Special Issue "Geovisualization and Analysis of Dynamic Phenomena"

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 March 2013)

Special Issue Editors

Guest Editor
Dr. Marguerite Madden (Website)

Center for Remote Sensing and Mapping Science (CRMS), Department of Geography, University of Georgia, Athens, GA 30602, USA
Interests: GIScience; including remote sensing; geographic information systems (GIS); spatio-temporal analysis; geovisualization and geographic object-based image analysis, as applied to landscapescale biological/physical processes and human-impacts on the environment
Guest Editor
Dr. Chiao-Ying (Jill) Chou

Center for Remote Sensing and Mapping Science (CRMS), Department of Geography, University of Georgia, Athens, GA 30602, USA
Interests: three-dimensional landscape visualization; geographic information system (GIS) modeling and programming; landscape disturbance (i.e., forest fire and beetle infestation) monitory using GIS and remote sensing images and natural resources inventory
Guest Editor
Dr. Andrea Presotto

Center for Remote Sensing and Mapping Science (CRMS), Department of Geography, University of Georgia, Athens, GA 30602, USA
Interests: geovisualization and geoscience in spatial cognition studies in human and non-human animals; Geotechnologies, such as geographic information system (GIS) and remote sensing; to explore animal movements and to contribute with natural landscape conservation

Special Issue Information

Dear Colleagues,

Geovisualization allows a wide range of users from lay-public to GIS specialists to explore, synthesize, present, integrate, and analyze their geospatial data with different degrees of interaction from low (passive) to high (active). Nowadays, the techniques of geovisualization in 3D perspective views, 4D animations, virtual objects and environments can aid natural and cultural resource managers in the decision making process to communicate decisions/plans to the public, as well as aid in scientific analysis. In addition, the use of remotely sensed and derived data (e.g., terrestrial, airborne and satellite digital imagery, radar, and LiDAR) provides more possibilities, while using large volume data sources to efficiently generate geovisualizations also present challenges.

This special issue focuses on:

  • geovisualization and analysis of dynamic phenomena (e.g., movement data and change detection)
  • animation and real-time interactive 2D, 3D, and 4D geovisualizations
  • reliability and uncertainty of spatio-temporal data
  • photo-realism and augmented reality in geovisualization
  • applications of geovisualization such as in landscape design, decision making, disaster response analysis of social interactions and education
  • technical improvements of geovisualization using various mobile devices (e.g., smart phones, PDAs, tablets and GPS)
  • gaming technology for simulation and geospatial education (geo-gaming)

Prof. Dr. Marguerite Madden
Dr. Chiao-Ying (Jill) Chou
Guest Editors

Dr. Andrea Presotto
Guest Editor Assistant

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 900 CHF (Swiss Francs).

Keywords

  • cognitive geovisualization
  • cartographic techniques for visual analysis
  • geospatial visual analytics
  • web-based virtual globes and digital cities
  • interactive mapping
  • challenges of large volume data sets (e.g., Big Data)
  • geospatial intelligence and actionable information
  • web-based geovisualization of social interactions
  • exploratory analysis [= geovisualization for data mining]
  • geovisualization of modeling results

Published Papers (4 papers)

