McDougall, K. and Temple-Watts, P. (2012) The use of LiDAR and volunteered geographic information to map flood extents and inundation. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 1-4. pp. 251-256.
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Floods are one of the most destructive natural disasters that threaten communities and properties. In recent decades, flooding has claimed more lives, destroyed more houses and ruined more agricultural land than any other natural hazard. The accurate prediction of the areas of inundation from flooding is critical to saving lives and property, but relies heavily on accurate digital elevation and hydrologic models. The 2011 Brisbane floods provided a unique opportunity to capture high resolution digital aerial imagery as the floods neared their peak, allowing the capture of areas of inundation over the various city suburbs. This high quality imagery, together with accurate LiDAR data over the area and publically available volunteered geographic imagery through repositories such as Flickr, enabled the reconstruction of flood extents and the assessment of both area and depth of inundation for the assessment of damage. In this study, approximately 20 images of flood damaged properties were utilised to identify the peak of the flood. Accurate position and height values were determined through the use of RTK GPS and conventional survey methods. This information was then utilised in conjunction with river gauge information to generate a digital flood surface. The LiDAR generated DEM was then intersected with the flood surface to reconstruct the area of inundation. The model determined areas of inundation were then compared to the mapped flood extent from the high resolution digital imagery to assess the accuracy of the process. The paper concludes that accurate flood extent prediction or mapping is possible through this method, although its accuracy is dependent on the number and location of sampled points. The utilisation of LiDAR generated DEMs and DSMs can also provide an excellent mechanism to estimate depths of inundation and hence flood damage.
|Item Type:||Article (Commonwealth Reporting Category C)|
|Additional Information:||© Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 License. This is a peer reviewed journal.|
|Uncontrolled Keywords:||volunteered geographic information, LiDAR, flood mapping, spatial analysis|
|Depositing User:||Mr Kevin McDougall|
|Date Deposited:||31 Aug 2012 02:57|
|Last Modified:||03 Jul 2013 01:17|
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