Characterizing regional dikes with LiDAR using ArcGIS 10 by Grontmij
2For those seeking presentations on #LiDAR analysis based onpoint clouds; you will not find it in this presentation.This presentation is about the analysis of raster data, derivedfrom LiDAR data, that has been created specifically for theWater Boards in the Netherlands (bare earth, 0.5 m resolution).
3 About two thirds of the Netherlands is vulnerable to flooding 1953 North Sea flood; 9% of total Dutch farmland flooded, 1835 peoplekilled, 30000 animals drowned, 47300 buildings damaged Long history of reclamation of marshes and fenland, resulting insome 3,000 polders There are about 14.000 km of regional dikes in the NetherlandsSources: Wikipedia, Flood control in the Netherlands Wikipedia, North Sea flood of 1953 Wikipedia, Polders and the Netherlands Deltawerken online Waternet, Flood control and protection
4 Determination of dike top height for five-year legal assessment Determination of dike strength on representative profiles Mapping of primary and regional dikes and embankmentsDoing that manually is a time consuming effort …… the alternative is using GIS and LiDAR data
5 (Up-to-date Height Model of the Netherlands) AHN is funded by the Directorate General forPublic Works and Water Management of theDutch Government and the 26 Regional WaterBoards The main purpose of AHN is to get a highlydetailed representation of the bare earth.Objects (houses, trees, etc.) are filtered. Available Spring 2012 Source: Spring 2013 AHN website, availability of AHN2 (Dutch)
6 Managing more than 600 km of regional dike in the Northernpart of NL and about 66 km of sea dikes.
7 Pre-process AHN2 data Correct location of the dike based on AHN2 Divide line representing the dike in parts of 100m Determine the lowest point per 100m (H100Min) Create cross profile AHN2 on each H100Min Analyze standard profiles Determine maximum width Bmax Determine the design profile Iteration to correct profiles
8 Necessary to filter outliers Choose filter small to avoid puling the initial dike track away fromthe water -> use a Focal mean 3x3 Fill up small areas with NoData Unfiltered Filtered
9 Step size interval on centerline (10m) Maximum search tolerance (5m) Evaluate several methods: Without step size and search tolerance Search highest point in original AHN2 Search highest point in filtered AHN2 Determine highest point weighted by distance from centerline and using a minimal increment (e.g., 2cm/m) Correct original centerline to create a new centerline basedon the elevation data.
10 Influence of rising “hinterland” at small dikes, pulling the lineaway from the actual dike 1 Small outliers can create large errors 2 Resulting centerline is less gradually 3 1 2 3
11 Influence of rising “hinterland” at small dikes remains 1 Small outliers are removed 2 Resulting centerline is a bit more gradually 3 1 2 3
12 Influence of rising “hinterland” at small dikes is less apparent 1 Result looks better, but… creates new inconsistencies 2 2 1
13 Alternative: determine the maximum deviation of twoconsecutive points (exclude red point, see 1 ) Incorrect position of the centerline will have consequences 1
14 The corrected centerline is divided into parts of 100m. When apart is smaller than 50m it is added to the previous part. Gather statistics per part(min, max, mean, etc)
15 For each part the location of the lowest point H100Min isdetermined
16 On each H100Min location a cross profile is drawn (100m) Step size (precision) is pixel size of AHN2 (0.5m) Store as XYZ and dZ (=distance vs. elevation) lines
17 Distance d (horizontally) versus Z (vertically) Z (* factor 5) L R Distance from H100min (d)H100minFirst NoData L and R from H100min Classic example of a centerline that doesn’t follow the highest part of the dike and causes the H100min to be located to low.
18 4 standard trapezoid profiles are fitted at the highest positioncentered underneath the H100min point Exaggeration Z-axis is factor 5 4 standard trapezoid profiles defined by widths 1m and 2m versus slopes 1:1.5 and 1:2
19 The highest trapezoid profile is selected. When more than 1profile have the highest position, the widest is chosen. If more than 1 option remains, the one with the slightestinclination is chosen. Exaggeration Z-axis is factor 5
20 Try to extent the best standard trapezoid profile bydetermining the maximum width Bmax at that height. Exaggeration Z-axis is factor 5
21 Over 6000 locations have been processed In about 1300 locations the results were different than expected,due to errors in the location of the original dike line In the second part of the project, code was developed to correctthese situations Dike is here Dike is NOT here
22 Does not have to be centered at H100min Should not cross NoData (probably water) After Should limit search to 5 meter L and R iterations H100min Last point Last point before NoData before NoData on right side on left side Standard trapezoid L1 before iteration
23 All 4 standard trapezoids should be evaluated Best option is selected
24 Bmax is determined for new location of best trapezoid H100min Max search tolerance 5m Bmax of best standard trapezoid Best standard trapezoid after iteration
25 Z 3D view of a location: X Y First result before correction Second result after correction with better position
26 Water Board Noorderzijlvest is using these results to fill theirdatabase, fieldwork would have required many months more. Relatively large datasets can be used for this analysis (a rasterdataset of 40Gb was used, but can be much bigger too) Process is flexible and can be used for any Water Board Generation of centerline should be done implementing thetechniques developed for iteration of the standard trapezoids Centerline should have correct position or the results will notbe reliable ArcGIS 10.1 beta 2 was used for this analysis, but ArcGIS 10.0 or 9.3.x can be used as well.