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Presentation on how ArcGIS was used to perform an in-depth analysis of the height of regional dikes of HH Rijnland using AHN2 (LiDAR) data.
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AHN2 2010 – interpolated
AHN2 2008 – interpolated
AHN2 2008 – not interpolated
Location of dikes
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AHN2 dataset consists of over 7 billion pixels ( 30GB)
Querying the pixels values becomes slower when the size of the raster increments
There are 1212 km of dike, every 0.5m 11 pixels are queried ( 27 million points) and evaluated against 2 reference heights
For each point on a dike there should be al least a length of 1.5m connected within a class
No standard tools available for this specific task
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Merge AHN2 tiles to 1 raster dataset
loop through dikes
fetch height every 0.5m
evaluate against two reference heights (A and B)
AHN2<B or B<=AHN2<A or AHN2>=A or NoData
Combine points with same class together to form a line
next point on dike
next dike
(repeat validation
for reference heights C and D) > 1.5m, it does
meet the criteria
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For each class (AHN2<B, B<=AHN2<A, AHN2>=A) register the number of consecutive points that fall inside that class
The highest class with at least 3 consecutive points is assigned
In the example below the resulting class is B<=AHN2<A, based on points 4 to 9 which are higher that B, but not all above A (the lower limit of a class is used for validation)
B
A
Dike center1
2
3
4 5
6 7
8 9
10 11
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7
Class
Point >= A
B <= Point < A
Point < B
NoData
8
Class
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData
9
Class
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData
10
Class
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData
11
More than 1.5m, AHN2 > A AHN2 < B
Insufficient data, less than 70% NoData,
but no 3 consecutive points with data
More than 70% NoData
More than 1.5m, B <= AHN2 < A
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Correct method of processing solitary points
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AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData
14
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData
AHN2 >= A
B <= AHN2 < A
Bmin10 <= AHN2 < B
Bmin20 <= AHN2 < Bmin10
Bmin30 <= AHN2 < Bmin20
Bmin40 <= AHN2 < Bmin30
AHN2 < Bmin40
Insufficient data
NoData
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Calculate percentage of total length per class per dike
Sums 100%
Explanation of the column names:
“KL” stands for class
“X” represents AHN2 value
“lt” is less than “<“
“le” is less equal “<=“
“ge” is greater equal “>=“
So “KL_BleXltA” means:
Class where B <= AHN2 < A
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Percentage per class (based on A and B) Percentage per class (based on C and D)
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The 1212 km of dike has been processed into classified points and lines and additionally aggregated per dike
Processing time has been reduced to 12 minutes for the entire area based on the 30 GB raster.
For each point information about:
%NoData (indicates reliability)
elevation (min, max, mean)
classification
For each polyline information about:
elevation (min, max, mean)
classification
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After the height test, the results were combined with known instabilities and observations from previous research and fieldwork, in order to derive those locations with the highest priority.
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indicating the percentage of a dike with sufficient stability to safeguard the surrounding area
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indicating the amount of lacking height to safeguard the surrounding area
Sufficient heightHeight shortage between 0 and 10 cmHeight shortage between 10 and 20 cm
Height shortage between 20 and 30 cmHeight shortage more than 30 cmNoData
Insufficient data to quantify
Xander Bakker
Senior GIS Advisor
Grontmij Netherlands BV :: GIS & ICT – GIS Team :: http://www.Grontmij.com :: +31 30 220 79 11
http://twitter.com/#!/XanderBakker
http://nl.linkedin.com/in/xanderbakker
Xander [DOT] Bakker [AT] Grontmij [DOT] NL
http://software.grontmij.nl
