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Geomatics and Water Resources Research Group Geomatics and Water Resources Research Group SeminarsSeminars
Autumn Term 2007Autumn Term 2007
Dr. Fernando J. Aguilar TorresDr. Fernando J. Aguilar Torres
Department of Agricultural Engineering, University of Almeria, SpainDepartment of Agricultural Engineering, University of Almeria, Spain
A METHODOLOGICAL PROPOSAL FOR ACCURACY ASSESSMENT A METHODOLOGICAL PROPOSAL FOR ACCURACY ASSESSMENT OF LIDAR DERIVED DIGITAL ELEVATION MODELSOF LIDAR DERIVED DIGITAL ELEVATION MODELS
Newcastle, September 2007
2
1.1. Introduction.Introduction.
2.2. Accuracy assessment of DEMs.Accuracy assessment of DEMs.
3.3. Reference Standards (official guidelines). Are they enough?Reference Standards (official guidelines). Are they enough?
4.4. Do we really know the reliability of our DEM accuracy measures?Do we really know the reliability of our DEM accuracy measures?
5.5. Our methodological proposal in the case of LiDAR derived DEMs.Our methodological proposal in the case of LiDAR derived DEMs.
6.6. Modelling LiDAR error. Preliminary results. Modelling LiDAR error. Preliminary results.
7.7. Conclusions.Conclusions.
ScheduleSchedule
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
3
1. 1. IntroductionIntroduction
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
DEM? What is a DEM?DEM? What is a DEM?
Z = f(x,y)
A DEM is a digital and mathematical representation of an existing or virtual terrain by means of storing the land elevations (void of vegetation and manmade features) usually at regularly spaced intervals in x and y directions.
4
1. 1. IntroductionIntroduction
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
DEM?DEM?
5
1. 1. IntroductionIntroduction
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Applications of DEMsApplications of DEMs
Hydrological and erosion modelsHydrological and erosion models Viewshed analysis and visual impactViewshed analysis and visual impact Flood risk analysisFlood risk analysis Planning of land development. Suitability models (GIS)Planning of land development. Suitability models (GIS) Civil Engineering (cut and fills calculation)Civil Engineering (cut and fills calculation) Relief description and geomorphology (slopes, aspects and so on)Relief description and geomorphology (slopes, aspects and so on) Topographic correction of remote sensing imagery, insolation and Topographic correction of remote sensing imagery, insolation and
shadowing modelsshadowing models 3D visualisation and virtual environments3D visualisation and virtual environments Orthoimages generationOrthoimages generation
6
1. 1. IntroductionIntroduction
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Orthoimages generationOrthoimages generation
2D environment 3D environment
7
OffNadir View Angle (degrees)
DE
M a
ccur
acy
(m)
RMSEortho (m)0.71.01.31.61.92.22.52.83.13.4
3 6 9 12 15 18 21 240123456789
10
1. 1. IntroductionIntroduction
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Error propagation from DEM to the final productError propagation from DEM to the final product
Aguilar et al. Annual International Conference ADM and INGEGRAF. Perugia, Italy, June 2007.
8
2. 2. Accuracy assessment of Accuracy assessment of DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Why?Why?
A responsible DEM user must be A responsible DEM user must be able to answer the following able to answer the following questions (planning):questions (planning):
What precisely is the application for What precisely is the application for the DEM?the DEM?
What type of DEM will best meet What type of DEM will best meet these needs?these needs?
How do I know that I am getting How do I know that I am getting what I ordered?what I ordered?
