Production of 1:50,000 scale image maps using satellite imagery
Kasi Balarathinam
Digital mapping centre, Survey of India
17-EC Road, Dehra Dun-248001, INDIA
Abstract
The author has the privilege of creating an image map, by combining SPOT panchromatic data with the Landsat TM data and annotating with selected topographical map features. Bands 5 3 1 of the TM data are used in the R G B (Red, Green, Blue) channels in false colours. The work is done in the International Imaging System(IIS) using the System-600 software in VaxVms environment . The job is scheduled to be completed by Aug. 90 and the map printed by sept 90. Brief-600 command history as used in the process with description of the purpose, is appended as enclosure-1.
The TM image is registered with the reference SPOT Panchromatric image using 28 ground control points (GCPs). By using least squares regression technique(4), the RMS error in the image registeration, could be reduced to less than 0.9 of a TM pixel. The SPOT and the TM data are mixed by adding the intensity values of the SPOT pixel at each location to the intensity value of the TM pixel in the corresponding location in each of the three bands. The output image is scaled suitably and registered with the 1:50,000 topographical map using 21 GCPs achieving an RMS error of less than 0.9 of a SPOT pixel (9 m ) . The information contents in the SPOT panchromatic data of 10m resolution are found enhanced in the multispectral environment in the TM bands reasonable success.
The image map is annotated with selected topographical map features. Contours at 200m vertical interval, annotations and other cultural information (not clear in the image), are compiled from the topographical maps and composed with the image map in suitable R G B colour values. Contours are merged with the image map in blue and brown for regions of permanent snow and other regions. The permanent snow area is classified (using the minimum distance classifier) and filtered (using mode filters of varying kernels in succession). The resulting snow region in raster form is edited in the Intergraph environment. This classified and processed output is used as a mask to split the contour file of the topographical map into two files viz, one for the permanent snow bound region and the other for the remaining regions, using map composing techniques.
In principle, the primary colours in the R G B channels in the video, are identical to the negated C M Y (Cyan, Magenta & Yellow) reprographic inks. The optronics 4040 photo plotter can directly plot or negate and plot these R G B band images with suitable half-tone screens for reproduction in C M Y.
This beginning in the image map reproduction in the survey of India, is a mile stone in the mapping technology for planners, engineers, scientists and other users in India.
The input satellite data for mapping
The SPOT panchromatic data and Tm data for the region of mapping were supplied by the national Remote sensing Agency (NRSA) . The area for mapping is incident in adjoining TM quadrants of a scene in the X-direction and the IMAGER, an Intergraph image processing system, has the necessary software to combine the adjoining quadrants situated in the X or Y direction. We, therefore, read the TM data in the IMAGER. By examining the TM image, Bands 5 3 1 were selected for projection in false colours in the R G B channels.
Registeration of TM image with SPOT image
The SPOT and the TM images were displayed in a split screen mode and 33 common points (GCPs) were chosen. A polynomial least squares fit the RMS error as 2.015 TM pixels and indicated that the 17th GCP is the most erroneous point with error as 6.889 pixels. This erroneous control point was deleted. Now the next fit agreed with lesser RMS error. This erroneous control point was deleted. Now the next fit agreed with lesser RMS error, This process of least squares regression was repeated until about 12 control points were left. The analysis indicated that 18 control points would be and optimum choice, with RMS error as 0.896 TM pixels. The Warping is done using full bivariate third order Legendre Polynomial. The rate of convergence of the RMS error will be very slow if the recorded machine coordinates are rounded and not precise. It is avoided by enlarging the region of incidence of the control points and indication the location as precisely as possible. The rate of convergence is then found to be faster.
