This tool creates a multiscale topographic position (MTP) image (see here for an example) from three DEVmax rasters of differing spatial scale ranges. Specifically, multiscale_topographic_position_image takes three DEVmax magnitude rasters, created using the max_elevation_deviation tool, as inputs. The three inputs should correspond to the elevation deviations in the local (local
), meso (meso
), and broad (broad
) scale ranges and will be forced into the blue, green, and red colour components of the colour composite output (output
) raster. The image lightness value (lightness
) controls the overall brightness of the output image, as depending on the topography and scale ranges, these images can appear relatively dark. Higher values result in brighter, more colourful output images.
The user may optionally specify an input hillshade raster. When specified, the hillshade will be used to provide a shaded-relief overlaid on top of the coloured multi-scale information, providing a very effective visualization. Any hillshade image may be used for this purpose, but we have found that multi-directional hillshade (multidirectional_hillshade), and specifically those derived using the 360-degree option, can be most effective for this application. However, experimentation is likely needed to find the optimal for each unique data set.
The output images can take some training to interpret correctly and a detailed explanation can be found in Lindsay et al. (2015). Sites within the landscape that occupy prominent topographic positions, either low-lying or elevated, will be apparent by their bright colouring in the MTP image. Those that are coloured more strongly in the blue are promient at the local scale range; locations that are more strongly green coloured are promient at the meso scale; and bright reds in the MTP image are associated with broad-scale landscape prominence. Of course, combination colours are also possible when topography is elevated or low-lying across multiple scale ranges. For example, a yellow area would indicated a site of prominent topographic position across the meso and broadest scale ranges.
Lindsay J, Cockburn J, Russell H. 2015. An integral image approach to performing multi-scale topographic position analysis. Geomorphology, 245: 51-61.
def multiscale_topographic_position_image(self, local: Raster, meso: Raster, broad: Raster, lightness: float = 1.2) -> Raster: ...