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Computer Science
Computer Graphics

Intuitive Colormaps for Environmental Visualization

Profile image of Roxana BujackRoxana Bujack

2017

https://doi.org/10.2312/ENVIRVIS.20171105
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5 pages

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Abstract

Figure 1: Illustrated here is the process of building a custom colormap for Sentinel2 CIR satellite data of the Wax Lake Delta. Starting from the left, one sees an image of the delta where brighter blue indicate regions with enhanced vegetation. Flow structures in the coastal ocean correspond to regions of enhanced sediment transport. In the central image, a separator pin divides land and water; a choice is made from the blues for the near-shore ocean and from the greens to evoke the land and foliage in the delta. In the finalized image, a brown is used in for the earth and blue variants are added to show greater detail in the water.

Figures (6)
Figure 1: Illustrated here is the process of building a custom colormap for Sentinel2 CIR satellite data of the Wax Lake Delta. Starting fron the left, one sees an image of the delta where brighter blue indicate regions with enhanced vegetation. Flow structures in the coastal ocear correspond to regions of enhanced sediment transport. In the central image, a separator pin divides land and water; a choice is made from the blues for the near-shore ocean and from the greens to evoke the land and foliage in the delta. In the finalized image, a brown is used in fo the earth and blue variants are added to show greater detail in the water.
Figure 1: Illustrated here is the process of building a custom colormap for Sentinel2 CIR satellite data of the Wax Lake Delta. Starting fron the left, one sees an image of the delta where brighter blue indicate regions with enhanced vegetation. Flow structures in the coastal ocear correspond to regions of enhanced sediment transport. In the central image, a separator pin divides land and water; a choice is made from the blues for the near-shore ocean and from the greens to evoke the land and foliage in the delta. In the finalized image, a brown is used in fo the earth and blue variants are added to show greater detail in the water.
Samsel, Turton, Wolfram, Bujack, / Intuitive Colormaps for Environmental Visualization Figure 2: Blue color scales for water and sky. Green color scales for vegetation and water. Brown, red and yellow color scales for earth and air. The XML files for these color scales are available on the SciVisColor website, sciviscolor.org/colormaps.
Samsel, Turton, Wolfram, Bujack, / Intuitive Colormaps for Environmental Visualization Figure 2: Blue color scales for water and sky. Green color scales for vegetation and water. Brown, red and yellow color scales for earth and air. The XML files for these color scales are available on the SciVisColor website, sciviscolor.org/colormaps.
colorscales enable sharing the visualization space. A colorscale that goes through too broad a spectrum creates issues when insufficient color channels are left for encoding all variables or auxiliary infor- mation. Figure 3: This figure shows the construction of a green colorscale with that moves from a warm dark yellow-green through a mid- range cool blue-green and back to a warm light yellow-green. This allows the colorscale to maintain intuitive order while moving be- tween warm and cool greens, shifts that create greater contrast.
colorscales enable sharing the visualization space. A colorscale that goes through too broad a spectrum creates issues when insufficient color channels are left for encoding all variables or auxiliary infor- mation. Figure 3: This figure shows the construction of a green colorscale with that moves from a warm dark yellow-green through a mid- range cool blue-green and back to a warm light yellow-green. This allows the colorscale to maintain intuitive order while moving be- tween warm and cool greens, shifts that create greater contrast.
Table 1: Summary of how the suggested colorscales, tool, and workflow help the environmental scientists face typical visualiza- tion challenges.
Table 1: Summary of how the suggested colorscales, tool, and workflow help the environmental scientists face typical visualiza- tion challenges.
Samsel, Turton, Wolfram, Bujack, / Intuitive Colormaps for Environmental Visualization Figure 4: An MPAS-Ocean visualization of kinetic energy around the Antarctic. Viridis (left) can be compared to a custom colormap using these intuitive colorscales (right). While the hues are simi- ar, the value range is greater on the custom map and is employed twice, once through green and once through blue. Here, the sci- entists welcomed the greater discriminative power created by the uminance changes. While there are benefits to both, our goal is to provide the flexibility to the scientists to assist in resolving their scientific queries.
Samsel, Turton, Wolfram, Bujack, / Intuitive Colormaps for Environmental Visualization Figure 4: An MPAS-Ocean visualization of kinetic energy around the Antarctic. Viridis (left) can be compared to a custom colormap using these intuitive colorscales (right). While the hues are simi- ar, the value range is greater on the custom map and is employed twice, once through green and once through blue. Here, the sci- entists welcomed the greater discriminative power created by the uminance changes. While there are benefits to both, our goal is to provide the flexibility to the scientists to assist in resolving their scientific queries.
Figure 5: Arctic scientists are studying how subtle changes in the topography can lead to significant changes in vegetation type and distribution. This topographical LIDAR data without context is rather an abstract pattern. Rendering in the green and brown palette provides associative clues not available in the standard cool warm. Additionally, identifying the areas of foliage verses dry tundra is quite intuitive.
Figure 5: Arctic scientists are studying how subtle changes in the topography can lead to significant changes in vegetation type and distribution. This topographical LIDAR data without context is rather an abstract pattern. Rendering in the green and brown palette provides associative clues not available in the standard cool warm. Additionally, identifying the areas of foliage verses dry tundra is quite intuitive.

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