PerilAUS II - Relative Risk Ratings for Postcodes and CRESTA/ICA Zones

Slides:



Advertisements
Similar presentations
Alternative schemes for representing numerical magnitude: A. Barcode magnitude representation (Viscuso et al., 1989; Anderson et al., 1994; McCloskey &
Advertisements

Vulnarability in Relation to Risk Management Sebnem Düzgün Middle East Technical University, Ankara, Turkey
Patient information extraction in digitized X-ray imagery Hsien-Huang P. Wu Department of Electrical Engineering, National Yunlin University of Science.
GPS & GIS – An Introduction. Where Will This Take Us? What is GPS? What is GIS? How do GPS and GIS work? How will they help us? ? Find This!
Please single mouse click to move to next slide. 3 year project funded by the Insurance Council of Australia Database of natural perils in Australia 1900.
Digital Vulnerability Atlas of South Asia
Millennium Ecosystem Assessment Northern Australia floodplain and coastal wetlands Max Finlayson National Centre for Tropical Wetland Research Darwin,
Graphing Linear Inequalities in Two Variables
Soil Information Working Group (SIWG) ESBN Plenary, London, 2005 Identifying Risk Areas for Landslides Florence Carre (JRC, Subgroup leader), D. Seebach,
Project Natural and Technological Hazards in Europe Philipp Schmidt-Thomé
A survey of geo-spatial data needs Barbara Morris Digimap.Plus Project Officer.
Safe Schools for Our Students Its the best investment youll ever make! Douglas C. Dougherty, Ph.D. Superintendent of Seaside School District.
Lessons Learned from a Low-Slope Roof System LCA Project Dr. James L. Hoff, DBA TEGNOS Research, Inc. Prepared for ASTM E-60 Workshop on.
Analysis grid superimposed 2D Street Grid Calculating Travel-Time …vector to raster conversion Note that a 100 row by 100 column analysis grid (10,000.
AgroCLIM software tool for effective calculation of agrometeorological indices ADAGIO & COST 734 Miroslav Trnka, Petr Hlavinka, Jan Balek, Josef Eitzinger,
Money Math Review.
Risk Information Issues and Needs: An Overview Synthesis paper as an output of the First Technical Workshop on Standards for Hazard Monitoring, Databases,
2 nd WORKSHOP OF THE NATO SfP PROJECT “Improvements in the Harmonized Seismic Hazard Maps for the Western Balkan Countries” April 25-26, 2013 Belgrade,
GIS IN GEOLOGY Miloš Marjanović Lesson
S tatistics Processing in ITU Esperanza C. Magpantay Telecommunication Data and Statistics Unit (TDS) Telecommunication Development Bureau.
Geospatial Issues update CR GIS survey summary (most slides on this) SBW polygons white paper NGWT geospatial element Flood map inundation NSTEP training.
Hydraulic parameterization of 3D subsurface models: from measurement-scale to model-scale Jan L. Gunnink, Jan Stafleu, Denise Maljers and Jan Hummelman.
Climate Change Vulnerability in Jakarta Dr. Armi Susandi, MT. Bandung Institute of Technology National Council on Climate Change Republic of Indonesia.
CFR 250/590 Introduction to GIS, Autumn 1999 Data Search & Import © Phil Hurvitz, find_data 1  Overview Web search engines NSDI GeoSpatial Data.
Wavelets Fast Multiresolution Image Querying Jacobs et.al. SIGGRAPH95.
FEMA Higher Education Conference June 2011 GIS in Emergency Management.
Raster Based GIS Analysis
590 Lipoa Parkway, Suite 259 Kihei, Maui, Hawaii (Fax) Pacific Disaster Center.
Geographic Information Systems
CS 128/ES Lecture 5a1 Raster Formats (II). CS 128/ES Lecture 5a2 Spatial modeling in raster format  Basic entity is the cell  Region represented.
Conclusions, planning and prospects Follow-up committee meeting 6 October, Leuven.
Geographic Information Systems. What is a Geographic Information System (GIS)? A GIS is a particular form of Information System applied to geographical.
CS 128/ES Lecture 5a1 Working with Rasters.
CS 128/ES Lecture 5a1 Raster Formats (II). CS 128/ES Lecture 5a2 Spatial modeling in raster format  Basic entity is the cell  Region represented.
1 What is the Richter Scale? How large is a large earthquake? How is earthquake size measured? Earthquake Magnitude Module LRW-1 Prepared for SSAC by Laura.
Spatial data Visualization spatial data Ruslan Bobov
Module 2.1 Monitoring activity data for forests using remote sensing REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 1 Module.
Foster and sustain the environmental and economic well being of the coast by linking people, information, and technology. Center Mission Coastal Hazards.
Title: Spatial Data Mining in Geo-Business. Overview  Twisting the Perspective of Map Surfaces — describes the character of spatial distributions through.
1 Multi-Criteria Evaluation for Desertification assessment and Mapping A GIS and remote sensing Application Dr. Hussein Harahsheh.
OHRI towards an Open Humanitarian Risk Index A comprehensive, widely-accepted and open evidence base with which to reach common understanding and coordinated.
Training course on biodiversity data publishing and fitness-for-use in the GBIF Network, 2011 edition Tools and Resources to Assess and Enhance Fitness-For-Use.
How do we represent the world in a GIS database?
Advanced Topics in GIS. Natural Hazards Landslide Susceptibility.
قسم الجيوماتكس Geomatics Department King AbdulAziz University Faculty of Environmental Design GIS Components GIS Fundamentals GEOM 121 Reda Yaagoubi, Ph.D.
Assessing Natural Hazard Risk in Urban Areas Henrike Brecht Louisiana State University Emergency Management Higher Education Conference, June 7, 2007.
Role of Spatial Database in Biodiversity Conservation Planning Sham Davande, GIS Expert Arid Communities Technologies, Bhuj 11 September, 2015.
International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 RiskCity Exercise: Spatial Multi Criteria Evaluation for Vulnerability.
1 Establishing standardized National Disaster Loss Databases IAP Meeting September 2011.
Hazards, Vulnerability, and Mitigation Sub-Committee.
Raster Data Models: Data Compression Why? –Save disk space by reducing information content –Methods Run-length codes Raster chain codes Block codes Quadtrees.
Spatial Data Models Geography is concerned with many aspects of our environment. From a GIS perspective, we can identify two aspects which are of particular.
Developing a Spatial Hazard Index Methodology Using ModelBuilder Joe Ludwig Geography 596A January 6, 2009 Advisor: Dr. Todd Bacastow Photo Source: NOAA.
WFM 6202: Remote Sensing and GIS in Water Management © Dr. Akm Saiful IslamDr. Akm Saiful Islam WFM 6202: Remote Sensing and GIS in Water Management Dr.
Czech Technical University in Prague Faculty of Transportation Sciences Department of Transport Telematics Doc. Ing. Pavel Hrubeš, Ph.D. Geographical Information.
DISASTER MANAGEMENT AND MITIGATION: AN ENGINEER’S PERSPECTIVE SHUBHI JAIN B.E. 4 th YEAR (e.c.) G.G.I.T.S. JABALPUR.
But how reliable are these statistics?
GEOGRAPHICAL INFORMATION SYSTEM
Actuaries Climate Index™
The Index and Payment Solutions of Typhoon Index Insurance for Rubber Trees in Hainan Province of China Xinli Liu1, Tao Ye2, Jing Dong1 , Miluo Yi2, Shuyi.
Overview of Downscaling
Change in Flood Risk across Canada under Changing Climate
Actuaries Climate Index™
Statistical Analysis with Excel
Statistical Analysis with Excel
Effect of Earthquake on Fire Protection Systems
GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for LA County The threat of global warming has caused.
Igor Appel Alexander Kokhanovsky
An Asia Pacific Natural Hazards and Vulnerabilities Atlas
Generation of Historical Vulnerability Indices using a DesInventar Database Julio Serje, Deepa Chavali and Sujit Mohanty.
Presentation transcript:

