Special Issue "Smart Solutions for Disaster Risk Reduction: Big Data Concepts for Disaster Risk Reduction (DRR)"

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

Deadline for manuscript submissions: closed (30 April 2017)

Special Issue Editor

Guest Editor
Prof. Dr. Milan Konecny

Former President of ICA, chairman of the ICA Commission Cartography for Early Warning and Crises Management, Department of Geography, Faculty of Science, Masyryk University, Brno, Czech Republic
Website | E-Mail
Phone: +420549495135
Fax: +420 549 49 1061
Interests: early warning and disaster/crises management; disaster risk reduction; big data; space and geospatial solutions; GI Science

Special Issue Information

Dear Colleagues,

Overall Motivation

The United Nations work to reduce disaster risk is built on the knowledge and experience of countries and other stakeholders over the past several decades. Milestones include the 1990s being declared the international decade for natural disaster reduction, the adoption of the International Framework for Action for the International Decade for Natural Disaster Reduction, the Yokohama Strategy and Plan of Action for a Safer World adopted by the 1st World Conference on Natural Disaster Reduction, the endorsement of the International Strategy for Disaster Reduction, and the adoption of the Hyogo Framework for Action (HFA) at the 2nd World Conference on Disaster Reduction.

The last U.N. Disaster Risk Reduction (DRR) conference in Sendai, Japan (March 18, 2015) decided to continue in best practices for the present and also to enhance the sustainability of all efforts through the deeper, wider, and complex approaches to Disaster Risk Reduction, formulated in four most important priorities: 1. Understanding disaster risk; 2. Strengthening disaster risk governance to manage disaster risk; 3. Investing in disaster risk reduction for resilience; and 4. Enhancing disaster preparedness for effective response and to “Build Back Better” in recovery, rehabilitation, and reconstruction.

As never before, such U.N. efforts are formulated expectations from research and science, which would make all efforts more progressive, effective, and efficient. In realizations of priorities, it is expected that space and (geo)spatial methods and technologies and various parts of mapping (e.g., risk one) will be fully included. Moreover, our research efforts can fill up ISPRS intentions about “the central role of imagery and derived products in disaster management and homeland establishment, complementing its traditional central place in defence”. GI Science can also offer new and strong efforts, such as VGI (Volunteer Geographic Information),  VGE (Virtual Geographic Environments), new ways of fully use Big Data, personalization of maps, by understanding context and adaptive cartography, etc. These, all together, can progressively improve the quality of the disaster risk management cycle (preparedness, early warning, alert, assessment, etc.) and also, and it is the main topic of this Special Issue, to improve complex smart solutions for the realization of Disaster Risk Reduction tasks.

Aims of this Special Issue

This Special Issue aims to promote innovative concepts, methods and tools that help in solving current and future problems in DRR, assisted by space and (geo)spatial technologies,  approaches in GI Science, and mapping.

Global, national, and local level development, which periodically updates and disseminates, as appropriate, location-based disaster risk information, is expected from our research communities. There are requests to design and improve risk maps for decision makers, the general public, and communities at risk of exposure to disaster, in an appropriate format by using, as applicable, geospatial information technology; e.g., to promote real-time access to reliable data, make use of space and in situ information, including geographic information systems (GIS), and use information and communications innovations, and, last but not least, to enhance measurement tools and the collection, analysis, and dissemination of data.

Very important is to formulate the role of Big Data technologies and methods and potentials of newly appearing activities, such as citizen science, which should also effectively enhance  approaches used in DRR.

Topics

In line with the specific DRR context, as outlined above, we would like to invite original research contributions on the following topics (which might be extended):

Space Solutions:
  • Remote Sensing Usability for DRR
  • Matching RS and PE to 2D maps and 3D models
  • Remote sensing in different disaster management phases (warning, monitoring, relief, assessment and recovery).
  • UAV application in DRR
  • Open RS clouds for DRR
  • New sensor data for disaster monitoring and response
  • Sensor cloud for disaster data acquisition
  • Multi-source RS data fusion for disaster management
  • Automated disaster information extraction from RS data
  • Automated 3D scene reconstruction for disaster management

Spatial solutions:

  • Big Data and VGI for disaster risk reduction
  • Smart Maps for DRR
  • Geoinformatics for DRR
  • Real-time mapping
  • Dynamic geovisualization
  • Geo-process model bases
  • Efficiency of disaster maps
  • Standardization of maps of hazards and disasters
  • Geo Map Web Services
  • Disaster Early warning systems
  • Disaster Assessment and aftermath monitoring
  • Prediction of combined hazards, risks and disaster effects.
  • Evaluation of hazard, risk and disaster scenarios
  • 3D modeling and mapping of hazards, risks and disasters
  • Space-Time Data Mining and Knowledge Discovery
  • Disaster Risk management and sustainable development in DRR
  • Sharing and use of non-sensitive data and information
  • Geospatial and space-based technologies and related services for decision-makers, inhabitants and customers

Prof. Dr. Milan Konecny
Guest Editor

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 900 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.

