The effect of spatial distance on the discriminability of colors in maps

ABSTRACT

The spatial distance (gap) between map symbols can have a great impact on their discriminability, however, there is little empirical evidence to establish spatial and attribute thresholds. In this paper, we examine the effect of the spatial gap in discriminability of color hue and value, that is, we conducted an online study to obtain performance metrics; then an eye-tracking study to understand participants’ strategies and cognitive processes. Participants completed two experimental tasks (compare two areas and decide if their color is the same; and compare three areas and rank them from the lightest to the darkest). The color distances and the spatial distances were strictly controlled for the compared areas. Our analyses confirmed that, overall, increasing the gap between colors has a consistent negative impact on the ability to differentiate them with both sequential and qualitative schemes. Furthermore, we observed that sequential schemes require larger color distances than qualitative schemes for discriminability. Finally, our results suggested that for qualitative colors, the largest tested color distance ?E₀₀ = 10 yields considerably higher levels of accuracy in color discrimination (even when the spatial gap between the two colors is large), thus we recommend ?E₀₀ = 10 to practicing cartographers and other information visualization designers.     

Blending Aggregation and Selection: Adapting Parallel Coordinates for the Visualization of Large Datasets

Abstract

Many of the traditional data visualization techniques, which proved to be supportive for exploratory analysis of datasets of moderate sizes, fail to fulfil their function when applied to large datasets. There are two approaches to coping with large amounts of data: data selection, when only a portion of data is displayed, and data aggregation, i.e. grouping data items and considering the groups instead of the original data. None of these approaches alone suits the needs of exploratory data analysis, which requires consideration of data on all levels: overall (considering a dataset as a whole), intermediate (viewing and comparing collective characteristics of arbitrary data subsets, or classes), and elementary (accessing individual data items). Therefore, it is necessary to combine these approaches, i.e. build a tool showing the whole set and arbitrarily defined subsets (object classes) in an aggregated way and superimposing this with a representation of arbitrarily selected individual data items.

We have achieved such a combination of approaches by modifying the technique of parallel coordinate plot. These modifications are described and analysed in the paper.     

3D Visualization for the Analysis of Forest Cover Change

Abstract

Visualization techniques have been developed to recreate natural landscapes, but little has been done to investigate their potential for illustrating land cover change using spatio‐temporal data. In this work, remote sensing, geographic information systems (GIS) and visualization techniques were applied to generate realistic computer visualizations depicting the dynamic nature of forested environments. High resolution digital imagery and aerial photography were classified using object‐oriented methods. The resulting classifications, along with preexisting land cover datasets, were used to drive the correct placement of vegetation in the visualized landscape, providing an accurate representation of reality at various points in time. 3D Nature's Visual Nature Studio was used to construct a variety of realistic images and animations depicting forest cover change in two distinct ecological settings. Visualizations from Yellowstone National Park focused on the dramatic impact of the 1988 fire upon the lodgepole pine forest. For a study area in Kansas, visualization techniques were used to explore the continuous human‐land interactions impacting the eastern deciduous forest and tallgrass prairie ecotone between 1941 and 2002. The resulting products demonstrate the flexibility and effectiveness of visualizations for representing spatio‐temporal patterns such as changing forest cover. These geographic visualizations allow users to communicate findings and explore new hypotheses in a clear, concise and effective manner.     

Stakeholder analysis of the governance framework of a national SDI dataset – whose needs are met in the buildings and address register of the Netherlands?

ABSTRACT

National spatial data infrastructures are key to achieving the Digital Earth vision. In many cases, national datasets are integrated from local datasets created and maintained by municipalities. Examples are address, building and topographic information. Integration of local datasets may result in a dataset satisfying the needs of users of national datasets, but is it productive for those who create and maintain the data? This article presents a stakeholder analysis of the Basisregistratie Adressen en Gebouwen (BAG), a collection of base information about addresses and buildings in the Netherlands. The information is captured and maintained by municipalities and integrated into a national base register by Kadaster, the Cadastre, Land Registry and Mapping Agency of the Netherlands. The stakeholder analysis identifies organisations involved in the BAG governance framework, describes their interests, rights, ownerships and responsibilities in the BAG, and maps the relationships between them. Analysis results indicate that Kadaster and the municipalities have the highest relative importance in the governance framework of the BAG. The study reveals challenges of setting up a governance framework that maintains the delicate balance between the interests of all stakeholders. The results provide guidance for SDI role players setting up governance frameworks for national or global datasets.     