PerilAUS II - Relative Risk Ratings for Postcodes and CRESTA/ICA Zones Part 1: Methodology Part 2: CD-ROM

Background PerilAUS I CD-ROM (released in October 1999) Most comprehensive collection of natural perils data 1900-1999 Searchable database with geo-spatial mapping software 9 perils 5,000 events and 10,000 affected locations PerilAUS II CD-ROM (release in January 2001) Relative Risk Ratings (RRR) 2,573 postcodes 49 CRESTA/ICA Zones PerilAUS I historical data + additional natural hazards potential Main concern: Damage to buildings Approach: Multi-Criteria Evaluation (MCE)-GIS

Geographical scales Global States ICA zones Balaclava Road Individual dwellings Postcodes Street blocks RRR of PerilAUS II deal with two geographical scales: ICA zones and Postcodes

Part 1 - Methodology (PerilAUS II) Historical data from PerilAUS I Potential hazards data Step 1 Step 2 Step 3 Damage index Future perspective Normalisation of scales for each peril Global weighting Peril-by-peril (W1, W2, …, W9) Normalisation of scales for each peril Combination (historical) Combination (potential) Final RRR

Step 1: Historical data from PerilAUS I (e.g. earthquake) Earthquake MM intensity scale for 1448 affected locations Number of affected locations: Bushfire: 941 Earthquake: 1448 Flood: 990 Gust: 1763 Hail: 2984 Landslide: 278 Tornado: 712 T. Cyclone: 877 Tsunami: 74 Total: 10067

Affected locations are overlaid with postcode boundaries For each peril, at a postcode level:  The number of affected locations;  Magnitude or intensity;  Frequency.

