Section 5 Orthoimage generation

Transcription

1 Section 5 Orthoimage generation Emmanuel Baltsavias

2 Orthoimage Generation Older sensor models methods: Kratky s Polynomial Mapping Functions (PMFs) Relief corrected affine transformation - Project GCPs on reference plane (X, Y coordinate corrections) using sensor elevation and azimuth - Reference plane -> reference plane of DTM - Compute affine transformation between X, Y object and x, y pixel coordinates - 3 GCP s are needed but 4-6 are suggested Current method: Use RPCs and subsequent shifts or affine transformation

3 Orthoimage Generation Luzern Test results Sens elev. (deg) 67.7 DTM spacing/accur (m) 25 / 2.5 lowland, 10 Alps GCP accuracy (m) GCP definition Very poor to good Elevation range (m) Method: Relief corrected affine transformation Version GCPs/CPs RMS/X RMS/Y Max. abs X Max. abs Y 1 0 / / / CPs = check points

4 Orthoimage Generation Nisyros Test results Sens elev. (deg) 73.5 DTM spacing/accur (m) 2 / 3.3 GCP accuracy (m) ca. 0.5 GCP definition Poor to good Elevation range (m) Method: Relief corrected affine transformation Version GCP's/CPs RMS/X RMS/Y Max. abs X Max. abs Y 1 0 / / /

5 Orthoimage generation (IKONOS, Quickbird) in Geneva Input data 2 IKONOS Geo images (IKONOS-West / IKONOS-East) 1 Basic QUICKBIRD Image Orthoimages (for acquisition of GCPs): OP-DIAE: Digital Orthos of Canton Geneva (25 cm pixel size, 0.5 m planimetric RMS) Swissimage: Digital Orthos of Switzerland of Swisstopo (50 cm pixel size, 1m planimetric RMS) DTMs: DTM-AV (from airborne laser scanning): 1 m grid spacing, 0.5 m height RMS DHM25 of Swisstopo (from digitised contours): 25 m grid spacing, m height RMS Measurement of GCPs with ellipse fit and line intersection. Image orientation with various sensor models. RPCs with subsequent affine transformation used for orthoimage generation.

6 GCP example: roundabout (Melbourne testfield)

7 Roundabout measurement via ellipse fit Edge points digitized semi-automatically, followed by ellipse fit

8 Roundabout measurements via least-squares template matching

9 Sensor Modeling and Block Adjustment Ellipse Fitting Ellipse fitting mode Line intersection mode User-interface for GCP measurement & block adjustment (Sat-PP ETHZ)

10 Orthoimage generation (IKONOS, Quickbird) in Geneva

11 Orthoimage generation (IKONOS, Quickbird) in Geneva Pansharpened orthoimages. Left Ikonos, right Quickbird.

12 Orthoimage generation (IKONOS, Quickbird) in Geneva Definition of lines and circles. Left Ikonos, right Quickbird. Note the large visual difference although pixel size is 1m and 0.7m respectively.

13 Orthoimage generation (IKONOS, Quickbird) in Geneva Planimetric accuracy of panchromatic orthos with GCPs from OP-DIAE (CPs = check points) Image Number of GCPs/CPs X RMS (m) Y RMS (m) X mean with sign (m) Y mean with sign (m) Ikonos West 10/ Ikonos East 10/ Quickbird 10/ Quickbird is not more accurate than Ikonos although GSD was 0.7m and 1m respectively. Planimetric accuracy could be even higher with well defined GCPs measured with GPS. In Y mean (bias) large due to coordinate system differences (Geneva and national systems differ).

14 Orthoimage generation (IKONOS, Quickbird) in Geneva Planimetric accuracy of panchromatic orthos with GCPs from OP-DIAE and Swissimage Image Number of GCPs/CPs X RMS (m) Y RMS (m) X mean with sign (m) Y mean with sign (m) Ikonos West 10/ Ikonos 10/ East Quickbird 10/ Submeter accuracy even with GCPs from not so accurate Swissimage orthos.