Effectiveness of Cartogram for the Representation of Spatial Data

Abstract

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Cartogram is a technique for visualisation of the geographical distribution of spatial data. It has two main types, i.e. distance cartogram and area cartogram. Area cartogram is a transformed map in which areas are resized in proportion to an attribute value. A number of techniques have been developed for the generation of area cartograms. Some researchers consider cartogram as a very effective technique for visualisation of spatial data, while others doubt about the effectiveness because of the possible distortion in shape and/or disconnectivity in topology. This study aims to evaluate the effectiveness of area cartogram for visualizing spatial data. In this study, two comparative experiments have been conducted. One is the comparison between thematic maps and cartograms, and the other is the comparison among different types of area cartogram. Two sets of data with different characteristics are used, i.e. 2005 China population data and 1996 US election data. Results show that cartogram is more effective in the representation of the 1996 US election data which provides a qualitative result (i.e. in binary form or nominal data), but thematic map is far more effective in the representation of 2005 China population data which provides a quantitative result (in classes or ordinal data). It is also found that among different types of area cartogram, pseudo-cartogram is the most preferred technique and Dorling cartogram is the least preferred one.     

Augmented virtual environment: fusion of real-time video and 3D models in the digital earth system

ABSTRACT

An Augmented virtual environment (AVE) is concerned with the fusion of real-time video with 3D models or scenes so as to augment the virtual environment. In this paper, a new approach to establish an AVE with a wide field of view is proposed, including real-time video projection, multiple video texture fusion and 3D visualization of moving objects. A new diagonally weighted algorithm is proposed to smooth the apparent gaps within the overlapping area between the two adjacent videos. A visualization method for the location and trajectory of a moving virtual object is proposed to display the moving object and its trajectory in the 3D virtual environment. The experimental results showed that the proposed set of algorithms are able to fuse multiple real-time videos with 3D models efficiently, and the experiment runs a 3D scene containing two million triangles and six real-time videos at around 55 frames per second on a laptop with 1GB of graphics card memory. In addition, a realistic AVE with a wide field of view was created based on the Digital Earth Science Platform by fusing three videos with a complex indoor virtual scene, visualizing a moving object and drawing its trajectory in the real time.     

Transfer function-based 2D/3D interactive spatiotemporal visualizations of mesoscale eddies

ABSTRACT

In this paper, we present a transfer function-based approach to developing an interactive visualization algorithm for ocean mesoscale eddies. Spatiotemporal coherence and viewport coherence are achieved. Evenly spaced streamlines are only integrated for visible portions of the datasets that maintain a relatively stable visual pattern resolution. The interactive transfer function is introduced to extract 2D and 3D eddy features, such as the Okubo-Weiss parameter, from background ocean currents, and a highly efficient GPU-based framework with an output-sensitive performance is utilized. Using the high-resolution 2D/3D ocean current datasets Maps of Sea Level Anomalies (MSLA) and Hybrid Coordinate Ocean Model (HYCOM), the feasibility and efficiency of our framework are demonstrated.     

Sonifying data uncertainty with sound dimensions

ABSTRACT

The communication of data uncertainty is a crucial problem in data science, information visualization, and geographic information science (GIScience). Effective ways to communicate the uncertainty of data enables data consumers to interpret the data as intended by the producer, reducing the possibilities of misinterpretation. In this article, we report on an empirical investigation of how sound can be used to convey information about data uncertainty in an intuitive way. To answer the research question How intuitive are sound dimensions to communicate uncertainty? we carry out a cognitive experiment, where participants were asked to interpret the certainty/uncertainty level in two sounds A and B (N = 33). We produce sound stimuli by varying sound dimensions, including loudness, duration, location, pitch, register, attack, decay, rate of change, noise, timbre, clarity, order, and harmony. In the stimuli, both synthetic and natural sounds are used to allow comparison. The experiment results identify three sound dimensions (loudness, order, and clarity) as significantly more intuitive to communicate uncertainty, providing guidelines for sonification and information visualization practitioners.     

FunnelCloud: a cloud-based system for exploring tornado events

ABSTRACT

Recent research has shown an increase in the number of extreme tornado outbreaks per year. The characterization of the spatio-temporal pattern of tornado events is therefore a critical task in the analysis of meteorological data. Currently, there are a large number of available meteorological datasets that can be used for such analysis. However, much of these data are distributed across multiple websites and are not accessible in a central location. This poses a significant challenge for a scientist who is interested in exploring meteorological patterns associated with tornado events. This paper presents a novel system which uses cloud-based technology for integrating, storing, exploring, analyzing, and visualizing meteorological data associated with tornado outbreaks. The system employs a novel NoSQL database schema and web services architecture for data integration and provides a user friendly interface that allows scientists to explore the spatio-temporal pattern of tornado events. Furthermore, scientists can use this interface to analyze the relationship between different meteorological variables and properties of tornado outbreaks using a number of spatio-temporal statistical and data mining methods. The efficacy of the system is demonstrated on a use case centered on the analysis of climatic indicators of large spatio-temporally clustered tornado outbreaks.     

