减灾研究历史数据集专题 I 区论文(评审中) 版本 EN2
下载
Rapid Damage Mapping and Loss Data Collection for Natural Disasters - Case Study from Kaikoura Earthquake, New Zealand
 >>
: 2018 - 05 - 25
: 2018 - 07 - 04
: 2018 - 07 - 04
809 1 0
Abstract & Keywords
Abstract: On November 13, 2016, a 7.8 magnitude earthquake struck the northeast coast of the South Island in New Zealand. A tsunami swept onto the coastlines with wave-heights of 2.5 m at Kaikoura. This earthquake is the largest event in the region since a magnitude 7.5 earthquake that occurred 100 km to the northeast in October 1848. The days immediately following a natural disaster are particularly challenging for authorities and aid organisations who need to make decisions relating to deployment and distribution of resources. Rapid Damage Mapping (RDM) is a tool developed by Tonkin + Taylor International Limited (T+TI) whereby integrated disaster mapping information is assembled within the first 24 to 72 hrs of an event. The CODATA Task Group of Linked Open Data for Global Disaster Risk Research (LODGD) organized ChinaGEOSS portal to access TripleSat and JL-1 satellite images immediately following the devastating Kaikoura Earthquake. An internet based Project Orbit portal was set up for use by all response and recovery organisations in New Zealand. While the recent RDM response work was largely reactive in nature, the data set compiled during this work provides a valuable resource, presenting opportunities to apply a more proactive and refined approach to similar RDM work in the future. The recent RDM work provides valuable insight into key vulnerabilities that evolved after the earthquake, and helped to identify more than 10,000 landslips in the area.
Keywords: Rapid damage mapping; earthquake; risk reduction
Dataset Profile
Chinese title自然灾害快速灾损制图与损失数据收集——以新西兰凯库拉地震为例
English titleRapid Damage Mapping and Loss Data Collection for Natural Disasters - Case Study from Kaikoura Earthquake, New Zealand
Corresponding authorBapon Fakhruddin
Data author(s)Bapon Fakhruddin, Li Guoqing, Rebekah Robertson
Time range2016-2018
Geographical scope 41.966997 S - 42.631182 S, 173.465577 N - 173.948527 N ; Specific areas include: Kaikoura Peninsular and inland mountains of the top of the North Island of New Zealand
Spatial resolution3mData volume3.37 MB
Data formatTIFF
Data service system<http://www.sciencedb.cn/dataSet/handle/605>
Source(s) of fundingNA
Dataset/Database compositionThe data set consists of a geodatabase (KevDataWithoutPhotos.gdb.zip) which contains a set of 11 feature classes showing the following information: EQC_NOV16DamageArea_PVE EQC_Nov16DamageLine_PVE EQC_Nov16DamageLocation_PVE GNS_Nov16LandslideCrown_PVS GNS_Nov16LandslideDebrisToe_PVS GNS_Nov16LandslideDebrisTrails_PVS GNS_Nov16LandslideSourceAreas_PVS GNS_Nov16LandslideSurfaceDeformation_PVS GNS_Nov16LandslideFaultRuptures_PVS GNS_Nov16LandslideFaultRupturesBuffer_PVS UC_FaultTraceMapping_PVS
1.   Introduction
Rapid advances in technology leading to substantially higher resolution data-sets arguably hamper regional scale damage assessment, particularly in counties that lack specialist services to manage this information. The primary objective of Rapid Damage Mapping (RDM) is to empower organisations with regional scale mapping information of a resolution appropriate for early coordination and management for disaster response.
The following outlines the setting in which the Kaikoura earthquake occurred and an overview on rapid disaster mapping and loss data collection, focusing on the benefits of a central data repository.
2.   New Zealand’s Tectonic Setting
New Zealand is situated on the boundary of the Australian and the Pacific tectonic plates. Off the east coast of the North Island, the Pacific Plate subducts beneath the Australian plate (Figure 2-1). Off the south west coast of the South Island, this feature is reversed with the Australian Plate subducting under the Pacific plate. The transition between these subduction zones occurs through the top east of the South Island and down the west coast in the form of the transpressional Alpine Fault (Bain, 2014). This fault has an estimated rupture reoccurrence interval of ~330 years and has had up to ~480 km of movement in the form of multiple magnitude ~8 earthquakes (Castelltort, et al., 2012).


Figure 2-1   Tectonic setting of New Zealand adapted from (Bain, 2014)
At the northern end of the Alpine Fault, the system begins to transition into the Hikurangi Trench subduction zone (Figure 2-1 and) as multiple faults splay off creating the Marlborough Fault System (MFS) (Wilson, Jones, Molnar, Sheehan, & Boyd, 2004). The four major splay faults include the Wairau, Awatere, Calrence, Kekerengu and Hope faults and each have a moment magnitude potential of up to 7 Mw or possibly greater (Robinson & Davies, 2013).
