Original Research ARTICLE
Field Data Collection Framework Development and Applications
- 1GNS Science, New Zealand
- 2Retired, New Zealand
- 3National Institute of Water and Atmospheric Research (NIWA), New Zealand
Rapid and profound changes in the technology used for data acquisition, computing and information management provides a framework that has the potential to allow communities to consider acquiring, analysing and managing data in new ways. Improving the collection and management of data, immediately in post-disaster reconnaissance and in long-term impact assessments, is central to enabling knowledge of such events to be used and applied to improving community resilience to those disasters.
This paper presents the development and applications of an integrated and extensible framework for the capture of attribute data that describes pre-disaster physical characteristics and post-disaster damage of assets within our communities. The framework, referred to as Real-time Individual Asset Attribute Collection Tool (RiACT) and its associated Asset Repository Web Portal, enables data capture by direct field observations of asset attributes. It also includes the real-time transfer of these field observations to the web portal and/or the download of previously acquired history and metadata of any specific asset of interest to the observer whilst they are in the field. The use of this framework enables improved understanding of asset portfolios within the context of risk reduction and readiness, as well as facilitating efficient and rapid capture of damage distribution across the affected region. This in turn supports better decision making for a quicker disaster response and recovery.
This paper presents a review of the existing state-of-art data collection methodologies and describe the development of an improved tool and its Information Technology architecture. Experiences and challenges in applying the framework are highlighted through: 1) the capture of community data in Viet Nam for a multi-hazard assessment in 2014 and 2018, the refinement of asset data related to residential buildings in the Greater Wellington region in 2016, and a survey of building types in Tanna, Vanuatu in 2018; 2) facilitating training in field data capture processes in Indonesia in 2015, as well as in Samoa and Vanuatu in 2017; 3) collection of asset damage data following the 2016 Kaikōura earthquake in New Zealand, the 2016 Tropical Cyclone Winston in Fiji and the 2015 Illapel earthquake and tsunami in Chile.
Keywords: post-disaster reconnaissance, Field data collection, survey attributes, inventory repository, exposure dataset, Damage assessment
Received: 28 Jun 2018;
Accepted: 04 Feb 2019.
Edited by:Sean Wilkinson, Newcastle University, United Kingdom
Reviewed by:Michele Palermo, University of Bologna, Italy
Richard J. Krupar III, Independent researcher
Copyright: © 2019 Lin, King, Horspool, Sadashiva, Paulik and Williams. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Sheng-Lin Lin, GNS Science, Lower Hutt, New Zealand, firstname.lastname@example.org