Special Issue "Scaling, Spatio-Temporal Modeling, and Crisis Informatics"

Special Issue Editors

Dr. Bandana Kar
Website
Guest Editor
Remote Sensing Group, Oak Ridge National Laboratory, P.O. Box 2008, 1 Bethel Valley, Road Oak Ridge, TN 37831-6134, USA
Interests: scaling and reproducibility; spatiotemporal modeling; geoifnormatics; risk assessment; infrastructure and community resilience; risk communication; spatial decision support system; remote sensing applications; data mining; machine learning
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Dr. Xinyue Ye
Website
Guest Editor
Department of Informatics, Urban Informatics & Spatial Computation Lab, New Jersey Institute of Technology, Newark, NJ 07102, USA
Interests: network science; natural language processing; open source geocomputation; spatio-temporal analysis; spatial econometrics; urban informatics; visual analytics
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Dr. Zhenlong Li
Website
Guest Editor
Geoinformation and Big Data Research Laboratory (GIBD), Department of Geography, University of South Carolina, Columbia, SC, 29208, USA
Interests: GIScience; geospatial big data analytics; high-performance computing; cybergis; social media analytics
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Dr. Qunying Huang
Website
Guest Editor
Department of Geography, University of Wisconsin-Madison, Madison, WI 53706-1491, USA
Interests: spatial data mining; machine learning; social media analytics; natural hazards; human mobility
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Special Issue Information

Dear Colleagues,

There has been a significant increase in the severity and frequency of crises and hazards worldwide, which are defined as “an interruption in the reproduction of economic, cultural, social and/or political life (Johnston, R.J. (2002). Dictionary of human geography. (4th ed.). Oxford, UK: Blackwell.)”. While extreme weather events are usually the causes of crisis, 2020 has become an expensive and deadly year due to another type of crisis, i.e., the COVID-19 pandemic. Whatever the cause of a crisis, though, technologies like cloud computing, location-based services, network science, web applications, and artificial intelligence (AI) are being used for crisis informatics to aid with crisis management and resilience efforts. 
Similarly, data obtained from both static and dynamic sources, such as remote sensing, unmanned aerial systems, and social media, enable the development of new approaches to charaterize and predict disaster situations at different locations and scales. Human dynamics data in both physical and virtual spaces are big, spatial, temporal, dynamic, and unstructured. The proliferation of data and interactive mapping technologies has also significantly enhanced access to and utility of spatial decision support systems, helping communities to better prepare for, respond to, and recover from crises and hazards. Understanding human dynamics can help to more efficiently deal with natural or man-made disasters. Significant advancements have also been made in developing statistical as well as data-driven models to integrate these heterogeneous data for real-time and off-time informatics. Because of the heterogeneous nature of these data in terms of data structure, content, data sources, and the spatial and temporal resolutions at which they are being obtained, these data suffer from uncertainties associated with positional accuracy, reliability, and completeness, thereby impacting the quality of the models being generated and their reproducibility.
Due to the spatiotemporal nature of a crisis, geospatial data sets and spatiotemporal models integrating various data sources are being developed. In addition to the uncertainties associated with the data, the developed models rarely account for scale, which influences not only the mechanisms used to aggregate and integrate data sets, but also the final outputs of the model. The end result is the development of models for crisis informatics that produce varying results and hence may not be useful in real-time decision making.
In this Special Issue in ISPRS International Journal of Geo-Information, we solicit articles that advance theories and methods and/or applications integrating spatial and temporal datasets at varying scales for crisis informatics. The articles should leverage existing theories and/or develop new theories of scaling and spatiotemporal modeling while taking advantage of big data theories and technologies to aid with crisis/disaster preparedness, mitigation, recovery, and resilience.

 Potential topics include (but are not limited to) the following:

  1. Uncertainty in data and spatiotemporal models;
  2. Data fusion methods and accuracies;
  3. Data quality and impact on decision making;
  4. Role of scale and reproducibility of models;
  5. Human dynamics in crises and hazards;
  6. Open knowledge network and convergence research;
  7. Spatial decision support systsem for crisis management;
  8. Geo-visualization and geo-computation techniques for real-time applications;
  9. Models and analytics for crisis, human movement and behaviors, interaction of natural and built environments.

This Special Issue is scheduled to be published by 30 April 2021. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the Special Issue website.

Dr. Bandana Kar
Dr. Xinyue Ye
Dr. Zhenlong Li
Dr. Qunying Huang
Guest Editors

Manuscript Submission Information

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. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short 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 thoroughly refereed through a single-blind 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 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers

This special issue is now open for submission.
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