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7 srtm paleochannels_aeromagnetics data

  1. What is SRTM? Definitions of SRTM on the Web: •The Shuttle Radar Topography Mission (SRTM) is an international research effort that obtained digital elevation models on a near- global scale from ... en.wikipedia.org/wiki/SRTM •A NASA Space Shuttle mission that used C-band and X-band interferometric synthetic aperture radars (IFSARs) to acquire topographic data over 80 ... earthobservatory.nasa.gov/Library/glossary.php3
  2. Where can you get it?
  3. Different formats available
  4. Another site for Landsat & SRTM
  5. How can you use SRTM? •Mapping current geomorphology •Mapping lineaments and other structural features •Landsat shows surface variations while SRTM has a penetration depth – ie reveals subsurface information useful for structural interpretations •Spatial Analyst (ESRI) can be used to creat hillshades of the data as shown on following slides
  6. SRTM hillshaded view Cape Fold Belt near Montague
  7. SRTM hillshaded view and modified colour ramp
  8. SRTM hillshaded view and modified colour ramp
  9. Paleochannels interpreted from aeromagnetics data SRTM can be used in combination with other geophysical datasets to reveal variations in geological patterns / processes with time. An example of this is detecting changes in drainage channel patterns with time – which is NB When considering alluvial diamonds.
  10. Older paleochannel course (red vectors from aeromagentics data) More recent paleochannel course (from SRTM greyscale image) Comparing recent drainage with paleodrainage from geophysics data
  11. Placing drilled samples in the context of channel migration
  12. SRTM imagery can also be used to create flow direction maps based on the associated DEM data Hillshaded SRTM data overlain by extracted streams
  13. SRTM imagery can also be used to create flow direction maps based on the associated DEM data Extracted streams
  14. Regional aeromagnetics data for Southern Africa – further basis for aiding structural interpretations
  15. Regional aeromagnetics at 50 m – as tiffs for countries Tracing units of interest
  16. Regional aeromagnetic data as grey scale
  17. Combining aeromagnetic data with geology for exploration
  18. A closer look at using multiple datasets for exploration •Geological problems are often regional in nature There are many gaps in detailed geological mapping Remote sensing techniques provide a way to bridge these gaps GIS facilitates this process immensely
  19. A closer look at using multiple datasets for exploration In the following example we see how regional aeromagnetic data is used in a regional study to trace the trail of a geological unit of interest. Data from historical studies, digital geological data, structural and other geophysical data sets are all analyzed together in an attempt to define the unit across country boundaries.
  20. Structural and aeromagnetic data comparisons.
  21. Structural and aeromagnetic gradient data
  22. Comparing lithological datasets for different countries A B
  23. Structural and aeromagnetic dataset comparisons
  24. Feature definition Is the data good enough to resolve the feature of interest? Buffers around known unit trend compared to aeromagnetics data image
  25. Extrapolating the buffer zone across several images
  26. Mapping trends where the trace of the unit is lost
  27. Mapping trends where the trace of the unit is lost
  28. Filling the data gaps
  29. Can one link the trends back to the most likely continuation of the unit?
  30. More on Aeromagnetic data •Ring features are sometimes viewed on aeromagnetic / Landsat datasets •These maybe associated with radial dykes / intrusives or impact craters •Both provide an potential area of interest for exploration •In the following example we see how such features may appear on the imagery
  31. Aeromagnetic data color ramped Ring features – radial dykes / intrusives or impact craters?
  32. Through customized image processing additional ring features are visible (Impact crater Research Group, Wits, 2008) MATLAB processed image georeferenced in ArcMap
  33. MATLAB processed image 3D view
  34. MATLAB processed image – impact crater modeling