Initial release: 22 May 2019
Over the past few years we have been active developing site-level flood risk analytics tools, e.g.
– Introducing Three New Tools for Investigating Flood-prone Areas (link, 11/2017)
– Advancing Flood Risk Analytics with Location Profile APIs (link, 09/2018)
Now we are pleased to release two additional new tools as part of our ongoing significant effort to improve the accuracy, transparency and accessibility of underling hazard risk information.
1. High-resolution Tiled Web Maps on Elevation Contours, Modelled Surface Water Flow Directions and Shaded Relief
1.1 From Raw Data to Tile Maps: Elevation data is the most important input to model flood risk. Flood maps, often presented in an abstract form, can be greatly enhanced with some measured contextual layers derived from elevation, such as contours, modelled surface water flow directions and shaded relief. Thanks to the Geoscience Australia’s Elevation Information System (ELVIS), ~75% of populated areas in Australia are now covered with LiDAR-derived DTMs. We adopt this popular open dataset to make high-resolution elevation-specific contextual layers.
The main challenge of the project was to efficiently scale up the production of high-resolution contextual layers from a small area to a national coverage (e.g. from a single map tile to tens of millions of map tiles). Initial thought was that the data size might be a major hurdle (e.g. the data size for a single region at high resolutions could easily exceed 100 GB, much larger than that of the national dataset at 30m-resolution), but it turns out pre-processing the ELVIS data to a clean format that the project needs is painstakingly slow. Some issues (e.g. edges and gaps) of the merged ELVIS data, 5m-resolution DTM mosaics directly downloaded from GA, are illustrated in this figure. We have undertaken five major revisions involving treatments (e.g. updates with 1m-resolution elevation if available at ELVIS, masking, and exclusion of questionable patches) for more than 150 scattered areas. If one deals with a small area, such issues may not be obvious.
Figure 1 shows a list of newly developed tile maps (with XYZ Tiles convention). Figures 2, 3 and 4 are examples of the tile map on contours, flow directions and shaded relief, in an web app environment. As the original LiDAR data for the 5m-resolution DTM has a vertical accuracy of at least 0.3m (95% confidence), the choice of a contour interval of 2m may be conservative. Zoom levels shown in Figure 1 are those currently rendered as a minimum set and have been expanded constantly. For each tile map, we have explored various analysis and mapping techniques in order to present features both physically meaningful and cartographically clear.
Figure 1: New tiled web maps on elevation contours, modelled surface water flow directions and shaded relief.
Figure 2: Example of the new tile map (Hawkesbury River, NSW; Zoom level 17 displayed)
Figure 3: Example of the new tile map (Brisbane River, QLD; Zoom level 18 displayed)
Figure 4: Example of the new tile map (Stanwell Park, NSW; Zoom level 15 displayed)
More examples:
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Fitzroy River, Rockhampton, QLD (link)
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Queanbeyan River, Queanbeyan, NSW (link)
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Huon River, Huonville, TAS (link)
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Swan River, Perth, WA (link)
The following feedback is received from one of the reviewers of the new tile maps:
“I’ll never look at flood maps the same way again…”