Potential of Collaborative Mapping for Disaster Relief: A Case Study of OpenStreetMap in the Nepal Earthquake 2015

Poiani, Thiago Henrique; Rocha, Roberto dos Santos; Degrossi, Lívia Castro; Albuquerque, João Porto de

doi:10.1109/hicss.2016.31

Cited by 63 publications

(49 citation statements)

References 8 publications

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“…These sites produced damage maps that were used extensively by the Nepali military, both for logistics planning and for identifying communities in need of assistance (Nepalese Army, 2015). The value of such crowd-sourced information has also been recognized by the scientific community in response to several recent natural disasters (e.g., Goodchild and Glennon, 2010;Barrington et al, 2012;Roche et al, 2013;Poiani et al, 2016). To date crowd sourcing has not, however, been employed to map coseismic landslides in a manner that is reliable.…”

Section: Science Citizen Science and Coseismic Landslide Assessmentmentioning

confidence: 99%

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Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

Williams

Rosser

Kincey

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides triggered by large earthquakes in mountainous regions contribute significantly to overall earthquake losses and pose a major secondary hazard that can persist for months or years. While scientific investigations of coseismic landsliding are increasingly common, there is no protocol for rapid (hours-to-days) humanitarian-facing landslide assessment and no published recognition of what is possible and what is useful to compile immediately after the event. Drawing on the 2015 M w 7.8 Gorkha earthquake in Nepal, we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated. We find that, at present, many forms of landslide assessment are too slow to generate relative to the speed of a humanitarian response, despite increasingly rapid access to high-quality imagery. Importantly, the value of information on landslides evolves rapidly as a disaster response develops, so identifying the purpose, timescales, and end users of a post-earthquake landslide assessment is essential to inform the approach taken. It is clear that discussions are needed on the form and timing of landslide assessments, and how best to present and share this information, before rather than after an earthquake strikes. In this paper, we share the lessons learned from the Gorkha earthquake, with the aim of informing the approach taken by scientists to understand the evolving landslide hazard in future events and the expectations of the humanitarian community involved in disaster response.

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Section: Science Citizen Science and Coseismic Landslide Assessmentmentioning

confidence: 99%

“…communicate or interpret. Roche et al, 2013; ascertainment of total spatial extent and relative intensity Poiani et al, 2016 Lu et al, 2011;.…”

Section: Empirically Modeledmentioning

confidence: 99%

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

Williams

Rosser

Kincey

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…The fast growing Humanitarian OpenStreetMap Team has reached some of the most disaster vulnerable and data scarce regions, such as South and Southeast Asia and Sub-Saharan Africa [46]. For example, in the 2015 Nepal Earthquake, thousands of volunteers from around the world contributed to mapping the surrounding infrastructure such as buildings and roads in Nepal [47]. Humanitarian OpenStreetMap Team relies heavily on the willingness of volunteers, both to contribute entries and to validate the maps through its OSM tasking manager.…”

Section: Literature Review: Participatory and Collaborative Risk Mappmentioning

confidence: 99%

Integrated Participatory and Collaborative Risk Mapping for Enhancing Disaster Resilience

Liu

Dugar²,

McCallum

et al. 2018

IJGI

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Critical knowledge gaps seriously hinder efforts for building disaster resilience at all levels, especially in disaster-prone least developed countries. Information deficiency is most serious at local levels, especially in terms of spatial information on risk, resources, and capacities of communities. To tackle this challenge, we develop a general methodological approach that integrates community-based participatory mapping processes, one that has been widely used by governments and non-government organizations in the fields of natural resources management, disaster risk reduction and rural development, with emerging collaborative digital mapping techniques. We demonstrate the value and potential of this integrated participatory and collaborative mapping approach by conducting a pilot study in the flood-prone lower Karnali river basin in Western Nepal. The process engaged a wide range of stakeholders and non-stakeholder citizens to co-produce locally relevant geographic information on resources, capacities, and flood risks of selected communities. The new digital community maps are richer in content, more accurate, and easier to update and share than those produced by conventional Vulnerability and Capacity Assessments (VCAs), a variant of Participatory Rural Appraisal (PRA), that is widely used by various government and non-government organizations. We discuss how this integrated mapping approach may provide an effective link between coordinating and implementing local disaster risk reduction and resilience building interventions to designing and informing regional development plans, as well as its limitations in terms of technological barrier, map ownership, and empowerment potential.

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“…However, very few studies have reported on the fitness-of-use of the dataset in developing countries [56,[90][91][92][93] using established quality indicators. The established methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data [14].…”

Section: Semantic Accuracymentioning

confidence: 99%

Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox

Sehra

Singh

2017

Future Internet

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OpenStreetMap (OSM) is a recent emerging area in computational science. There are several unexplored issues in the quality assessment of OSM. Firstly, researchers are using various established assessment methods by comparing OSM with authoritative dataset. However, these methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data. In such a scenario, the intrinsic quality indicators can be used to assess the quality. Secondly, a framework for data assessment specific to different geographic information system (GIS) domains is not available. In this light, the current study presents an extension of the Quantum GIS (QGIS) processing toolbox by using existing functionalities and writing new scripts to handle spatial data. This would enable researchers to assess the completeness of spatial data using intrinsic indicators. The study also proposed a heuristic approach to test the road navigability of OSM data. The developed models are applied on Punjab (India) OSM data. The results suggest that the OSM project in Punjab (India) is progressing at a slow peace, and contributors' motivation is required to enhance the fitness of data. It is concluded that the scripts developed to provide an intuitive method to assess the OSM data based on quality indicators can be easily utilized for evaluating the fitness-of-use of the data of any region.

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Potential of Collaborative Mapping for Disaster Relief: A Case Study of OpenStreetMap in the Nepal Earthquake 2015

Cited by 63 publications

References 8 publications

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

Integrated Participatory and Collaborative Risk Mapping for Enhancing Disaster Resilience

Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox

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