A perception-based color recommendation algorithm for hierarchical regions

The visualization of hierarchical and nested spatial regions remains a challenge to cartographers. Despite progress in computer algorithms for visualizing general hierarchical data, mapping spatial hierarchical regions, especially with static, noninteractive means, still requires considerable manual efforts. This paper proposes a two-step algorithm that can automatically recommend perception-based colors and help reveal the hierarchical structure embedded in nested regions. It first systematically sorts regions according to their contiguity and containment relations at multiple hierarchical levels. Then, perception-based colors are generated using the order of regions with the goal of maximizing differentiability between top-level regions while retaining the perceived uniformity of the bottom-level regions. With the coloring scheme recommended by this algorithm, the metric color differences among regions mathematically reflect their hierarchical positions and spatial relations. The resultant colors, therefore, can potentially help map-readers perceive the spatially constrained hierarchy structure built in nested regions.     

Interface Design for Geographic Visualization: Tools for Representing Reliability

Digital "softcopy" maps are becoming the norm—replacing static paper maps in applications from wayfinding to scientific research. As a result, the design of interface tools that allow users to manipulate map parameters effectively and efficiently is likely to become as fundamental to cartography as the design of maps themselves. This article presents some principles for the design of interfaces to geo-referenced data. These principles are summarized in a hierarchical approach to interface design with conceptual, operational, and implementational levels. This hierarchical approach leads designers from questions about the goals of the system and the users of that system to the creation of tools to accomplish those goals and interface controls that allow effective interaction with the tools. The article goes on to describe the application of these principles to a prototype geographic visualization system designed for exploration of spatial data sets and visualization of reliability of both data and data abstractions associated with environmental change. The prototype involves a synthesis of concepts and methods derived from cartography, scientific visualization, and exploratory data analysis into a system for exploratory spatial data analysis and spatial decision support.     

Development and comparison of aerial photograph aided visualization pipelines for LiDAR datasets

Light Detection and Ranging (LiDAR) technology generates dense and precise three-dimensional datasets in the form of point clouds. Conventional methods of mapping with airborne LiDAR datasets deal with the process of classification or feature specific segmentation. These processes have been observed to be time-consuming and unfit to handle in scenarios where topographic information is required in a small amount of time. Thus there is a requirement of developing methods which process the data and reconstruct the scene in a small amount of time. This paper presents several pipelines for visualizing LiDAR datasets without going through classification and compares them using statistical methods to rank these processes in the order of depth and feature perception. To make the comparison more meaningful, a manually classified and computer-aided design (CAD) reconstructed dataset is also included in the list of compared methods. Results show that a heuristic-based method, previously developed by the authors perform almost equivalent to the manually classified and reconstructed dataset, for the purposes of visualization. This paper makes some distinct contributions as: (1) gives a heuristics-based visualization pipeline for LiDAR datasets, and (2) presents an experimental design supported by statistical analysis to compare different pipelines.     

Potential of Landsat-8 and Sentinel-2A composite for land use land cover analysis

Abstract

This study proposes the development of a multi-sensor, multi-spectral composite from Landsat-8 and Sentinel-2A imagery referred to as ‘LSC’ for land use land cover (LULC) characterisation and compared with respect to the hyperspectral imagery of the EO1: Hyperion sensor. A three-stage evaluation was implemented based on the similarity observed in the spectral response, supervised classification results and endmember abundance information obtained using linear spectral unmixing. The study was conducted for two areas located around Dhundi and Rohtak in Himachal Pradesh and Haryana, respectively. According to the analysis of the spectral reflectance curves, the spectral response of the LSC is capable of identifying major LULC classes. The kappa accuracy of 0.85 and 0.66 was observed for the classification results from LSC and Hyperion data for Dhundi and Rohtak datasets, respectively. The coefficient of determination was found to be above 0.9 for the LULC classes in both the datasets as compared to Hyperion, indicating a good agreement. Thus, these three-stage results indicated the significant potential of a composite derived from freely available multi-sensor multi-spectral imagery as an alternative to hyperspectral imagery for LULC studies.     

Testing Popular Visualization Techniques for Representing Model Uncertainty

Many land allocation issues, such as land-use planning, require input from extensive spatial databases and involve complex decision-making. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of land allocation alternatives. In this paper we analyze techniques for visualizing uncertainty of an urban growth model called SLEUTH, which is designed to aid decision-makers in the field of urban planning and fits into the computational framework of an SDSS. Two simple visualization techniques for portraying uncertainty—static comparison and toggling—are applied to SLEUTH results and rendered with different background information and color schemes. In order to evaluate the effectiveness of the two visualization techniques, a web-based survey was developed showing the visualizations along with questions about the usefulness of the two techniques. The web survey proved to be quickly accessible and easy to understand by the participants. Participants in the survey were mainly recruited among planners and decision-makers. They acknowledged the usefulness of portraying uncertainty for decision-making purposes. They slightly favored the static comparison technique over toggling. Both visualization techniques were applied to an urban growth case study for the greater Santa Barbara area in California, USA.     

