Coastal Urban DEM project - Mapping the vulnerability of Australia's Coast
- 1. The Coastal Urban DEM Project Mapping the Vulnerability of Australia’s Coasts Phil Tickle and Nathan Quadros Cooperative Research Centre for Spatial information Better data for improved decision making
- 2. Background, national scale: • Since 1990, observed sea level rise of >3mm per year corresponds to upper limit of IPCC projections • Science indicates greater than predicted sea level rise of potentially >1m by 2100 • Australia has 25,700km of coastline • Increased frequency and intensity of storms • 80% of population lives in the coastal zone; 85% within 50km of coast; 25% within 3km
- 3. Context: Commonwealth Department of Climate Change Addressing capacity gaps to support risk assessment & adaptation ─ High resolution elevation data acquisition and distribution ─ Coastal Landform database – mapping coastal stability ─ National Storm surge modelling and event frequency ─ Mapping shoreline recession ─ Integrated coincident event modelling
- 4. Context: National Coastal Risk Assessment $226 B in commercial, industrial, road and rail, and residential assets are potentially exposed to inundation and erosion hazards at 1.1 m SLR (high end scenario for 2100). Assets at risk from impact of inundation and shoreline recession: – 5,800-8,600 commercial buildings @$58-81 B (2008 values) – 3,700-6,200 light industrial buildings @$4.2-6.7 B (2008 values) –27,000-35,000 km of roads and rail, @ $51-67 B (2008 values)
- 5. Local Level Implications • Decision support for planning rules, building restrictions, infrastructure & insurance rely upon vulnerability maps, which in turn rely upon DEMs • Decisions about future development, particularly in areas highly exposed to the impacts of climate change, should not increase risk. • Poor decisions as a consequence of DEMs of insufficient resolution can have significant economic and social impacts
- 6. Local Level Implications • Imperative issue in coastal environments is determining adaptation response to predicted sea-level rise • Associated vulnerability and risks need to be quantified and communicated to potentially affected populations • Topography is a key parameter and availability of DEMs becomes central to preparation of vulnerability maps & risk analysis • Too date, there’s been excessive reliance upon inundation scenarios built upon DEM data of insufficient resolution to support fine-scale differentiation of processes driving coastal change
- 7. Local Level Implications • Increased demand for infrastructure and service provision (more with less) • Changing demographic trends –pressures on coastal property values and coastal property development • Difficult to resource and retain coastal adaptation planning and management skills • Uncertain future liability
- 8. Background to the NEDF The potential impacts of rising sea levels was identified as a national priority by COAG in 2007 COAG also noted the need for a fit-for-purpose coastal DEM to assess the impacts of potential sea-level-rise. ANZLIC, DCCEE (then AGO), GA and the CRCSI engaged in a partnership to drive the development of the National Elevation Data Framework The Urban DEM Project aimed to deliver the initial phase of the NEDF
- 9. NEDF Strategies (2009-2011) Governance structures Mechanisms for funding which promote cost sharing, Technical standards which maximise the utility and interoperability of data Access, distribution and use arrangements Industry development and capacity building
- 10. The Urban Digital Elevation Modelling (UDEM) Project Played a major role in implementing the NEDF $8.1 million 2009-12 investment to underpin nationally consistent coastal risk assessments A focus on the issues of standards, licensing and governance outlined in the NEDF Strategic Plan
- 11. The Urban Digital Elevation Modelling (UDEM) Project Motivation: Policy makers need improved toolsets to quantitatively assess risks to infrastructure, communities and natural systems from coastal inundation & other impacts of climate change Scope: Begin implementation of the National Elevation Data Framework (NEDF) ─ generation of high resolution elevation data for key urban areas – High-resolution, 15cm accurate datasets Initial coverage of 8 major urban areas covering 20,000 km2 & >15 million population ─ Develop prototype interactive, web-based visualisation tools for sea level rise ─ Develop an online web portal for elevation data ─ Undertake necessary applied research
- 12. The Need for High Resolution Elevation Data Why use High resolution elevation data? Provides valuable information and visualisation capability to modellers and coastal decision makers Enables more accurate coastal analysis Enables the forecasting of inundation levels, visualisation of coastal change, establishment of shorelines When combined with other datasets, provides for more comprehensive scenarios (shoreline movement, storm surge, high astronomical tide levels, erosion, geomorphological analysis, asset risk etc ) The exposure of coastal assets is already widespread and will increase into the future. Exposure will also increase as the population grows.