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Research

Open AccessArticle Visual Analysis for Nowcasting of Multidimensional Lightning Data
ISPRS Int. J. Geo-Inf. 2013, 2(3), 817-836; doi:10.3390/ijgi2030817
Received: 17 June 2013 / Revised: 22 July 2013 / Accepted: 14 August 2013 / Published: 26 August 2013
PDF Full-text (1519 KB) | HTML Full-text | XML Full-text
Abstract
Globally, most weather-related damages are caused by thunderstorms. Besides floods, strong wind, and hail, one of the major thunderstorm ground effects is lightning. Therefore, lightning investigations, including detection, cluster identification, tracking, and nowcasting are essential. To enable reliable decisions, current and predicted [...] Read more.
Globally, most weather-related damages are caused by thunderstorms. Besides floods, strong wind, and hail, one of the major thunderstorm ground effects is lightning. Therefore, lightning investigations, including detection, cluster identification, tracking, and nowcasting are essential. To enable reliable decisions, current and predicted lightning cluster- and track features as well as analysis results have to be represented in the most appropriate way. Our paper introduces a framework which includes identification, tracking, nowcasting, and in particular visualization and statistical analysis of dynamic lightning data in three-dimensional space. The paper is specifically focused on enabling users to conduct the visual analysis of lightning data for the purpose of identification and interpretation of spatial-temporal patterns embedded in lightning data, and their dynamics. A graphic user interface (GUI) is developed, wherein lightning tracks and predicted lightning clusters, including their prediction certainty, can be investigated within a 3D view or within a Space-Time-Cube. In contrast to previous work, our approach provides insight into the dynamics of past and predicted 3D lightning clusters and cluster features over time. We conclude that an interactive visual exploration in combination with a statistical analysis can provide new knowledge within lightning investigations and, thus, support decision-making in weather forecast or lightning damage prevention. Full article
(This article belongs to the Special Issue Geovisualization and Analysis of Dynamic Phenomena)
Open AccessArticle Dynamics of Sheep Production in Brazil
ISPRS Int. J. Geo-Inf. 2013, 2(3), 665-679; doi:10.3390/ijgi2030665
Received: 30 May 2013 / Revised: 22 July 2013 / Accepted: 22 July 2013 / Published: 31 July 2013
Cited by 4 | PDF Full-text (1098 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Sheep production is present on all continents and has been practiced in Brazil since the colonization. In this study, the multitemporal dynamics of sheep production in Brazil is examined using official government data (Brazilian Institute for Geography and Statistics-IBGE) from 1976 to [...] Read more.
Sheep production is present on all continents and has been practiced in Brazil since the colonization. In this study, the multitemporal dynamics of sheep production in Brazil is examined using official government data (Brazilian Institute for Geography and Statistics-IBGE) from 1976 to 2010. Maps of flock growth rates and growth acceleration maps by municipality were elaborated. The Southern states are seen to show a reduction in production mainly due to the wool crisis in the 1970s and 80s. The Northeast is seen to be important for meat production. More recently, centerwest and northern states have shown an increase in growth rates but this is still incipient. The maps of growth, acceleration and midpoint for sheep production showed a noticeable return to an increase in production in the South in recent years. The midpoint of production flow was in the northeast direction, which has stagnated. There was great dynamics in sheep production over the whole Brazilian territory, which affected supply chains due to the expansion of domestic and foreign markets. Areas with higher fluctuations in production are more vulnerable in terms of investment policies. Full article
(This article belongs to the Special Issue Geovisualization and Analysis of Dynamic Phenomena)
Open AccessArticle Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors
ISPRS Int. J. Geo-Inf. 2013, 2(3), 645-664; doi:10.3390/ijgi2030645
Received: 18 May 2013 / Revised: 17 June 2013 / Accepted: 27 June 2013 / Published: 22 July 2013
PDF Full-text (1170 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a [...] Read more.
Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. Full article
(This article belongs to the Special Issue Geovisualization and Analysis of Dynamic Phenomena)
Open AccessArticle Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization
ISPRS Int. J. Geo-Inf. 2013, 2(2), 456-479; doi:10.3390/ijgi2020456
Received: 22 March 2013 / Revised: 6 May 2013 / Accepted: 6 May 2013 / Published: 24 May 2013
Cited by 1 | PDF Full-text (1478 KB) | HTML Full-text | XML Full-text
Abstract
Visualizing quantitative time-dependent changes in the topography requires relying on a series of discrete given multi-temporal topographic datasets that were acquired on a given time-line. The reality of physical phenomenon occurring during the acquisition times is complex when trying to mutually model [...] Read more.
Visualizing quantitative time-dependent changes in the topography requires relying on a series of discrete given multi-temporal topographic datasets that were acquired on a given time-line. The reality of physical phenomenon occurring during the acquisition times is complex when trying to mutually model the datasets; thus, different levels of spatial inter-relations and geometric inconsistencies among the datasets exist. Any straight forward simulation will result in a truncated, ill-correct and un-smooth visualization. A desired quantitative and qualitative modelling is presumed to describe morphologic changes that occurred, so it can be utilized to carry out more precise and true-to-nature visualization tasks, while trying to best describe the reality transition as it occurred. This research paper suggests adopting a fully automatic hierarchical modelling mechanism, hence implementing several levels of spatial correspondence between the topographic datasets. This quantification is then utilized for the datasets morphing and blending tasks required for intermediate scene visualization. The establishment of a digital model that stores the local spatial transformation parameterization correspondences between the topographic datasets is realized. Along with designated interpolation concepts, this complete process ensures that the visualized transition from one topographic dataset to the other via the quantified correspondences is smooth and continuous, while maintaining morphological and topological relations. Full article
(This article belongs to the Special Issue Geovisualization and Analysis of Dynamic Phenomena)

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