1887
Volume 26, Issue 2-3
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

High resolution digital elevation models (DEMs) can now be produced for large areas of Australia. This paper will describe the method of producing DEMs and some of the applications.

The change in technology which has made possible routine generation of height data for large areas, is soft photo-grammetry. In the past, the method of determining height was by matching points on two airphoto stereopairs. This was accomplished manually which made for a tedious and time consuming process. The advent of computer software that can match features on stereopairs has meant that DEMs can be created much more quickly.

The procedure is to scan the diapositives of the air photographs with a geometrically accurate scanner at high resolution (15-30 microns). This will give a pixel size of 1.5 metres for a 1:50,000 scale photo. Internal and external distortion is then removed from the scanned images by internal, relative and absolute orientation procedures. The images are then resampled as epipolar pairs. The final procedure is to automatically match common features on both of the stereopairs. Changes in the X parallax give the height or Z value.

The DEMs are accurate to within +/-1 pixel i.e. 1.5 metres for standard 1:50,000 scale photography or 25 cm for 1:10,000 photography. This high resolution allows for a number of novel applications, including:- identify topographic anomalies associated with mineralisation (e.g. kimberlite lows, silicified highs)

- georectify photographs to produce orthophotos

- 3D visualisation, 3D Photomaps, and terrain draping

- structural analysis using shaded relief images

- landform analysis including palaeo surface reconstruction

- slope vector maps for soil sampling and geochemical dispersion

- drainage maps and drainage divides for stream sampling programs

- height corrections for high resolution gravity surveys

Images for these applications will be shown for the Laverton 1:50,000 sheet area in Western Australia.

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1995-06-01
2026-01-16
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References

  1. Dong-Chen, He, and Li, Wang, 1990, Texture unit, texture spectrum, and texture analysis: IEEE Transactions on geoscience and remote sensing 28, 509512.
  2. Fairall, J., 1995, Soft Photogrammetry: The Australian geographic information systems applications journal 9, 62-64.
  3. Gong, P., et al, 1992, A comparison of spatial feature extraction algorithms for land-use classification with SPOT HRV data: Remote sensing and environmental science 40, 137-151.
  4. Haralick, R.M., et al, 1973, Textural features for image classification: IEEE Transactions on systems, man, and cybernetics SMC-3, 610-621.
  5. Marceau, D.J., et al, 1990, Evaluation of the grey-level co-occurence matrix method for land-cover classification using SPOT imagery: IEEE Transactions on Geoscience and Remote Sensing 28, 513-518.
  6. Miller, S.B., et al, 1992, Softcopy photogrammetric workstations: Photogrammetric Engineering and Remote Sensing 58, 77-83.
  7. Shin-yi Hsu, 1978, Texture-tone analysis for automated land-use mapping: Photogrammetric Engineering and Remote Sensing 44, 1393-1404.
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