjota tarkempaa dataa ja informaatiota liittyen edellämainittujen aiheiden tutkimiseen Perun Amazoniassa ja mahdolllisesti muillakin Amazonin alueilla. Kehitettyä analyysityökalua (TRAT) on myös mahdollista hyödyntää laajemmissa yhteyksissä, kuten globaalin laivaliikenteen tutkimuksessa, tekemällä pieniä muutoksia työkalun algoritmeihin

Spationomy

This open access book is based on "Spationomy – Spatial Exploration of Economic Data", an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works

Spationomy

This open access book is based on "Spationomy – Spatial Exploration of Economic Data", an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works

État des lieux des représentations dynamiques des temporalités des territoires

Le temps et ses caractéristiques ont toujours fait l’objet de grandes attentions pour comprendre les dynamiques des territoires. Aujourd’hui, que ce soit à cause des nouvelles capacités d’observation en temps réel, de l’accumulation des séries de données au cours du temps, ou à cause de la multiplication des rythmes, les temporalités à prendre en compte pour comprendre les dynamiques territoriales se multiplient et leurs imbrications se complexifient. Interroger les rythmes, les vitesses, les cycles de ces dynamiques, ou mettre en relation temporelle des phénomènes spatiaux tels que les évènements catastrophiques passés devient plus que jamais un enjeu pour comprendre et décider.Les jeux de méthodes mobilisables aujourd’hui pour représenter les temporalités des territoires sont en plein renouvellement, et imposent désormais bien souvent de franchir les fractures disciplinaires traditionnelles entre échelles, entre outils, entre formalismes. Les domaines d’applications potentiellement concernés, comme celui du développement durable des territoires, sont autant de domaines susceptibles de nourrir les questions associées à l’exploration des temporalités des territoires. Le projet "Représentation dynamique des temporalités des territoires" se veut un état des lieux de différents développements et solutions pour analyser et rendre compte des temporalités des territoires. Cet état des lieux est à entrées multiples, interrogeant à la fois des choix amont (modélisation) et des choix proprement liés à la question de la représentation. Le projet débouche sur un ensemble de résultats dont certains sont mis en ligne sur le site: http://www.map.cnrs.fr/jyb/puca/- Une grille de lecture de la collection d'applications analysée (voir onglet "47 applications"), grille où sont combinés des indicateurs généraux sur par exmeple le type de service rendu ou le type de dynamique spatiale analysée, et des indicateurs plus spécifiques au traitement des dimensions spatiales et temporelles. Cette grille est mise en place sur 47 applications identifiées et analysées,- Des visualisations récapitulatives conçues comme outils d'analyse comparative de la collection,- Une bibliographie structurée en relation avec la grille de lecture

A Data-driven Methodology Towards Mobility- and Traffic-related Big Spatiotemporal Data Frameworks

