Abstract :
Up to the availability of the announced very high resolution satellite images, the IRS-1C and IRS-1D PAN-camera creates with 5.8 m pixel size, digital space images with the highest resolution which are not classified. The swath width of 70 km in the nadir view is covered by a combination of 3 CCD-line sensors, each with 4096 pixels. There is a time delay in imaging with the center line against both other CCD-lines, causing geometric problems of joining the 3 CCD-lines together. Based on ground points, visible in the overlapping area of 2 neighbored CCD-lines, the image parts can be transformed together. But a simple shift is not sufficient because the scale of the CCD-lines is different and there is also a rotation of the sub-scenes. This only can be determined by self-calibration with additional parameters in a bundle solution using a rigorous mathematical model. With precise control and check points a ground accuracy of SX=+/-7.1 m, SY=+/-5.0 m and SZ=+/-9.7 m has been reached corresponding to +/-1.1 pixel. This is possible without pre-knowledge of the sensor geometry just with 8 control points for the covered area of 86 km*84 km. The achieved accuracy is mainly representing the point identification, not the sensor accuracy itself. A comparison of mapping the same area with IRS-1C-PAN-images and with multispectral and panchromatic SPOT-images has shown the advantage of the higher resolution IRS-1C-images. Nearly all objects required for mapping in the scale 1:50 000 could be identified, which was not the case for the SPOT-images. Only with the very high resolution Russian KVR 1000-photos, better object information could be achieved
Keywords :
geophysical techniques; terrain mapping; IRS; IRS-1C; Indian Remote Sensing satellite; PAN-image; geometric potential; geophysical measurement technique; information potential; land surface; optical imaging; satellite remote sensing; terrain mapping; Availability; Delay effects; Geometry; High-resolution imaging; Image resolution; Jacobian matrices; Mathematical model; Optical imaging; Pixel; Satellites;