USER
PRODUCER
9
2. 2. Accuracy assessment of Accuracy assessment of DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
How to compute it? Statistical inference (Sampling How to compute it? Statistical inference (Sampling theory)theory)
Check points selection (finite sample N)
Differences between z DEM and z from an independent source of higher accuracy
RMSE and ME calculation
DEM quality evaluation
Check Points Error (ZDEMi -ZCPi = ei)
10
2. 2. Accuracy assessment of Accuracy assessment of DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Types of errorsTypes of errors
1.1. Blunders or OutliersBlunders or Outliers
2.2. Systematic (bias) errors (constant Systematic (bias) errors (constant offset) offset)
3.3. Random errors (random fluctuations Random errors (random fluctuations in the measurements)in the measurements)
11
2. 2. Accuracy assessment of Accuracy assessment of DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Types of errorsTypes of errors
• Systematic errors (A and B)
• Spatially autocorrelated errors (C)
• Random errors with no spatial autocorrelation (D)
P. Fisher and N. Tate, 2006. Causes and consequences of error in DEMs. Progress in Physical Geography 30(4): 467-489
Ground truth
DEM
12
3. 3. Reference StandardsReference Standards
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
National Standard for Spatial Data Accuracy (NSSDA, National Standard for Spatial Data Accuracy (NSSDA, US)US)
> 20%
> 20%
> 20%
> 20%
Federal Geographic Data Commitee U.S., 1998
Minimum distance between check points >0,10 diagonal
> 20 check points
Assumption of a normal distribution of residuals and the absence of systematic errors
13
3. 3. Reference StandardsReference Standards
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
National Standard for Spatial Data Accuracy (NSSDA, National Standard for Spatial Data Accuracy (NSSDA, US)US)
95% confidence level
Compiled to meet ...... meters vertical accuracy at 95% confidence level
Check points selection (finite sample N>20)
Differences between z DEM and z from an independent source of higher accuracy
RMSE calculationVertical accuracy = 1,96.RMSE
14
3. 3. Reference StandardsReference Standards
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
But is it enough? Some questions arise...But is it enough? Some questions arise...
It is assumed that residuals at check points follow a normal distribution and It is assumed that residuals at check points follow a normal distribution and systematic errors have been “reasonably” removed (no bias), which is known systematic errors have been “reasonably” removed (no bias), which is known as the “strong assumption”. as the “strong assumption”.
We need at least 20 check points. But it is supposing error normal We need at least 20 check points. But it is supposing error normal distribution. If not, how many check points do we need? 30, 50, maybe 100?distribution. If not, how many check points do we need? 30, 50, maybe 100?
Who controls the reliability of the accuracy
assessment process?
15
3. 3. Reference StandardsReference Standards
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
ASPRS Guidelines. Vertical accuracy reporting for ASPRS Guidelines. Vertical accuracy reporting for LiDARLiDAR
Non-open terrain
Non-open terrainOpen
terrain
Flood, M., 2004. http://www.asprs.org/society/divisions/ppd/standards/Lidar%20guidelines.pdf
Fundamental accuracy (NSSDA protocol)
Supplemental accuracy
16
3. 3. Reference StandardsReference Standards
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
ASPRS Guidelines. Supplemental accuracyASPRS Guidelines. Supplemental accuracy
Flood, M., 2004. http://www.asprs.org/society/divisions/ppd/standards/Lidar%20guidelines.pdf
Residuals
+
-
95th percentile = vertical accuracy at 95% confidence level
Maybe used regardless of whether or not the errors follow a normal distribution and whether or not errors qualify as outliers. 5% of the errors will be of larger value.
17
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Bringing ReliabilityBringing Reliability
We need to quantify which is the error we are committing when we say “the RMSE of this DEM resulted to be ..... meters”
That error should depend on the number of check points used and somehow the “quality” of the sample from which we have computed the total error (RMSE).
18
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
The Li’s modelThe Li’s model
Li, Z., 1991. Effect of check points on the reliability of DTM accuracy estimates obtained from experimental tests. PE&RS 57(10): 1333-1340.
10012
1
)()(
NSdR
11
2
N
ee
Sd
N
ii )(
How many check points do we need to evaluate the error at a confidence level of 90% (R=10%):
puntosSdR
NSdR 5112
110
2
)(,)(
Hypothesis: normal distribution of errors and no bias
19
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
The Aguilar’s modelThe Aguilar’s model
Aguilar F.J. et al., 2007. A theoretical approach to modelling the accuracy assessment of DEMs. PE&RS 73(12): to be published in December.