Human population is increasing at unprecedented rates, particularly in urban areas. This increase, along with the rise of a more economically empowered middle class, brings new and complex challenges to the mobility of people within urban areas. To tackle such challenges, transportation and mobility authorities and operators are trying to adopt innovative Big Data-driven Mobility- and Traffic-related solutions. Such solutions will help decision-making processes that aim to ease the load on an already overloaded transport infrastructure. The information collected from day-to-day mobility and traffic can help to mitigate some of such mobility challenges in urban areas. Road infrastructure and traffic management operators (RITMOs) face several limitations to effectively extract value from the exponentially growing volumes of mobility- and traffic-related Big Spatiotemporal Data (MobiTrafficBD) that are being acquired and gathered. Research about the topics of Big Data, Spatiotemporal Data and specially MobiTrafficBD is scattered, and existing literature does not offer a concrete, common methodological approach to setup, configure, deploy and use a complete Big Data-based framework to manage the lifecycle of mobility-related spatiotemporal data, mainly focused on geo-referenced time series (GRTS) and spatiotemporal events (ST Events), extract value from it and support decision-making processes of RITMOs. This doctoral thesis proposes a data-driven, prescriptive methodological approach towards the design, development and deployment of MobiTrafficBD Frameworks focused on GRTS and ST Events. Besides a thorough literature review on Spatiotemporal Data, Big Data and the merging of these two fields through MobiTraffiBD, the methodological approach comprises a set of general characteristics, technical requirements, logical components, data flows and technological infrastructure models, as well as guidelines and best practices that aim to guide researchers, practitioners and stakeholders, such as RITMOs, throughout the design, development and deployment phases of any MobiTrafficBD Framework. This work is intended to be a supporting methodological guide, based on widely used Reference Architectures and guidelines for Big Data, but enriched with inherent characteristics and concerns brought about by Big Spatiotemporal Data, such as in the case of GRTS and ST Events. The proposed methodology was evaluated and demonstrated in various real-world use cases that deployed MobiTrafficBD-based Data Management, Processing, Analytics and Visualisation methods, tools and technologies, under the umbrella of several research projects funded by the European Commission and the Portuguese Government.A população humana cresce a um ritmo sem precedentes, particularmente nas áreas urbanas. Este aumento, aliado ao robustecimento de uma classe média com maior poder económico, introduzem novos e complexos desafios na mobilidade de pessoas em áreas urbanas. Para abordar estes desafios, autoridades e operadores de transportes e mobilidade estão a adotar soluções inovadoras no domínio dos sistemas de Dados em Larga Escala nos domínios da Mobilidade e Tráfego. Estas soluções irão apoiar os processos de decisão com o intuito de libertar uma infraestrutura de estradas e transportes já sobrecarregada. A informação colecionada da mobilidade diária e da utilização da infraestrutura de estradas pode ajudar na mitigação de alguns dos desafios da mobilidade urbana. Os operadores de gestão de trânsito e de infraestruturas de estradas (em inglês, road infrastructure and traffic management operators — RITMOs) estão limitados no que toca a extrair valor de um sempre crescente volume de Dados Espaciotemporais em Larga Escala no domínio da Mobilidade e Tráfego (em inglês, Mobility- and Traffic-related Big Spatiotemporal Data —MobiTrafficBD) que estão a ser colecionados e recolhidos. Os trabalhos de investigação sobre os tópicos de Big Data, Dados Espaciotemporais e, especialmente, de MobiTrafficBD, estão dispersos, e a literatura existente não oferece uma metodologia comum e concreta para preparar, configurar, implementar e usar uma plataforma (framework) baseada em tecnologias Big Data para gerir o ciclo de vida de dados espaciotemporais em larga escala, com ênfase nas série temporais georreferenciadas (em inglês, geo-referenced time series — GRTS) e eventos espacio- temporais (em inglês, spatiotemporal events — ST Events), extrair valor destes dados e apoiar os RITMOs nos seus processos de decisão. Esta dissertação doutoral propõe uma metodologia prescritiva orientada a dados, para o design, desenvolvimento e implementação de plataformas de MobiTrafficBD, focadas em GRTS e ST Events. Além de uma revisão de literatura completa nas áreas de Dados Espaciotemporais, Big Data e na junção destas áreas através do conceito de MobiTrafficBD, a metodologia proposta contem um conjunto de características gerais, requisitos técnicos, componentes lógicos, fluxos de dados e modelos de infraestrutura tecnológica, bem como diretrizes e boas práticas para investigadores, profissionais e outras partes interessadas, como RITMOs, com o objetivo de guiá-los pelas fases de design, desenvolvimento e implementação de qualquer pla- taforma MobiTrafficBD. Este trabalho deve ser visto como um guia metodológico de suporte, baseado em Arqui- teturas de Referência e diretrizes amplamente utilizadas, mas enriquecido com as característi- cas e assuntos implícitos relacionados com Dados Espaciotemporais em Larga Escala, como no caso de GRTS e ST Events. A metodologia proposta foi avaliada e demonstrada em vários cenários reais no âmbito de projetos de investigação financiados pela Comissão Europeia e pelo Governo português, nos quais foram implementados métodos, ferramentas e tecnologias nas áreas de Gestão de Dados, Processamento de Dados e Ciência e Visualização de Dados em plataformas MobiTrafficB

Visualization for exploratory analysis of spatio-temporal data

Analysis of spatio-temporal data has become critical with the emerge of ubiquitous location sensor technologies and applications keeping track of such data. Especially with the widespread availability of low cost GPS devices, it is possible to record data about the location of people and objects at a large scale. Data visualization plays a key role in the successful analysis of these kind of data. Due to the complex nature of this analysis process, current approaches and analytical tools fail to help spatio-temporal thinking and they are not effective when solving large range of problems. In this work, we propose an interactive visualization tool to support human analyst understand user behaviors by analyzing location patterns and anomalies in massive collections of spatio-temporal data. The tool that we developed within this work combines a geovisualization framework with 3D visualizations and histograms. Tool's effectiveness in exploratory analysis is tested by trend analysis and anomaly detection in a real mobile service dataset with almost 1.5 million rows