At 12.02 am on 14 November 2016, a complex sequence of 21 fault ruptures in the MFS, including a section of the Hope and Kekerengu faults. The ruptures produced a series of earthquakes with a combined magnitude of 7.8 Mw. Their collective energy spread 250km northward at 7,200 kilometres per hour with the seismic shaking lasting up to two minutes. Strong shaking was reported throughout New Zealand’s North and South Islands (GNS, 2016).
At Kaikoura, a massive shoreline shelf was thrust upwards, while parts of the South Island were shunted more than 5m closer to the North Island and other parts raised by up to 8 m (T+TI, 2017). The resultant tsunami waves reached a peak height of about 2 m at Kaikoura, 7 m at Goose Bay and 5 m high at Little Pigeon Bay on Banks Peninsula which knocked a cottage off its foundations (T+TI, 2017). Tsunami waves were also recorded in Wellington Harbour, Castlepoint, Lyttleton and the Chatham Islands. However, there was no significant damage to infrastructure (T+TI, 2017). State Highway One (SH1) and the main trunk rail line running to the north and south of Kaikoura were blocked by a few of the expected 80,000 to 100,00 landslides that occurred after the shaking (GNS, 2016). The secondary inland Kaikoura road had also been blocked. With road and rail links severed, Kaikoura township - home to approximately 3,700 people – and its wide rural catchment scattered with many farms and tiny, remote communities, were only accessible by air (T+TI, 2017). Massive changes to the sea shore and seabed had rendered the town’s port commercially inoperable until dredging of the harbour could occur. At least 150 landslides had blocked rivers creating landslide dams (GNS, 2016). Dam outbreak floods created a high risk for townships down stream with some towns needing to be evacuated during periods of higher rainfall during the days and weeks after the initial earthquake (GNS, 2016).


Figure 2-2   Active faults in the Marborough Fault System adapted from the Kaikoura Earthquake Viewer (T+TI, 2016)
2.1   Rapid Damage Mapping
In a natural disaster, such as an earthquake, accurate and locationally precise information on the damage caused is vital for prioritised rescue and relief operations, to mobilise resources for repair and recovery (Saito & Spence, 2004). An early response in case of strong and destructive event is very important to support and to manage the rescue activities (Dell’Acqua, Bignami, & Chini, 2011). Conventional methods of information gathering that often rely on teams studying the damage on the spot are slow and incompatible with immediate relief (Robinson & Davies, 2013). There is now considerable interest in the acquisition, interpretation and use of information from remote sensing such as satellite imagery or unmanned aerial vehicles (Saito & Spence, 2004). This is because of the opportunity it presents to gather information over a wide area quickly, consistently, and independently of the situation on the ground (Saito & Spence, 2004). Both qualitative and quantitative methods can rapidly create a damage map that visualises the distribution of damage and types of damages observed on buildings (Saito & Spence, 2004). Depending on the quality of the images obtained, the accuracy is typically suitable to support early emergency and rescue planning in areas which need the most immediate help (Saito & Spence, 2004). To create a rapid damage map, the following four processes are required:
1. Obtaining information on the building stock, e.g. footprints, function of the building, height, area size, material of building.
2. Assessment of the damage to buildings, such as total collapse or heavy damage to the structure.
3. The creation of damage maps. The maps could take the shape of grid-based damage maps or building-by-building damage maps, when possible.
4. Road network, access and damage location maps (Saito & Spence, 2004)
During the Kaikoura earthquake, IRDR’s Disaster Loss DATA project and the CODATA Task Group LODGD worked together with T+TI to provide TripleSat satellite images of the affected Hurunui District. Geo-spatial information was developed for the New Zealand Earthquake Commission (EQC) on the damage caused, and was made available through a web-based viewer to all government agencies, response and recovery agencies, engineers and researchers, thereby informing first response and mitigation measure (Fakhruddin, Murray, & Maini, 2017).
