Laserscanning Œ aktueller Stand in Forschung und … · Karl Kraus Laserscanning - aktueller Stand in Forschung und Entwicklung 2 Geo-Referencing Observations Łheights of the control

Laserscanning � aktueller Stand in Forschung und Entwicklung

Karl Kraus

Institute of Photogrammetry and Remote Sensing (I.P.F.), Vienna University of Technology

www.ipf.tuwien.ac.at

� Neues gegenüber dem Vorjahr

� Beispiele vor allem aus dem Pulkauprojekt (NÖ)

� Gebäude und Spezifisches zum Hochgebirge erst am Nachmittag

Karl Kraus Laserscanning - aktueller Stand in Forschung und Entwicklung 2

Geo-Referencing

Observations�heights of the control points

�height differences of parallel plane patches calculated from neighbouring points in adjacent strips

Unknowns�heights for all the tie points

�heights for all the control points

�additional parameters for the compensation of the systematic errors

Improvement of the homogeneity in the overlapping areas by a factor between 2 and 4

=> Extension to 3D (with structure line elements) and modelling the flight path, etc.


Geo-Referencing

�Control Point� = a few tilted planes


Projekt Pulkautal

Differenzmodell der Laserscanner-Streifen 10 und 11

nach der simultanen Höheneinpassung


Derivaton of DTMsRobust Linear Prediction

271 control points:

σ = ±18cm

point distance : ~3.1m

σ = ±29cm

point distance: ~1m

=> point density is the most important parameter


Derivation of DTMs (cont.)Robust linear prediction in a hierarchical approach

a) Creation of a data pyramid (lowest point with its xyz-co-ordinates in a regular grid)

b) DTM generation in the coarse level

c) Coarse DTM with a tolerance band

d) DTM generation in the fine(r) level


Derivation of DTMs (cont.)

Laser scanner data with the gaps after the elimination of theoff-terrain points

Kamptal in NÖ, Department of WaterManagement, Hydrology and Hydraulic EngineeringBOKU - University of Natural Resources and Applied Life Sciences, Vienna)

Quality Overlays� distance between each grid point and the next point of the original data set

� variances in small cells derived from the differences between the elevation of the original points and the elevation of the DTM at the same locations

� the density of the points also in this small cells

� σ in each grid point


Projekt Pulkautal

[Punkte/m2] [Punkte/m2]

Punktdichte der original Laserscanner-Punktwolke

Punktdichte der Bodenpunkte


Projekt Pulkautal (cont.)

Abstandsmodell für die Bodenpunkte



Mittlere Residuen zwischen Laserpunkten und DGM

ursprüngliche Laserpunkte Bodenpunkte



Manuelle photogrammetrischeDatenerfassung

Photogrammetrisches DGM



Laserscanner-DGM Orthophoto



� Photogrammetrie �Modell-Patches�

� Scanlag in ALS

� Kanten in Photogrammetrie

� Kleinformen in ALS


Accuracy and Geomorphologic Quality of Laser Scanner DTMs

Empirical elevation accuracy of LaserScan DTM

tanα . . . Terrain slopen . . . Average number of points per square meter

[ ]

⋅+±= ασ tan1206n

cmz

For flood risk area the accuracy of the positionof the border of predicted flood is of central interest:

ασσ

tanz

xy =

e.g. σz = +/- 12 cm σxy = +/- 25 m ! (tan α = 5%o)


Accuracy and Geomorphologic Quality of Laser Scanner DTMs (cont.)

Flood risk area (project of the Lower-Austrian Govermental Administration)


Geomorphologic Quality of Laser DTMs� only a point cloud� point density is the important parameterWavelike surfaces with a minimal wave length Lmin

Scanning theorem

∆ ≈ Lmin/3

Derivation of breaklines from the point cloud

minimal crown width Bmin

∆ ≈ Bmin/2


Surface Break Lines

Hybrid DTM consisting of a regular raster with 3D vectors


Surface Break Lines (cont.)

How to get the relevant 2D break lines?


Surface Break Lines (cont.)

Automatic procedure: rain simulationSemiautomatic procedurea. Manual digitization as 3D lines in photogrammetic stereomodels

Almtal

Upper-Austria

Govermental

Administration

BEV: The entire territory of Austria* image scale 1:15 000, 21 cm camera* σz = +/- 45 cm (too bad)* σxy = +/- 25 cm (good enough)


Data Reduction

� The very high density of points is a great advantage for improving the quality

� but there are difficulties in the data management.

Derivation in each grid point of the dense DTM:

� radius R of the curvature

� slope tanα

� allowable distance E in order to keep dZ less than threshold dZmax

Idea of progressive sampling


Data Reduction (cont.)

Small example

Wienerwald

MA 41 der

Stadtverwaltung

Wien

Typical example

� 4 millions of grid points

� user defined threshold dZmax = 25cm

� 1.3 million of the reduced points

� 4.75 minutes on a 2 GHz computer including the output in ASCII


Monitoring Flooding Catastrophes

Monoplotting

Different types of images, geo-referenced by GPS and IMU:

� Digital frame camera

� One-line scanner

� Three-line scanner

� Amateur camera (with oblique axes)

� Microwave sensors (for extreme weather conditions in flooding periods)


Monitoring Flooding Catastrophes (cont.)

Scenario� Actual water level and the 3D border lines of the

flood, corresponding to the time when the images have been taken

� Based on short-term prognoses of precipitation,prediction of the rise in water level

� Increase of the actual water level by the predicted rise ⇒ Surface at the predicted water level

� Intersection of the surface of the predicted water level with the precision DTM

⇒ Areas at immediate risk can be plotted

⇒ Catastrophe management can take important decisions and can inform those affected.

A vision: After taking the images final results within one day


Additional Features Relevant to Hydraulics and Hydrology

Model without structure lines:- grid width: 50 m- 55.000 points


Additional Features Relevant to Hydraulics and Hydrology (cont.)

Hydrological analysis:- drainage

dark-blue: valleylight-blue: watershed

developed by:

Rieger W.

Gajski D.

Molnar L.

Dorninger P.



Hydrological analysis:- lakes (depressions)- rivers

⇒ structure lines


Valles Marineris on the Mars:-10° x 10° = 593 x 593 km-grid width: 463 m / Pixel

Mars Global Surveyor (NASA)1997 � 2001

MOLA (Mars Orbiter Laser Altimeter)

330 m point distances in profiles


orthophotoz-coding



Valles Marineris on the Mars:- 10° x 10° = 593 x 593 km- grid width: 463 m / Pixel

river analysisorthophotoz-coding



Valles Marineris on the Mars:- 10° x 10° = 593 x 593 km- grid width: 463 m / Pixel

depressionsriver analysisorthophotoz-coding



Perspective view:

- z-coding

- MOC � orthophoto

- lakes and rivers

Documents

Laserscanning Œ aktueller Stand in Forschung und … · Karl Kraus Laserscanning - aktueller Stand in Forschung und Entwicklung 2 Geo-Referencing Observations Łheights of the control