References

Bandrova, T.; Zlatanova S.; Konecny, M. Three-dimensional maps for disaster management. ISPRS Ann. Photogramm. Remote Sens. 2012, doi:10.5194/isprsannals-I-4-245-2012.

Bandrova, T.; Konecny, M.; Zlatanova, S. Thematic Cartography for the Society; Springer: Berlin, Germany, 2014.

Bandrova, T.; Zlatanova, S.; Konecny, M. Geoinformation for Disaster and Risk Management, Examples and Best Practices; Joint Board of Geospatial Information Societies (JB GIS) and United Nations Office for Outer Space Affairs (UNOOSA): Copenhagen, Denmark, 2010.

ISDR, 2007, Hyogo Framework for Action, 2005-2015, Building the Resilience of Nations and Communities to Disasters. Avalible online: https://www.unisdr.org/we/coordinate/hfa (accessed on 14 April 2016).

Konecny, M.; Zlatanova, S.; Bandrova T. Geographic Information and Cartography for Risk and Crisis Management; Towards Better Solutions; Springer: Berlin Heidelberg, 2010.

Konecny, M.; Reinhardt W. Early warning and disaster management: the importance of geographic information (Part A). Int. J. Digit. Earth 2010, 3, 217–220.

Konecny, M.; Reinhardt W. Early warning and disaster management: the importance of geographic information (PartB). Int. J. Digit. Earth 2010, 3, 313–315.

Lin, H.; Batty, M.; Jørgensen, S.E.; Fu, B.; Konecny, M.; Voinov, A.; Torrens, P.; Lu, G.; Zhu, A-X.; Wilson, J.P.; Gong, J.; Kolditz, O.; Bandrova T.; Chen. M. Virtual environments begin to embrace process-based geographic analysis. Transact. GIS 2015, doi:10.1111/tgis.12167.

Nayak S.; Zlatanova S. Remote Sensing and GIS Technologies for Monitoring and Prediction of Disasters; Springer Science & Business Media: Berlin, Germany, 2008.

Altan, O.; Backhause, R.; Boccardo, P.; van Manen, N.; Trinder J.; Zlatanova. S. The Value of Geoinformation for Disaster and Risk Management (VALID): Benefit Analysis and Stakeholder Assessment; Joint Board of Geospatial Information Societies (JB GIS): Copenhagen, Denmark, 2013.

UNISDR. Sendai Framework for Disaster Risk Reduction 2015–2030; United Nations: New York, NY, USA, 2015.

Published Papers (6 papers)

View options order results:
result details:
Displaying articles 1-6
Export citation of selected articles as:

Research

Open AccessArticle Design of a Model Base Framework for Model Environment Construction in a Virtual Geographic Environment (VGE)
ISPRS Int. J. Geo-Inf. 2017, 6(5), 145; doi:10.3390/ijgi6050145
Received: 20 February 2017 / Revised: 21 April 2017 / Accepted: 27 April 2017 / Published: 4 May 2017
PDF Full-text (3708 KB) | HTML Full-text | XML Full-text
Abstract
The model environment is a key component that enables a virtual geographic environment (VGE) to meet the scientific requirements for simulating dynamic phenomena and performing analyses. Considering the comprehensiveness of geographic processes and the requirements for the replication of model-based research, this paper
[...] Read more.
The model environment is a key component that enables a virtual geographic environment (VGE) to meet the scientific requirements for simulating dynamic phenomena and performing analyses. Considering the comprehensiveness of geographic processes and the requirements for the replication of model-based research, this paper proposes a model base framework for a model environment of a VGE that supports both model construction and modelling management, resulting in improved reproducibility. In this framework, model management includes model metadata, creation, deposition, encapsulation, integration, and adaptation; while modelling management focuses on invoking the model, model computation, and runtime control of the model. Based on this framework, to consider the problem of ever-worsening air quality, we applied the Linux-Apache-MySQL-Perl stack plus Supervisor to implement the model base to support a VGE prototype using professional meteorological and air quality models. Using this VGE prototype, we simulated a typical air pollution case for January 2010. The prototype not only illustrates how a VGE application can be built on the proposed model base, but also facilitates air quality simulations and emergency management. Full article
Figures

