Interactive maps: What we know and what we need to know

This article provides a review of the current state of science regarding cartographic interaction a complement to the traditional focus within cartography on cartographic representation. Cartographic interaction is defined as the dialog between a human and map mediated through a computing device and is essential to the research into interactive cartography geovisualization and geovisual analytics. The review is structured around six fundamental questions facing a science of cartographic interaction: (1) what is cartographic interaction (e.g. digital versus analog interactions interaction versus interfaces stages of interaction interactive maps versus mapping systems versus map mash-ups); (2) why provide cartographic interaction (e.g. visual thinking geographic insight the stages of science the cartographic problematic); (3) when should cartographic interaction be provided (e.g. static versus interactive maps interface complexity the productivity paradox flexibility versus constraint work versus enabling interactions); (4) who should be provided with cartographic interaction (e.g. user-centered design user ability expertise and motivation adaptive cartography and geocollaboration); (5) where should cartographic interaction be provided (e.g. input capabilities bandwidth and processing power display capabilities mobile mapping and location-based services); and (6) how should cartographic interaction be provided (e.g. interaction primitives objective-based versus operator-based versus operand-based taxonomies interface styles interface design)? The article concludes with a summary of research questions facing cartographic interaction and offers an outlook for cartography as a field of study moving forward

Using Geovisual Analytics to investigate the performance of Geographically Weighted Discriminant Analysis

Geographically Weighted Discriminant Analysis (GWDA) is a method for prediction and analysis of categorical spatial data. It is an extension of Linear Discriminant Analysis (LDA) that allows the relationship between the predictor variables and the categories to vary spatially. This is also referred to spatial non-stationarity. If spatial non-stationarity exists, GWDA should model the relationship between the categories and predictor variables more accurately, thus resulting in a lower classification uncertainty and ultimately a higher classification accuracy. The GWDA output also requires interpretation to understand which variables are important in driving the classification in different geographical regions. This research uses interactive visualisations from the field of geovisual analytics to investigate the performance of GWDA in terms of classification accuracy, classification uncertainty and spatial non-stationarity. The methodology is demonstrated in a case study that uses GWDA to examine the relationship between county level voting patterns in the 2004 US presidential election and five socio-economic indicators. This research builds on existing techniques to interpret the GWDA output and provides additional insight into the processes driving the classification. It also demonstrates a practical application of geovisual analytic tools

A Geovisual Analytic Approach to Understanding Geo-Social Relationships in the International Trade Network

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly ‘balkanized’ (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above

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)

From SpaceStat to CyberGIS: Twenty Years of Spatial Data Analysis Software

This essay assesses the evolution of the way in which spatial data analytical methods have been incorporated into software tools over the past two decades. It is part retrospective and prospective, going beyond a historical review to outline some ideas about important factors that drove the software development, such as methodological advances, the open source movement and the advent of the internet and cyberinfrastructure. The review highlights activities carried out by the author and his collaborators and uses SpaceStat, GeoDa, PySAL and recent spatial analytical web services developed at the ASU GeoDa Center as illustrative examples. It outlines a vision for a spatial econometrics workbench as an example of the incorporation of spatial analytical functionality in a cyberGIS.

DIVAD: A Dynamic and Interactive Visual Analytical Dashboard for Exploring and Analyzing Transport Data

The advances in location-based data collection technologies such as GPS, RFID etc. and the rapid reduction of their costs provide us with a huge and continuously increasing amount of data about movement of vehicles, people and goods in an urban area. This explosive growth of geospatially-referenced data has far outpaced the planner-s ability to utilize and transform the data into insightful information thus creating an adverse impact on the return on the investment made to collect and manage this data. Addressing this pressing need, we designed and developed DIVAD, a dynamic and interactive visual analytics dashboard to allow city planners to explore and analyze city-s transportation data to gain valuable insights about city-s traffic flow and transportation requirements. We demonstrate the potential of DIVAD through the use of interactive choropleth and hexagon binning maps to explore and analyze large taxi-transportation data of Singapore for different geographic and time zones

GeoCAM: A geovisual analytics workspace to contextualize and interpret statements about movement

This article focuses on integrating computational and visual methods in a system that supports analysts to identify extract map and relate linguistic accounts of movement. We address two objectives: (1) build the conceptual theoretical and empirical framework needed to represent and interpret human-generated directions; and (2) design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled computational methods to identify documents containing movement statements and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract interpret and map geographic movement references in context. Additionally analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface an analyst can explore the results provide feedback to improve those results pose queries against a database of route directions and interactively represent the route on a map

Using treemaps for variable selection in spatio-temporal visualisation

We demonstrate and reflect upon the use of enhanced treemaps that incorporate spatial and temporal ordering for exploring a large multivariate spatio-temporal data set. The resulting data-dense views summarise and simultaneously present hundreds of space-, time-, and variable-constrained subsets of a large multivariate data set in a structure that facilitates their meaningful comparison and supports visual analysis. Interactive techniques allow localised patterns to be explored and subsets of interest selected and compared with the spatial aggregate. Spatial variation is considered through interactive raster maps and high-resolution local road maps. The techniques are developed in the context of 42.2 million records of vehicular activity in a 98 km(2) area of central London and informally evaluated through a design used in the exploratory visualisation of this data set. The main advantages of our technique are the means to simultaneously display hundreds of summaries of the data and to interactively browse hundreds of variable combinations with ordering and symbolism that are consistent and appropriate for space- and time- based variables. These capabilities are difficult to achieve in the case of spatio-temporal data with categorical attributes using existing geovisualisation methods. We acknowledge limitations in the treemap representation but enhance the cognitive plausibility of this popular layout through our two-dimensional ordering algorithm and interactions. Patterns that are expected (e.g. more traffic in central London), interesting (e.g. the spatial and temporal distribution of particular vehicle types) and anomalous (e.g. low speeds on particular road sections) are detected at various scales and locations using the approach. In many cases, anomalies identify biases that may have implications for future use of the data set for analyses and applications. Ordered treemaps appear to have potential as interactive interfaces for variable selection in spatio-temporal visualisation. Information Visualization (2008) 7, 210-224. doi: 10.1057/palgrave.ivs.950018