Wall Height and Aspect

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Wall Height Aspect

The Wall height and aspect plugin can be used to identify wall pixels and their height using ground and building digital surface models (DSM) by using a filter as presented by Lindberg et al. (2015a). Optionally, wall aspect can also be estimated using a specific linear filter as presented by Goodwin et al. (1999) and further developed by Lindberg et al. (2015b) to obtain the wall aspect. Wall aspect is given in degrees where a north facing wall pixel has a value of zero. The output of this plugin is used in other UMEP plugins such as SEBE (Solar Energy on Building Envelopes) and height to width ratio.

Location

The Sky View Factor Calculator is located at

  • UMEP
    • Pre-Processor
      • Urban Geometry
        • Wall Height and Aspect.

Running the Plugin

When you run the plugin, you will see the dialog shown below.

File:Wall Height.png
Wall Height and Aspect Calculator start window

Building and Ground DSM

A DSM (geoTIFF) consisting of ground and building heights.

Calculate Wall Aspect

Tick this box if you want to include estimation and output of a wall aspect grid. This calculation is computational intensive and will make your computer work for a while (depending on the size of the input DSM).

Lower Limit for Wall Height (m)

This limit gives the lowest height of a building wall.

Output File for Wall Aspect Raster

Name of the output file of the aspect raster.

Output File for Wall Height Raster

Name of the output file of the aspect raster.

Run

This starts the calculations.

Add Result to Project

If this is ticked in, the raster(s) will be added to the map canvas.

Close

This button closes the plugin.

Output

Two different files (geoTIFF) will be saved if also wall aspect is calculated. The figure below shows an example of input data (left) and the resulting wall height raster (right).

Example of input data (left) and the resulting wall height raster (right).

Remarks

  • Wall pixels will be located ‘inside’ of the building footprint.
  • The aspect algorithm gives reasonable result but improvements could be made by e.g. using a vector line layer which could be used to populate the wall pixels with aspect values.

References

  • Goodwin NR, Coops NC, Tooke TR, Christen A, Voogt JA (2009) Characterizing urban surface cover and structure with airborne lidar technology. Can J Remote Sens 35:297–309 Link to paper
  • Lindberg, F., Jonsson, P. & Honjo, T. and Wästberg, D. (2015) Solar energy on building envelopes - 3D modelling in a 2D environment. Solar Energy. 115 (2015) 369–378 Link to paper
  • Lindberg, F., Grimmond, C.S.B. and Martilli, A. (2015) Sunlit fractions on urban facets - Impact of spatial resolution and approach. Urban Climate. DOI 10.1016/j.uclim.2014.11.006 Link to paper