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Attribute Generation and Analysis

Attributes are attached to both point cloud and surface mesh data. Many attribute functions are common to both point clouds and surface mesh data.

By default point clouds have Red, Green, and Blue (RGB) attributes, and intensity if the information exists in the imported data. Sometimes these attributes may be NULL (empty). VRGS requires at least 1 attribute in order to display a dataset. Red, Green, and Blue attributes are preferred. False colour RGB can be created based on elevation or intensity.

Meshes do not require any attributes to display them if they have associated textures.

Creating attributes​

False Colour​

Right + click a point cloud or surface mesh in the Data tab, then select False Colour → Elevation to create an elevation attribute.

WARNING: Creating a false colour RGB set will overwrite any existing RGB values.

Attributes common to point clouds and meshes​

Tensor Analysis:​

WARNING: Potentially a very long operation.

An approach developed by Fernández1 and developed further by García-Sellés et. al.2 uses a tensor analysis approach to analyse the topography of a point dataset to generate a variety of parameters. The sphere radius defines the volume of the model around each point for which the tensor analysis will be performed. As a minimum, this should twice the de-cluster distance, or twice the data spacing. Larger values give a smoothed result, small values are more perceptible to noise in the data.

The check all button selects all attributes for output.

The most useful attributes are:

  • Dip & Azimuth (of the outcrop model surface)
  • colinearity (how linear the points are)
  • coplanarity (how flat the points are)
  • Number of values used (useful to check if the sphere radius is too small or too big)
  • Colourspace: Converts the RGB values to different colour-spaces which may give a different visual representation of the data.

Editing and Filtering Attributes​

Colour Maps​

By default, attributes are shown with a magma colourmap. VRGS provides several other perceptually uniform (or linear) colourmaps. Perceptually uniform colourmaps minimise visualisation bias of the data and provide a universally readable dataset for people that may be colour-vision deficient3.

Perceptually Linear​

  • inferno
  • magma
  • plasma
  • virids

Elevation-specific​

  • Ordinance Survey (OS) Elevation
  • USGS Elevation

Attributes can be transformed, edited, and displayed with different colourmaps. Current transforms are Log, Square Root, Clip, Cox Box, Normalise, and Exponential.

The Clip attribute operation allows high and low values to be truncated, effectively performing a contrast stretch on the attribute. This allows the full colour scale to be used effectively in the display. The red and yellow dotted lines can be dragged to change the degree of clipping.

Filters​

The attribute properties also provide a means to filter by attributes, this allows us to, for example, show only the point where the dip attribute is > 45 degrees. Filters can be set on each attribute and the results of all the filters are combined to give the final display.

In the attributes property page (see above) check the Use Filter option. Set the filter minimum and filter maximum values to match the range of values you wish to use. Then in the parent point clouds properties, check the Use Attribute Filters box. This allows multiple filters to be switched off easily.

RGB Blended Display​

False colour displays can be created by using attributes in place of the colour channels in the RGB view. A display can be generated, for example, using Dip for the Red channel, Azimuth for the Green channel and co-planarity for the blue channel. In order to do this, show the attributes for the point clou, then in the Properties Panel select the attributes to replace the Red, Green and Blue colour channels with.

Footnotes​

  1. Fernández, O. (2005) Obtaining a best fitting plane through 3D georeferenced data. J. Struct. Geol., 27, p. 855-858 https://www.sciencedirect.com/science/article/abs/pii/S0191814105000143 ↩

  2. García-Sellés, D., Falivene, O., Arbués, P., Gratacos, O., Tavani, S. and Munoz, J.A., 2011. Supervised identification and reconstruction of near-planar geological surfaces from terrestrial laser scanning. Computers & Geosciences, 37(10), p.1584-1594. https://www.sciencedirect.com/science/article/abs/pii/S0098300411001099 ↩

  3. Crameri, F., Shephard, G.E. and Heron, P.J., 2020. The misuse of colour in science communication. Nature communications, 11(1), p.5444. https://www.nature.com/articles/s41467-020-19160-7 ↩