Figure 1

Open AccessArticle Multi-Objective Emergency Material Vehicle Dispatching and Routing under Dynamic Constraints in an Earthquake Disaster Environment
ISPRS Int. J. Geo-Inf. 2017, 6(5), 142; doi:10.3390/ijgi6050142
Received: 9 December 2016 / Revised: 28 April 2017 / Accepted: 28 April 2017 / Published: 2 May 2017
PDF Full-text (20072 KB) | HTML Full-text | XML Full-text
Abstract
Emergency material vehicle dispatching and routing (EMVDR) is an important task in emergency relief after large-scale earthquake disasters. However, EMVDR is subject to dynamic disaster environment, with uncertainty surrounding elements such as the transportation network and relief materials. Accurate and dynamic emergency material
[...] Read more.
Emergency material vehicle dispatching and routing (EMVDR) is an important task in emergency relief after large-scale earthquake disasters. However, EMVDR is subject to dynamic disaster environment, with uncertainty surrounding elements such as the transportation network and relief materials. Accurate and dynamic emergency material dispatching and routing is difficult. This paper proposes an effective and efficient multi-objective multi-dynamic-constraint emergency material vehicle dispatching and routing model. Considering travel time, road capacity, and material supply and demand, the proposed EMVDR model is to deliver emergency materials from multiple emergency material depositories to multiple disaster points while satisfying the objectives of maximizing transport efficiency and minimizing the difference of material urgency degrees among multiple disaster points at any one time. Furthermore, a continuous-time dynamic network flow method is developed to solve this complicated model. The collected data from Ludian earthquake were used to conduct our experiments in the post-quake and the results demonstrate that: (1) the EMVDR model adapts to the dynamic disaster environment very well; (2) considering the difference of material urgency degree, the material loss ratio is −10.7%, but the variance of urgency degree decreases from 2.39 to 0.37; (3) the EMVDR model shows good performance in time and space, which allows for decisions to be made nearly in real time. This paper can provide spatial decision-making support for emergency material relief in large-scale earthquake disasters. Full article
Figures

Figure 1

Open AccessArticle Detecting Damaged Building Regions Based on Semantic Scene Change from Multi-Temporal High-Resolution Remote Sensing Images
ISPRS Int. J. Geo-Inf. 2017, 6(5), 131; doi:10.3390/ijgi6050131
Received: 28 January 2017 / Revised: 20 April 2017 / Accepted: 25 April 2017 / Published: 27 April 2017
PDF Full-text (8620 KB) | HTML Full-text | XML Full-text
Abstract
The detection of damaged building regions is crucial to emergency response actions and rescue work after a disaster. Change detection methods using multi-temporal remote sensing images are widely used for this purpose. Differing from traditional methods based on change detection for damaged building
[...] Read more.
The detection of damaged building regions is crucial to emergency response actions and rescue work after a disaster. Change detection methods using multi-temporal remote sensing images are widely used for this purpose. Differing from traditional methods based on change detection for damaged building regions, semantic scene change can provide a new point of view since it can indicate the land-use variation at the semantic level. In this paper, a novel method is proposed for detecting damaged building regions based on semantic scene change in a visual Bag-of-Words model. Pre- and post-disaster scene change in building regions are represented by a uniform visual codebook frequency. The scene change of damaged and non-damaged building regions is discriminated using the Support Vector Machine (SVM) classifier. An evaluation of experimental results, for a selected study site of the Longtou hill town of Yunnan, China, which was heavily damaged in the Ludian earthquake of 14 March 2013, shows that this method is feasible and effective for detecting damaged building regions. For the experiments, WorldView-2 optical imagery and aerial imagery is used. Full article
Figures

Figure 1

Open AccessArticle A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution
ISPRS Int. J. Geo-Inf. 2017, 6(4), 114; doi:10.3390/ijgi6040114
Received: 30 January 2017 / Revised: 28 March 2017 / Accepted: 5 April 2017 / Published: 8 April 2017
PDF Full-text (2079 KB) | HTML Full-text | XML Full-text
Abstract
With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout
[...] Read more.
With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout the different phases of risk management reaching from pre-disaster mitigation to the response after an event and the long-term recovery of affected assets. Spatio-temporal changes need to be integrated into a sound conceptual and technological framework able to deal with data coming from different sources, at varying scales, and changing in space and time. Especially managing the information life-cycle, the integration of heterogeneous information and the distributed versioning and release of geospatial information are important topics that need to become essential parts of modern exposure modelling solutions. The main purpose of this study is to provide a conceptual and technological framework to tackle the requirements implied by disaster risk management for describing exposed assets in space and time. An information life-cycle management solution is proposed, based on a relational spatio-temporal database model coupled with Git and GeoGig repositories for distributed versioning. Two application scenarios focusing on the modelling of residential building stocks are presented to show the capabilities of the implemented solution. A prototype database model is shared on GitHub along with the necessary scenario data. Full article
Figures