15 In-depth investigations of parameters influencing the accuracy of orthoimages from high resolution satellites AIMS The aim of this work was the analysis of orthoimage accuracy produced from IKONOS and QB images using different type of original data in Switzerland. More specifically, we were interested to see the influence on the planimetric accuracy of - different sources for the measurement of GCPs (Ground Control Points), - different elevation models and - different sensor elevation. The whole processing was performed mainly with Sat-PP (Satellite Imagery Precision Processing) software developed at IGP which makes use of good quality algorithms, especially for DSM generation and semi-automatic point measurement and feature extraction. The software can be used with any type of imagery, digital and scanned film, frame and linear sensors.

16 Specifications of the data The first area, Thun, lies in the central part of Switzerland 40 km southern of the capital of Switzerland, Bern. In this region in 2004, we established a testfield with a coverage of 15 by 20 sqkm for the analysis of high resolution satellite images. Later in 2006, this testfield was extended for the analysis of ALOS images to the neighborhood of Bern and Thun (30 by 30 sqkm). In the area of Geneva we used two IKONOS and one QB images. The test area had a size of 16 by 17 km.

17 Specifications of used satellite images: Image Date of acquisition Scanning mode Sensor- Azimuth (deg) Sensor-Elevation (deg) Geneva_Q Reverse Geneva_I_West Forward Geneva_I_East Reverse Thun_I_163003_ Reverse Thun_I_163003_ Reverse

18 Resolution and accuracy of used orthoimages and DTMs: OP-DIAE DTM-AV Swissimage DTM-AV DHM25 Rimini Produced by Reference frame Canton Geneva LV03-GE LV03-GE Swiss Federal Office of Topography (Swisstopo) LV03 LV03 LV03 LV03 Used elevation model DTM-AV DHM25 GSD / grid spacing [m] Planimetric accuracy [m] Accuracy of the height [m] / vegetation : 1.5 Flat-hilly- Jura: 1.5 Voralps: 2 Alps: 5-8 average deviation to DHM25 is about 17

19 RESULTS Orthoimage accuracy in the Geneva test area: CPs = check points Orthoimage version Number of CPs X (m) Mean Y (m) X (m) RMSE Y (m) Max Absolute X (m) Y (m) IKONOS_West_ DTM-AV IKONOS_West_DHM IKONOS_East_ DTM-AV IKONOS_East_DHM QB_DTM-AV QB_DHM

20 Results from the image orientation in Thun: GCP = Ground Control Points Date of Image Acquisition Type of GCP GCP CP x-rms [m] y-rms [m] z-rms [m] DGPS Orthoimage/DHM DGPS Orthoimage/DHM

21 Orthoimage accuracy in the Thun test area: Orthoimage version Elevation model Type of GCP Rimini GPS Rimini ORTHO Rimini GPS Rimini ORTHO DHM25 GPS DHM25 ORTHO DHM25 GPS DHM25 ORTHO Matching GPS Matching ORTHO Matching GPS Matching ORTHO LIDAR GPS LIDAR ORTHO LIDAR GPS LIDAR ORTHO Sensor elevation Number of CPs Mean X (m) Y (m) RMSE X (m) Y (m) Max Absolute X (m) Y (m)

22 Conclusions High accuracy DTM/DSM, as the DTM/LIDAR and the matching DSM, provide more similar accuracy in X and Y, quite independently of the sensor azimuth and elevation. As the DTM/DSM accuracy deteriorates, a higher sensor elevation is needed and the height errors are distributed in X and Y differently, depending on sensor azimuth. For high sensor elevation (in this case 83 degrees), an orthoimage accuracy of m was achieved even with the RIMINI dataset. The major influence on the orthoimage accuracy is from the DTM/DSM and the sensor elevation. The role of GCP accuracy, as long as this is within certain limits (e.g. at least one GSD) is subordinate. Since GCP acquisition is costly and time consuming, the selection of GCP acquisition method should be made based on the accuracy of the available DTM/DSM and the sensor elevation. Orthoimages with submeter accuracy can be produced even with suboptimal DSMs / DTMs and GCPs. Accuracy can reach 0.5 GSD.