An ontological system based on MODIS images to assess ecosystem functioning of Natura 2000 habitats: A case study for Quercus pyrenaica forests

The implementation of the Natura 2000 network requires methods to assess the conservation status of habitats. This paper shows a methodological approach that combines the use of (satellite) Earth observation with ontologies to monitor Natura 2000 habitats and assess their functioning. We have created an ontological system called Savia that can describe both the ecosystem functioning and the behaviour of abiotic factors in a Natura 2000 habitat. This system is able to automatically download images from MODIS products, create indicators and compute temporal trends for them. We have developed an ontology that takes into account the different concepts and relations about indicators and temporal trends, and the spatio-temporal components of the datasets. All the information generated from datasets and MODIS images, is stored into a knowledge base according to the ontology. Users can formulate complex questions using a SPARQL end-point. This system has been tested and validated in a case study that uses Quercus pyrenaica Willd. forests as a target habitat in Sierra Nevada (Spain), a Natura 2000 site. We assess ecosystem functioning using NDVI. The selected abiotic factor is snow cover. Savia provides useful data regarding these two variables and reflects relationships between them.     

A prototype web-based analysis platform for drought monitoring and early warning

ABSTRACT

It has long been recognized that an effective drought monitoring and early warning system, which provides functions for real-time condition monitoring and prediction, risk assessment, information dissemination and response recommendation, is very important for the preparedness for and mitigation of drought impacts. In this article, we review the currently existing drought monitor and early warning systems, discuss applicable remote sensing datasets and drought indicators and present the development of a web-based quasi-real-time Global Drought Monitoring & Analysis Platform (Web-GDMAP). The Web-GDMAP is built upon a series of indicators derived from multi-source satellite remote sensing data and various other sources of data. From a technical perspective, the Web-GDMAP system includes a series of components from data storage, model implementation and distribution, to client-side visualization and user intuitive interaction. From a theoretical perspective, the Web-GDMAP system integrates multi-indicators on different aspects of drought, including anomalies in precipitation, anomalies in land surface thermal and vegetation conditions, water deficit of soil and plants, etc. Several case studies on applying the developed Web-GDMAP in the Asian region are demonstrated. Further improvements and perspectives are discussed.     

Epistemology of Geopolitical Atlases from the 1980s to the Early 2000s

Abstract

Since the early 1980s, we have seen a new influx of numerous geopolitical atlases. They have been produced to meet society's implicit need to fix the boundaries of international issues and the relationships of force between the various powers. These atlases clearly express established ideologies and allow us to determine various trends of thought; messages which the authors wish us to take on board by studying cartographic themes. This is the approach we will be taking in this article.

In this paper, we aim to show the epistemological development of geopolitical atlases. The first part of the article gives the general outline of the epistemological development of geopolitical atlases, in which two main periods stand out. The first corresponds with the 1980s, which can be described as a realist decade. The state was a geopolitical player that could not be overlooked within a bipolar world; maps showing conflicts between the two major powers and thematic maps showing an ideological clash between them are typical of the period. The second period, corresponding with the 1990s, begins with the fall of the regimes in the Soviet bloc. This period can be described as having a neo-realist approach, where the threat from the East had moved to terrorism and drug trafficking. The atlases follow the geopolitical development of the world and describe international structural changes. In conclusion, the paper will return to the important educational and informative role of atlases and their effects on the ideas they are able to disseminate amongst the population.     

China Digital Ocean Prototype System

Abstract

Digital Ocean is a new research domain of Digital Earth. Because of the spatio-temporal, three-dimensional (3D) and intrinsically dynamic nature of ocean data, it is more difficult to make a breakthrough in this domain. The construction of the China Digital Ocean Prototype System (CDOPS) pushes Digital Ocean a step forward from its operation as a mere concept to its achievement as a realistic system. In this paper, the technical framework of the CDOPS is discussed, including its data, function, and application layers. Then, two key technologies are studied in detail that will enable the construction of the 3D ocean environment and the visualization of the ocean model output data. Practical demonstrations show that the CDOPS provides a technical reference for the development of Digital Ocean. This paper is based on an ongoing research project of the development of CDOPS that aims at the facilitation, integration, sharing, accessing, visualization, and use of the ocean data and model computing data from the Digital Earth perspective.