Potential hazards data (e.g. bushfire) Six base maps: Bushfire Earthquake Gust Hail T. Cyclone Tsunami Derivative maps: buffering zones of historical affected locations: Flood Landslide Tornado Bushfire Potential Source: Johnson et al., (1995). Natural Hazards: their Potential in the Pacific Southwest.

Potential regions are overlaid with postcode boundaries Medium Low Potential magnitude for the green postcode = Areal averaging (“Low”, “Medium”) Nine potential maps are converted into raster images with the same scale and same coordinate system: Size: 2250 pixels (W-E)  2000 pixels (N-S) Resolution: 2 km Low Medium

Step 2: Normalisation Conversion: linguistic terms  fuzzy sets  crisp values A numerical approximation system by Chen, S.J. and Hwang, C.L. (1992) with 8 conversion scales. 7th scale contains 9 linguistic terms (left). 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 X Very low Very high High-V. high V. low-low Low Medium High Low-medium Medium-high e.g., Bushfire potential with 5 scales

Weighting Weighting is to express the relative importance between 9 perils, in terms of damage to buildings (historical and potential) Four sub-factors were assessed using Analytical Hierarchy Process (AHP). The final relative weight for each peril uses their average.

Step 3: Combinations Weighted Linear Combination (WLC)-GIS was used, with five advantages (for details, refer to the PerilAUS II report) (1) Historical component: (2) Potential component: (3) RRR = 30%  (Historical) + 70%  (Potential) Finally, a series of composite maps and spreadsheets at a postcode level and at a CRESTA/ICA zone level are produced.

Results e.g. RRR at an ICA Zone level

RRR spreadsheet at a postcode level Results (contd.) RRR spreadsheet at a postcode level RRR are comparable and serve as “risk meters”, allowing arithmetic calculations. (1) Peril-by-peril (horizontally): Which peril is the most significant? Sub-total risk ratings for perils selected (2) Postcode-by-postcode (vertically): individually (9 perils) and collectively minimum, maximum, average values for easy comparisons Relative standings (taking the right-hand column “Total” as example, go next slide)

Distribution of RRR “Total” at a postcode level: Results (contd.) Distribution of RRR “Total” at a postcode level: For the Postcode 800, 98.9% of all 2,573 postcodes have RRR less than 119.3; or only 1.1% of all postcodes have RRR larger than 119.3. In this way, a RRR relative standing spreadsheet can be produced (go next page). e.g. 119.3 (Postcode 800, Darwin) 98.9%

New RRR relative standing spreadsheet at a postcode level Results (contd.) (previous) RRR spreadsheet at a postcode level New RRR relative standing spreadsheet at a postcode level

Results (contd.) Based on the calculated RRR, while the first three most damaging perils remain the same, RRR values for hails and tornadoes are higher than those from the previous 100 years. Tropical Cyclone Flood Bushfire Gust Hail Quake Tornado Landslide Tsunami

Part 2: PerilAUS II CD-ROM includes: Spreadsheets (4): RRR at a postcode level (70 pages) Relative standing of RRR at a postcode level (70 pages) RRR at a CRESTA/ICA zone level Relative standing of RRR at a CRESTA/ICA zone level Input maps (18): Historical maps (9) Potential maps (9) Output composite maps (6): Historical composite map at a postcode level Potential composite map at a postcode level Final RRR map at a postcode level Historical composite map at a CRESTA/ICA zone level Potential composite map at a CRESTA/ICA zone level Final RRR map at a CRESTA/ICA zone level Report

PerilAUS II CD-ROM Spreadsheets are provided in .pdf, Excel 97, Access 97 formats Report and maps are provided in .pdf and Word 97 formats - printable, editable, easy data manipulation and conversions

Spreadsheets - PerilAUS II CD-ROM East to browse and locate a postcode using left-pane indexes Summary given at bottom of each page facilitates comparisons

Maps - PerilAUS II CD-ROM East to browse and locate a map using left-pane indexes

Report - RRR of PerilAUS II Detailed methodology and procedures of the RRR development are given in a report

Natural Hazards Research Centre Thank you for viewing the PerilAUS II Demo. To place an order or for more information, please contact: Natural Hazards Research Centre Telephone: +61-2-9850 9683 Fax: +61-2-9850 9394 Email: nhrc@ocs1.ocs.mq.edu.au