Institute of Photogrammetry and GeoInformation

TUTORIAL Information extraction, with emphasis on DSM generation, from high resolution optical satellite sensors

Karsten Jacobsen1, Emmanuel Baltsavias2, Nicolas Paparoditis3, Peter Reinartz4

1 University 2 Institute

3 Institut

of Hannover, Nienburger Strasse 1, D-30167 Hannover, Germany, [email protected]

of Geodesy and Photogrammetry, ETH Zurich, Wolfgang Pauli Str. 15, CH-8093 Zurich, Switzerland, [email protected] Géographique National, 4 avenue Pasteur, 94165 Saint-Mande, France, [email protected]

4 DLR

(German Aerospace Centre), Institut für Methodik der Fernerkundung, Bildwissenschaften, D-82234 Oberpfaffenhofen, Post Wessling, Germany, [email protected]

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Section 5 DSM generation using SPOT-5 HRS and other space data Peter Reinartz, Karsten Jacobsen DLR (German Aerospace Centre), Institut für Methodik der Fernerkundung, Bildwissenschaften, D-82234 Oberpfaffenhofen, Post Wessling, Germany, [email protected] D-82234 Oberpfaffenhofen, Post Wessling, Germany, [email protected] University of Hannover, Nienburger Strasse 1, D-30167 Hannover, Germany, [email protected]

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

SPOT 5 HRS •

Image matching

•

Test Areas and ground reference data

•

Properties of SPOT- HRS Data

•

Orthoimage generation without ground control, accuracy

•

Image matching (image pyramid, interest operator, dense matching)

•

DEM generation without ground control

•

DEM comparison and accuracy analysis with reference DEM

•

Improvement of exterior orientation

•

DEM comparison and fusion with SRTM DEM

•

Conclusion ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

SPOT 5 HRS (high resolution stereo)

view d r a w for

iew v d war k c ba

View direction: +20°, -20°, incidence angle: +23°, -23° pixel size in orbit direction: 5m

h/b = 1.2

across orbit: 10m

advantage of configuration: no change of imaged object within 90 sec. no change of the object, no change of the illumination, no change of the atmosphere ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Methods of image matching 1. Feature based matching – corresponding well determined points – as start information for other matching methods 2. Area based matching - correlation – finding optimal position of pattern matrix in a search matrix, start values required, problems if area not flat 3. Image correlation in epipolar lines – at least relative orientation required, search only in one direction

4.

Vertical line locus – correlation of corresponding sub-matrixes in object space – exterior orientation required

5. Least square matching – respects object inclination and linear changes of grey values, precise but very good approximations required

dx1 inclin ation

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

dx2

Institute of Photogrammetry and GeoInformation

Problems with matching in build up areas first imaging

convergence angle

height

second imaging

ba se

it orb

left

top

top

right

imaged area

IKONOS Maras h/b = 7.5

OrbView-3 Zonguldak h/b = 1.4

shadow right

shadow left

= points which can be determined ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Problems with matching in build up areas sub-images IKONOS h/b=7.5

OrbView-3 h/b=1.4

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Vertical ground accuracy

hg SZ = sn ∗ ∗ Spx formula for photos b SZ =

hg ∗ a 2 ∗ GSD b

SZ = standard deviation of ground Z b = base (distance of projection centers Spx = standard deviation of x-parallax (x‘-x“)

a2 = factor

formula for digital images base

height

base

height

In case of automatic image matching: factor a2 smaller for larger h/b relation Æ SZ not so much depending upon h/b-relation

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Test area Bavaria

south

Z-range: 350m – 1850m ~ 20% forest,

lakes

view to south – DEM generated by SPOT HRS ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Orthoimage generation for accuracy analysis Test area Barcelona: for/back orthoimage overlay (Orthoimage generation with reference DEM)

The accuracy compared with 24 ground control points has been found in the range of one/two pixel for forward and backward looking channel

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Attitude data

1 scene = 60km in orbit direction = 8 sec effect on ground ~ 2m

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Attitude data

1 scene = 60km in orbit direction = 8 sec effect on ground ~ 1.5 m

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Attitude data

1 scene = 60km in orbit direction = 8 sec effect on ground ~ 0.1 m

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Absolute accuracy of orthoimages influence of sensor orientation + DEM Mean values and standard deviations for the difference to the orthoimages of 20 ground control points in meter in Transverse Mercator coordinate system (Bavaria) Forward looking x2 – x1 y2 – y1

Backward looking x3 – x1 y3 – y1

MEAN

-4,3

5.0

-14.3

11.5

Std. dev

5.89

7.35

6.23

8.64

Mean values and standard deviations for the difference to the orthoimages of 24 ground control points in meter in ED50 coordinate system (Catalonia) Forward looking Backward looking Nadir looking x2 – x1 y2 – y1 x3 – x1 y3 – y1 x4 – x1 y4 – y1 MEAN

-9,90

-16,59

-0,36

-11,16

-24,22

-6,22

STDV.

4,64

8,48

5,72

5,23

5,96

5,71

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Orthoimage generation for accuracy analysis

influence of sensor orientation + DEM Image Matching result between the two orthoimages (for/back)

Resulting mean vector length: 14 meters, RMS: 2 meters ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Image matching Matching strategy •

First image matching uses an image pyramid, restricting matching to interest operator points for each level (maximum of correlation coefficient)

•

Local least squares matching to sub-pixel accuracy in all levels of the pyramid generates tie-points for subsequent dense matching = start values for next step

•

Dense matching with region growing (Otto-Chau-algorithm) (with different window sizes and backward matching for blunder reduction) leads to mass points (here 60 to 80%) in image space

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Calculation of object coordinates •

Forward intersection using least squares adjustment of the two image rays

•

Rejection criterion: intersection of image rays exceeding one pixel

•

Interpolation of irregular distributed points into a grid of 15 x 15 meter pixel size (Catalonia), interpolation process is performed by a moving plane algorithm

distribution of matched points (about 2/3 of area covered)

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

DEM and orthoimage of Bavaria Image draped over generated height model

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Test area Bavaria

Accurate reference data: laser + photogrammetry

Colour coded height model from SPOT 5 HRS

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006

Institute of Photogrammetry and GeoInformation

Accuracy of DEM (single height points without GCP) • Comparison of height for high quality homologous points in SPOT-DEM and reference DEM Reference area

Size, Accuracy of Ref-DEM

bias [m]

Std. Dev. [m]

Points [#]

DEM-01, Prien

5 x 5 km, 0.5 m

6.8

2.0

240

DEM-02, Gars

5 x 5 km, 0.5 m

6.2

2.2

184

DEM-03, Peterskirchen

5 x 5 km, 0.5 m

5.6

1.8

261

DEM-04, Taching

5 x 5 km, 0.5 m

4.9

2.0

254

10 x 10 km, up to 5 m

5.7

3.5

458

50 x 30 km, 2-3 m

6.1

3.6

15177

DEM-05, Inzell (mountainous) DEM-06, Vilsbiburg

ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006