Error population
NxxxxX ,...,,, 321
1
443
2
100100
2
21
222
2
)((%)
nR
RMSE
RMSESd
x
x
2 = standardised kurtosis = (4/4)-3
1 = skewness = 3/3
Any assumption, any restriction to use it
20
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Morphology (cm) (cm) Skewness (1)
Kurtosis (2)
Mountainous 0.02 11.16 0.39 12.18
Rolling 1 0.01 2.72 0.84 13.20
Flat 0.01 2.08 0.64 23.99
Steep rugged hillside
0.48 41.01 0.60 21.55
Highly rugged -0.87 135.02 0.12 31.95
Slightly mountainous
0.12 6.36 1.12 21.12
Rolling 2 -0.08 1.84 -0.37 29.66
Newcastle, September 2007
Residuals datasets (raw data)Residuals datasets (raw data)
Leptokurtosis
2>0
Platykurtosis
2<0
21
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Residuals datasets (corrected data using 3-sigma rule)Residuals datasets (corrected data using 3-sigma rule)
Morphology (cm) (cm) Skewness Kurtosis Residuals removed (%)
Mountainous -0.12 8.20 -0.04 3.07 2.32
Rolling 1 -0.13 1.88 0.41 3.79 2.73
Flat -0.01 1.35 -0.04 4.15 2.16
Steep rugged hillside 0.22 30.34 0.04 3.16 1.90
Highly rugged -1.51 87.57 0.02 6.05 2.25
Slightly mountainous 0.03 4.42 0.10 4.39 2.49
Rolling 2 -0.03 1.11 -0.25 5.11 2.15
22
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Model validation using Monte Carlo simulation methodModel validation using Monte Carlo simulation method
Reliability predicted (%)
Rel
iabi
lity
obs
erve
d (%
)
0 10 20 30 400
10
20
30
40
Reliability predicted (%)
Rel
iabi
lity
obs
erve
d (%
)
0 20 40 60 800
20
40
60
80
Reliability predicted (%)
Rel
iabi
lity
obs
erve
d (%
)
0 10 20 30 400
10
20
30
40
Reliability predicted (%)
Rel
iabi
lity
obs
erve
d (%
)
0 10 20 30 40 50 600
10
20
30
40
50
60
Aguilar et al., 2007 (raw data) Aguilar et al., 2007 (filtered data)
Li, 1991 (raw data)
R2=97.32% R2=99.28%
R2=58.07% R2=82.61%
Li, 1991 (filtered data)
23
4. Reliability of DEM accuracy 4. Reliability of DEM accuracy measures?measures?
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Visualisation of theoretical modelVisualisation of theoretical model
N (number of check points)
Kurtosis
Rel
iabi
lity
(%
)
0 50 100150200250300350400 010
2030
40
010203040506070
24
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Estimating LiDAR vertical accuraciesEstimating LiDAR vertical accuracies
Non open terrain
25
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Model overviewModel overview
Error population
NxxxxX ,...,,, 321
Non-parametric approach using Estimating Functions Theory for computing mean error
confidence intervals
Statistical inference from N check points
(sample size)
Godambe, V.P., 1991. Estimating functions. Oxford University Press, Oxford, 356 pages.
26
2
122
422
1
2122
2
1
2
1
2
N
t
xm
mmm
m
m
m
m
upper
))((
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Estimating LiDAR vertical accuraciesEstimating LiDAR vertical accuracies
2
122
422
1
2122
2
1
2
1
2
N
t
x
mmm
m
m
m
m
lower
))((
and Being 22m
11m NN
Sd tx upperupper
Sd tx lowerlower
Aguilar, F.J. and Mills, J.P. Accuracy assessment of LiDAR derived digital elevation models. The Photogrammetric Record, under review.
27
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Datasets from EuroSDR project on laser scannerDatasets from EuroSDR project on laser scanner
7 datasets with 15 reference data
28
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Datasets from EuroSDR project on laser scannerDatasets from EuroSDR project on laser scanner
TerrascanTM last pulse data filtering
Comparison with
reference data
Error datasets for
non open terrain
29
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Error datasets from EuroSDRError datasets from EuroSDR
Samples Points Mean (m) Sd (m) γ1 γ2 % data outliers
11 16995 0·16 0·44 3·30 11·82 3·5
12 25203 0·04 0·16 6·26 54·41 0·5
21 9742 0·02 0·05 1·83 4·77 3·1
22 21193 0·04 0·13 5·12 32·39 1·7
23 10871 0·05 0·20 5·06 31·26 1·4
24 3695 0·04 0·17 5·31 45·81 1·6
31 15315 0·01 0·04 1·29 4·16 1·4
41 1626 0·25 1·11 5·05 24·41 1·6
42 11743 0·02 0·07 2·98 13·22 2.0
51 13701 0.00 0·06 0·26 5·32 1·1
52 17368 0·08 0·30 2·52 8·41 1·7
53 24702 0·16 0·71 6·64 57·08 1·6
54 3863 0.00 0·08 2·79 19·27 2·1
61 31057 0·01 0·10 3·84 24·07 1·5
71 12517 0·02 0·11 2·33 10·80 2·1
30
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
0
0.15
0.3
0.45
0.6
0.75
0.9
1.05
1.2
1.35
1.5
0 20 40 60 80 100 120
