Section 3: Blending 2D Data

  • New blends are added into the blend list via right click context menu.
  • Currently five plan-view blend tools available:
    1. icon3a Triangle (good for radiometric data)
    2. icon3b Clique (good for multi-channel data like ASTER)
    3. icon3c Image Wheel (good for revealing correlations)
    4. icon3d Param Linear (good for a single filtered dataset)
    5. icon3e Param Bilinear (good for two dataset filtered over the same range)

Steps

  1. Right click on the blend list and choose the Start new blend … option from the context menu.
  2. Name the new blend to something unique and select the Image Wheel blend tool type. This blend tool is particularly useful for revealing correlations between datasets (see notes for more blend types). Note the brief description box that updates for each selected tool type. Click on the Ok button.
  3. The blend tool area should now contain the Image Wheel blend tool. Make sure the new blend is selected, and highlighted in blue in the blend list.
  4. Drag a plan-view dataset from the dataset list onto the icon3f blend node. This will add the dataset to the blend tool as an additional blend node on the edge of the blend circle.
  5. Drag several other plan-view datasets (in the same georeferenced location as the first dataset) from the dataset list to the same icon3f blend node. Note the corresponding colour and number of the blend node to the datasets in the dataset list.
  6. Left click on the blender tool and drag the small blue dot blend cursor to control the blend weight distribution between the blend nodes (Figure 3). The centre of the blending circle represents an average (equal blend weighting) of all the blend nodes.
  7. Right click on a coloured/numbered blend node, and Remove Data. This will remove the blend node completely, and the blender will adjust accordingly.
  8. Experiment with the other 2D blenders and different types of plan-view datasets. Note that the Param blenders require filtered datasets (i.e. DRC) as input to work properly.
Figure 3: The image wheel blender can be used to visualise the orientation of structures. (a) Two blending results corresponding to the colour coded positions shown in the blending tool. The 5 (or more) nodes represent geophysical data filtered with certain orientations. (b) The orange dot shows the data filtered with a relatively horizontal orientation, whereas (c) the purple dot shows the data filtered at a more vertical orientation.

Figure 3: The image wheel blender can be used to visualise the orientation of structures. (a) Two blending results corresponding to the colour coded positions shown in the blending tool. The 5 (or more) nodes represent geophysical data filtered with certain orientations. (b) The orange dot shows the data filtered with a relatively horizontal orientation, whereas (c) the purple dot shows the data filtered at a more vertical orientation.