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.

2. 2
 AHN2 2010 – interpolated
 AHN2 2008 – interpolated
 AHN2 2008 – not interpolated
 Location of dikes

3. 3
 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

4. 4
 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

5. 5
 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)
6 7
A
2 4 5
8 9
B
3 10 11
1
Dike center

6. 6

7. 7
Class
Point >= A
B <= Point < A
Point < B
NoData

8. 8
Class
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData

9. 9
Class
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData

10. 10
Class
AHN2 >= A
B <= AHN2 < A
AHN2 < B
Insufficient data
NoData

11. 11
More than 1.5m, AHN2 > A More than 70% NoData AHN2 < B
Insufficient data, less than 70% NoData, More than 1.5m, B <= AHN2 < A
but no 3 consecutive points with data

12. 12
Correct method of processing solitary points

13. 13
AHN2 >= A AHN2 >= A
B <= AHN2 < A B <= AHN2 < A
AHN2 < B AHN2 < B
Insufficient data Insufficient data
NoData NoData

14. 14
AHN2 >= A AHN2 >= A
B <= AHN2 < A B <= AHN2 < A
AHN2 < B Bmin10 <= AHN2 < B
Insufficient data Bmin20 <= AHN2 < Bmin10
NoData Bmin30 <= AHN2 < Bmin20
Bmin40 <= AHN2 < Bmin30
AHN2 < Bmin40
Insufficient data
NoData

15. 15

16. 16
 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

17. 17
Percentage per class (based on A and B) Percentage per class (based on C and D)

18. 18
 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

19. 19
 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.

20. 20
 indicating the percentage of a
dike with sufficient stability to
safeguard the surrounding area

21. 21
Sufficient height
Height shortage between 0 and 10 cm
Height shortage between 10 and 20 cm
Height shortage between 20 and 30 cm
 indicating the amount of lacking Height shortage more than 30 cm
NoData
height to safeguard the Insufficient data to quantify
surrounding area

22. http://twitter.com/#!/XanderBakker
http://nl.linkedin.com/in/xanderbakker
Xander Bakker
Senior GIS Advisor
Xander [DOT] Bakker [AT] Grontmij [DOT] NL
http://software.grontmij.nl
Grontmij Netherlands BV :: GIS & ICT – GIS Team :: http://www.Grontmij.com :: +31 30 220 79 11