- 13. The NEDF Portal National Elevation Data Framework Portal http://nedf.ga.gov.au
- 14. National Elevation Data Framework Portal
- 15. 2. National LiDAR Standards http://www.icsm.gov.au/icsm/elevation/index.html
- 16. 2. National LiDAR Standards New classification levels for LiDAR data LiDAR doesn’t always “see” the ground
- 17. Classification Levels Level Description C0 Unclassified Point Cloud. C1 Automated Classification. Ground Anomaly Removal. C2 These are major errors only, i.e. quickly and easily identifiable. C3 Manual Ground Correction C4 Full Classification
- 18. 3. Applied Research Project 1 – Performance of DEM generation technologies in coastal environments Project 2 – Integration of multi- resolution DEMs Project 3 – Vertical datum harmonisation across the littoral zone Project 4 - User requirements for bathymetric data collection Project 5 – The need for hydrological conditioning of DEMs
- 19. 3. Acquisition of over 60,000sqkm of LiDAR Around 60,000sqkm of LiDAR has been acquired for coastal vulnerability modelling ─ Original objective of 20,000sqkm ─ Partnerships made it possible Seamless LiDAR from Cooktown to Adelaide Seamless Coastal DEM being developed
- 20. 4. Communication Products Communication products have increased awareness across government, community and the private sector Maps highlight the potential impacts of different sea level rise scenarios ─ Three sea level rise scenarios relevant to a 2100 time period with a very high tide (eg king tide): low (50 cm sea level rise + HAT) medium (80 cm SLR + HAT) high (1.1m SLR + HAT)
- 21. 4. Communication Products available online via the OzCoasts website (www.ozcoasts.org.au) Publicly available information important –facilitates private sector and community engagement Three sea level rise scenarios relevant to a 2100 time period with a very high tide (eg king tide): low (50 cm sea level rise + HAT) medium (80 cm SLR + HAT) high (1.1m SLR + HAT) 300,000 downloads of maps 500,000 page views in the first month and 10,000-40,000 visits per month
- 24. Visualising sea level rise tool (VisTool) Available to governments (public good use) Being accessed by 150 local governments Based on high resolution elevation data (vertical accuracy +/- 10-15cm) Hydrologically conditioned – to better show how water will flow such as streams, stormwater drains Bucket fill modelling approach only - assumes calm ocean surface What information do decision makers need and how do they need to access it? Interactive tool that can be used to consider various futures of sea level rise Potential to add in other data layers eg national storm tide model data, landform stability data etc
- 27. Visualising sea level rise tool limitations does not provide guidance about flood risk from an extreme event, eg storm surge, influence of wind and waves etc does not consider landform structure (geomorphological factors), eg potential erosion does not model potential change to tidal flows does not take account of some existing sea walls and other protective structures, eg some flood mitigation structures does not take account of the effects of coincident catchment flooding from extreme rainfall events does not indicate depth of flooding
- 28. Other work Source: http://www.cawcr.gov.au/
- 31. Observations & Conclusions National level work to build capacity to understand risks (DEMs, storm tide models, shoreline erosion, sediments, wave modelling) Significant national analysis yet to occur re SLR and coincident storm events combined with hazard predictions (erosion, inundation extent) Understanding of ,and communication of, modelling outcomes has a way to go Differing adaptation options with differing costs = tools to assess costs and benefits options required
- 32. Observations & Conclusions On-ground experience in acquiring, processing and delivering high resolution elevation data has provided many insights relevant to key national information infrastructure projects (hardest first!) UDEM being used as a case study for ANZLIC Framework datasets In the space of 4 years the technology, how its processed, and the market has changed dramatically A coordinated and informed purchasing has had a significant impact on price and quality Coordination and Collaboration across all levels of government is the key to success
- 33. Observations & Conclusions On-going funding models for fundamental data are still problematic Public-private partnerships are yet to be fully explored USGS study has demonstrated a 4.3-4.9 benefit:cost ratio when a coordinated national approach is taken Despite “open-government” policies, existing cost-recovery models are limiting access to private and research sectors Appropriate access is critical to community awareness, changing risk and insurance
- 34. Acknowledgments
Editor's Notes
- #7: Findings are largely consistent with accuracy expectations Accuracy gap between LIDAR & IFSAR or ADS40 DEMs only a factor of 3 to 4 according to specs., but difference is accentuated in automated classification & filtering , espec. of vegetationLIDAR has significant advantages, not matched in vegetated areas by radar & photogrammetry, except through skill-intensive and expensive manual editing Systematic filtering errors can compromise integrity of bare-earth DEMs in low-lying vegetated & urbanised coastal areas; majority of the populated coastal regions of Australia fit this description Due to classification/filtering issues, and to a lesser extent differing vertical resolution, can conclude that LIDAR is preferred option for DEM generation in coastal regions vulnerable to sea level rise
- #8: Findings are largely consistent with accuracy expectations Accuracy gap between LIDAR & IFSAR or ADS40 DEMs only a factor of 3 to 4 according to specs., but difference is accentuated in automated classification & filtering , espec. of vegetationLIDAR has significant advantages, not matched in vegetated areas by radar & photogrammetry, except through skill-intensive and expensive manual editing Systematic filtering errors can compromise integrity of bare-earth DEMs in low-lying vegetated & urbanised coastal areas; majority of the populated coastal regions of Australia fit this description Due to classification/filtering issues, and to a lesser extent differing vertical resolution, can conclude that LIDAR is preferred option for DEM generation in coastal regions vulnerable to sea level rise
- #19: Nathan.Can you drop in a couple of slides from your presentation
- #20: By the the end of 2012, the majority of Australia’s developed coastline will have seamless Airborne LiDAR data suitable for systematically modelling the impacts of coastal inundation and flooding