Figure 1

Open AccessArticle A Procedural Construction Method for Interactive Map Symbols Used for Disasters and Emergency Response
ISPRS Int. J. Geo-Inf. 2017, 6(4), 95; doi:10.3390/ijgi6040095
Received: 11 January 2017 / Revised: 19 March 2017 / Accepted: 22 March 2017 / Published: 24 March 2017
PDF Full-text (15497 KB) | HTML Full-text | XML Full-text
Abstract
The timely and accurate mapping of dynamic disasters and emergencies is an important task that is necessary for supporting the decision-making that can improve the efficiency of rescue and response efforts. The existing emergency symbol libraries are primarily composed of point symbols and
[...] Read more.
The timely and accurate mapping of dynamic disasters and emergencies is an important task that is necessary for supporting the decision-making that can improve the efficiency of rescue and response efforts. The existing emergency symbol libraries are primarily composed of point symbols and simple line symbols, focusing on the representation of disasters, related facilities, and operations. However, various existing response factors (e.g., the distribution and types of emergency forces) are also important for further decision-making and emergency responses; there is a need to design complex and diverse symbols to represent this rich information. Moreover, traditional mapping systems only provide static map symbols that cannot be easily edited after creation, making it difficult to support interactive editing after the symbols are mapped, thus hindering the representation of dynamic disasters and response factors. This article targets a solution of the above issues by proposing a procedural construction method of interactive map symbols for dynamic disasters and emergency responses. There are two primary research points. First, an emergency response and decision symbol library was classified and integrated into the existing attachments to form a richer symbol library for comprehensively representing disasters and emergencies. Second, an interactive map symbol procedural construction method was designed based on (1) primitive geometric compositions and geometric graphics algorithms to construct the map symbol graphics; (2) an interactive graphics control and drawing attributes configuration method to support user interactive editing of the visual variables of the mapped symbols; (3) and a dynamic updating and drawing strategy to support the real-time refreshing of the changing visual variables. The experiment was conducted using the Wenchuan earthquake as a case study, and the results demonstrate a powerful capacity of the produced interactive map symbols, which will contribute to the improvement of the mapping efficiency and representation capability of disasters and emergency response. Full article
Figures

Figure 1

Open AccessArticle A Spatial Lattice Model Applied for Meteorological Visualization and Analysis
ISPRS Int. J. Geo-Inf. 2017, 6(3), 77; doi:10.3390/ijgi6030077
Received: 10 October 2016 / Revised: 2 March 2017 / Accepted: 6 March 2017 / Published: 9 March 2017
PDF Full-text (9417 KB) | HTML Full-text | XML Full-text
Abstract
Meteorological information has obvious spatial-temporal characteristics. Although it is meaningful to employ a geographic information system (GIS) to visualize and analyze the meteorological information for better identification and forecasting of meteorological weather so as to reduce the meteorological disaster loss, modeling meteorological information
[...] Read more.
Meteorological information has obvious spatial-temporal characteristics. Although it is meaningful to employ a geographic information system (GIS) to visualize and analyze the meteorological information for better identification and forecasting of meteorological weather so as to reduce the meteorological disaster loss, modeling meteorological information based on a GIS is still difficult because meteorological elements generally have no stable shape or clear boundary. To date, there are still few GIS models that can satisfy the requirements of both meteorological visualization and analysis. In this article, a spatial lattice model based on sampling particles is proposed to support both the representation and analysis of meteorological information. In this model, a spatial sampling particle is regarded as the basic element that contains the meteorological information, and the location where the particle is placed with the time mark. The location information is generally represented using a point. As these points can be extended to a surface in two dimensions and a voxel in three dimensions, if these surfaces and voxels can occupy a certain space, then this space can be represented using these spatial sampling particles with their point locations and meteorological information. In this case, the full meteorological space can then be represented by arranging numerous particles with their point locations in a certain structure and resolution, i.e., the spatial lattice model, and extended at a higher resolution when necessary. For practical use, the meteorological space is logically classified into three types of spaces, namely the projection surface space, curved surface space, and stereoscopic space, and application-oriented spatial lattice models with different organization forms of spatial sampling particles are designed to support the representation, inquiry, and analysis of meteorological information within the three types of surfaces. Cases studies are conducted by (1) performing a visualization of radar data that is used to describe the reflectivity factor of a raindrop and the pressure field information acquired from the National Centers for Environmental Prediction (NCEP), and (2) taking cutting analysis as another example where advanced meteorological analysis is performed. The results show that the proposed spatial lattice model can contribute to the feasible and effective analysis of meteorological information. Full article
Figures

Figure 1

Journal Contact

MDPI AG
IJGI Editorial Office
St. Alban-Anlage 66, 4052 Basel, Switzerland
E-Mail: 
Tel. +41 61 683 77 34
Fax: +41 61 302 89 18
Editorial Board
Contact Details Submit to IJGI Edit a special issue Review for IJGI
loading...
Back to Top