Number of check pointsA
ccur
acy
(m)
0
10
20
30
40
50
60
70
Rel
iabi
lity
(%)
Fundamental vertical accuracy
Supplemental vertical accuracy
truth accuracy (95th method)
Reliability for fundamental accuracy calculation
Reliability for supplemental accuracy calculation
Newcastle, September 2007
Results for EuroSDR error datasetsResults for EuroSDR error datasets
75
80
85
90
95
100
0 20 40 60 80 100 120
Number of check points
Per
cent
age
of e
rror
s w
ithin
co
mpu
ted
inte
rval
s
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Rel
iabi
lity
(%)
Aguilar and Mills model Reliability
Results corresponding to dataset 1, sample 1
31
-1-0.8-0.6-0.4-0.2
00.20.40.60.8
11.21.4
0 20 40 60 80 100 120
Number of check points
Err
or v
alue
(m)
upper bound lower bound population mean
NSSDA upper NSSDA lower
5. Accuracy assessment of LiDAR derived 5. Accuracy assessment of LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Results for EuroSDR error datasetsResults for EuroSDR error datasets
32
6. Modelling error for LiDAR derived 6. Modelling error for LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
2222filteringgriddingSDEtotal 222
griddingSDEtotal
Newcastle, September 2007
Outlining the approachOutlining the approachNon-open terrainOpen
terrain
33
6. Modelling error for LiDAR derived 6. Modelling error for LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Outlining the approachOutlining the approach
222griddingSDEtotal
Computation at N check points on open terrain 22864602 03181 ILSDEgridding M ..
IDW method power to 2
34
0
1
2
3
4
5
6
7
8
9
0 1 2 3 4 5 6 7 8 9
Sd predicted (m)
Sd
ob
se
rve
d (
m)
6. Modelling error for LiDAR derived 6. Modelling error for LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Calibrating the empirical component (Information Loss)Calibrating the empirical component (Information Loss)
499870973070275840 .... DSlopeIL
29 morphologies of 4 has with average slopes ranging from 3% to up to 82%
R2 = 0.9856
35
6. Modelling error for LiDAR derived 6. Modelling error for LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Validating the modelValidating the model
33 GPS-obtained check points
Dataset of LiDAR data captured by Riegl Q560 sensor in August 2006 over Bristol area (Ordnance Survey project). Average density > 0.5 points/m2
With the permission of the Ordnance Survey
Sd = 0.124 m
max error = 0.37 m
min error = -0.17 m
mean error = 0.04 m
36
6. Modelling error for LiDAR derived 6. Modelling error for LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Validating the modelValidating the model
00.10.20.30.40.50.60.70.80.9
0 0.01 0.02 0.03 0.04 0.05 0.06
Lidar points density (points/m2)
Err
or
(m)
estimated error
observed error
spacing 4.4 m
spacing 23.5 m
37
6. Modelling error for LiDAR derived 6. Modelling error for LiDAR derived DEMsDEMs
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Behaviour of the modelBehaviour of the model
0
1
2
3
4
5
6
0 0.02 0.04 0.06 0.08 0.1 0.12
D (poins/m2)
To
tal e
rro
r (m
)
0.2 slope
0.6 slope
0.8 slope
1 slope
spacing 3.1 m
spacing 4.1 m
SDE = 0.15 m
spacing 7.1 m
38
7. Conclusions7. Conclusions
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Very little work has been done to determine the minimum data requirements for specific applications of DEMs, although there is a increasing tendency to collect larger volumes of elevation data. In the majority of the cases it is preferable to have an optimised DEM adapted to our needs rather than to have a vast amount of data, which will be more difficult to handle.
The reference standards methods for accuracy assessment of DEMs are based on hypothesis very restrictive and sometimes not according to reality, above all in the case of LiDAR data un non open terrain.
The tools expound in this talk are seeking to establish more general protocols for testing the quality of the product delivered from the part of the producer or even checking the quality of the own control quality, if there was.
39
8. That’s all8. That’s all
A METHODOLOGICAL PROPOSAL FOR ACCURACY A METHODOLOGICAL PROPOSAL FOR ACCURACY
ASSESSMENT OF LIDAR DERIVED DEMsASSESSMENT OF LIDAR DERIVED DEMs
Newcastle, September 2007
Thank you very much Thank you very much for your kind attention for your kind attention
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