2.2   Loss Data Collection for Natural Disasters
Damage and loss estimation is often difficult immediately after a natural disaster since data and information are not easily obtainable (Fakhrudden, Murray, & Maini, 2017). When human, monetary or environmental losses occur because of a disaster, extensive loss data is often collected and stored by different organizations, but the thoroughness and accuracy of the data can vary among local entities (Fakhruddin, Murray, & Maini, 2017). The data collection is pivotal to the comprehensive assessment of disaster impacts and can be hard to obtain due to the differences in the form it is presented in by different agencies. Centralised disaster loss databases are crucial to producing and acting upon risk information (Fakhruddin, Reinen-Hamill, & Murray, 2017). It also allows data to be shared across all agencies to help ensure a more efficient and prioritised response. Once the response is over, risk interpretation, with standardized loss data, can also provide loss-forecasting data in referencing historical loss modelling (Fakhruddin, Reinen-Hamill, & Murray, 2017).
3.   Methodology
The following outlines the three steps that went into building the rapid disaster map and creating the online Kaikoura Earthquake Viewer (KEV).
3.1   Field Reconnaissance
The image to the left of the page provides an overview of the timeline for 48 hours after the initial earthquake. The earthquake occurred at 12.02 am. By 10.00 am that same morning, the first land damage reconnaissance teams left Christchurch, Nelson and Wellington to undertake initial ground-based surveys. T+TI’s initial focus was on observing that damage along the transport corridors. Staff travelled in vehicles along key New Zealand Transport (NZTA) and railway routes (where possible) to observe the extent of the damage. Georeferenced images captured the location and extent of damage along SH1 including landslips, fault ruptures and some damage to residential and commercial infrastructure.
An hour later at 11.00 am T+TI natural hazards rapid disaster mapping responders flew out of Christchurch, Nelson and Wellington to undertake an aerial survey for New Zealand’s natural disaster insurer of residential land and buildings, the Earthquake Commission (EQC). This allowed a large area to be covered with the same process as the ground based survey where georeferenced photos could be uploaded online to provide information on the extent of the damage.
T+TI also used a collaborative data collection approach where geospatial data was compiled from a range of sources and reconnaissance surveys (both ground and aerial). Data was gathered from various agencies such as Red Cross and universities, and was regularly updated online as more information became available. The public was also encouraged to add their own photos and observations to the online portal. This resulted in constantly evolving data sets, offering improved accuracy over time and subsequently the best outcome for all involved. The overall timelines are shown in the Figure 3-1.


Figure 3-1   Earthquake damage mapping timelines
3.2   GIS Kaikoura Earthquake Viewer
The data gathered was then uploaded onto an online Project Orbit portal set up by T+TI. Georeferenced images could be opened online so users could view the extent of the damage and locate exactly where the damage had occurred. Scientific information was also uploaded such as landslide models and locations of where faults had ruptured and other topographic information showing magnitude of land movement and ground shaking. The building portfolio was also overlaid to get an indication of the number of buildings likely to be affected by different levels of shaking, liquefaction, landslides and fault rupture. As one of T+TI’s primary clients, understanding the damage to residential buildings was a focus of the T+TI reconnaissance surveys and was therefore able to inform the insurance assessment response for the EQC. By 2.30pm the same day, the Kaikoura Earthquake Viewer had been established and all data collected was able to be uploaded directly online into a central data repository.
3.3   Satellite Data
Roughly a week after the initial earthquake, the CODATA Task Group of Linked Open Data for Global Disaster Risk Research (LODGD) organized ChinaGEOSS portal to access TripleSat and JL-1 satellite images. These satellite images were then also uploaded to the KEV.
4.   Results and Discussions
The collaborative and centralised approach that T+TI carried out resulted in a relatively quick and prioritised response for all emergency services and agencies involved. As all data that had been directly uploaded into one place, by 4.55pm on the 16th of November, TATI was able to provide the first official briefing report to the EQC. This report gave an indication of the expected and actual damage that had been observed. EQC was then able to brief the then Prime Minister John Key and other government officials within the National Crisis Management Centre (NCMC) in Wellington to develop a prioritised and effective response.
At 7.00pm on Tuesday 15th November, the Kaikoura Earthquake Viewer (KEV) was released to the National Crisis Management Centre (NCMC), the Ministry of Civil Defence and Emergency Management (MCDEM) and all other response agencies. The KEV provided a clear picture of the extent of the damage and allowed emergency responders to prioritise areas that were worst hit. This significantly increased the ability for all to work collaboratively across the sector and subsequently provided the best service to those who had been affected the most.
The TripleSat and JL-1 images received from the ChinaGEOSS were focused on affected areas that were obscured by cloud cover after the earthquake (T+TI, 2017). This augmented the pre-existing satellite images and allowed gaps to be filled in the damage mapping process. The satellite images also provided valuable information that could confirm the extent of the damage across the top of the South Island and aided in improved modelling of shaking induced landslips.
5.   Conclusions
The Kaikoura earthquake is now described by experts as “the most complex earthquake ever studied” and continues to redefine scientific understanding of earthquake processes (NASA, 2017). Critically, the Hurunui-Kaikoura event has also served to highlight the immense value of international cooperation following natural disasters, not only on a local level, but also in terms of international research and understanding (T+TI, 2017). The Kaikoura GIS Viewer – created using T+T’s proprietary ProjectOrbit software – has since attracted global interest and has highlighted the efficiency centralised data repositories can create when responding to significant natural disaster events.
Acknowledgments
Lindy Andrews – formatting and editing report
Bain, S. (2014, March 20). New Zeland Geology: A Brief Overview. Retrieved from Leapfrog: http://blog.leapfrog3d.com/2014/03/20/new-zealand-geology-a-brief-overview/.
Castelltort, S., Goren, L., Willett, D. S., Champagnac, J.-D., Herman, F., & Braun, J. (2012). River drainage patterns in the New Zealand Alps primarily controlled by plate tectonic strain. Nature Geoscience. doi:DOI: 10.1038/NGEO1582.
Dell’Acqua, F., Bignami, C., & Chini, M. (2011). Earthquake damages rapid mapping by satellite remote sensing data: L’Aquila April 6th, 2009 event.
Fakhruddin, B., Murray, V., & Maini, R. (2017). Disaster loss data in monitoring the implementation of the Sendai Framework. International Council for Science, IRDR.Fakhruddin, B., Reinen-Hamill, R., & Murray, V. (2017). Disaster Loss Data: Raising the Standard.
GNS. (2016). Landslides and Landslide dams caused by the Kaikoura Earthquake. Retrieved from GeoNet Geological hazard information for New Zealand: https://www.geonet.org.nz/landslide/dam.
GNS. (2016). M 7.8 Kaikōura Mon, Nov 14 2016. Retrieved from GeoNet Geological hazard information for New Zealand: https://www.geonet.org.nz/earthquake/2016p858000
NASA. (2017, March 23). Study of Complex 2016 Quake May Alter Hazard Models. Retrieved from NASA Jet Propulsions Laboratory: https://www.jpl.nasa.gov/news/news.php?feature=6790.
Robinson, T. R., & Davies, T. R. (2013). Review Article: Potential geomorphic consequences of a future great (Mw = 8.0+) Alpine Fault earthquake, South Island, New Zealand. Natural Hazards Earth Systems Science, 2279–2299. doi:10.5194/nhess-13-2279-2013.
Saito, K., & Spence, R. (2004). Rapid damage mapping to support post-disaster recovery.
T+TI. (2016). Kaikoura Earthquake Viewer. Retrieved from https://kev.projectorbit.com/#.
T+TI. (2017, June 26). Kaikoura earthquake rapid disaster mapping. Retrieved from Tonkin + Taylor: https://www.tonkintaylor.co.nz/news/2017/6/kaikoura-earthquake-rapid-disaster-mapping/.
Wilson, C. K., Jones, C. H., Molnar, P., Sheehan, A. F., & Boyd, O. S. (2004). Distributed deformation in the lower crust and upper mantle beneath a continental strike-slip fault zone: Marlborough fault system, South Island, New Zealand. Geology, 32(10), 837–840. doi:10.1130/G20657.1.
Data citation
Bapon Fakhruddin, Li Guoqing, Rebekah Robertson. Rapid Damage Mapping and Loss Data Collection for Natural Disasters - Case Study from Kaikoura Earthquake, New Zealand. Science Data Bank, 2018. (2018-05-21). DOI:10.11922/sciencedb.605.
稿件与作者信息
How to cite this article
Bapon Fakhruddin, Li Guoqing, Rebekah Robertson. Rapid Damage Mapping and Loss Data Collection for Natural Disasters - Case Study from Kaikoura Earthquake, New Zealand. China Scientific Data, 2018. (2018-06-14). DOI: 10.11922/csdata.2018.0033.en (under review).
Bapon Fakhruddin
Contributed in writing the report and developing Rapid Mapping Method.
BFakhruddin@tonkintaylor.co.nz
PhD in Water Engineering. An international disaster risk reduction and hazard modeling expert who is a regular adviser to the United Nations on Natural Hazards and Climate Change.
Li Guoqing
Contributed to provide satellite data collection.
Professor and Head, Institute of Remote Sensing and Digital Earth, CAS, China.
Rebekah Robertson
Contribution involved writing the report.
Master’s in Disaster Risk and Resilience, research area includes disaster risk and resilience and natural hazard mapping and risk assessment.
出版历史
I区发布时间:2018年7月4日 ( 版本EN2
参考文献列表中查看
中国科学数据
csdata