While satellite-based remote sensing techniques are often used for studying and visualizing the urban heat island effect, they are limited in terms of resolution, view bias, and revisit times. In comparison, modern UAVs equipped with infrared sensors allow very fine-scale (cm) data to be collected over smaller areas and can provide the means for a full 3D thermal reconstruction over limited spatial extents. Irrespective of the data collection method, the thermal properties of cities are typically visually represented using color, although the choice of colormap varies widely. Previous cartographic research has demonstrated that colormap and other cartographic choices affect people's understanding. This research study examines the difference in map reading performance between satellite and drone-sourced thermal pseudo-color images for three map reading tasks, the impact of color map selection on map reading, and the potential benefits of adding shading to thermal maps using high-resolution digital surface models for improved interaction. Participants expressed a preference for the newly designed rainbow-style color map "turbo" and the FLIR "ironbow" colormap. However, user preferences were not strongly related to map reading performance, and differences were partly explained by the extra information afforded by multi-hue and shading-enhanced images. / Master of Science / While satellite-based remote sensing techniques are often used for studying and visualizing the urban heat island effect, they are limited in terms of resolution, view bias, and revisit times. In comparison, modern drones or Unmanned Aerial Vehicles (UAVs) equipped with infrared sensors allow very fine-scale (cm) data to be collected over smaller areas and can provide the means for a full 3D thermal reconstruction over a small area. Irrespective of the data collection method, the thermal properties of cities are typically visually represented using color, although the choice of colormap varies widely. Previous cartographic research has demonstrated that colormap and other cartographic choices affect people's understanding. This research study examines the difference in map reading performance between satellite and drone-sourced thermal pseudo-color images for three map reading tasks, the impact of color map selection on map reading, and the potential benefits of adding hillshade augmentation to thermal maps using high-resolution digital surface models for improved interaction. Participants expressed a preference for the newly designed rainbow-style color map "turbo" and the FLIR "ironbow" colormap. However, user preferences were not strongly related to map reading performance, and differences were partly explained by the extra information afforded by multi-hue and shading-enhanced images.

Continuous colormaps are integral parts of many visualization techniques, such as heat-maps, surface plots, and flow visualization. Despite that the critiques of rainbow colormaps have been around and well-acknowledged for three decades, rainbow colormaps are still widely used today. One reason behind the resilience of rainbow colormaps is the lack of tools for users to create a continuous colormap that encodes semantics specific to the application concerned. In this paper, we present a web-based software system, CCC-Tool (short for Charting Continuous Colormaps) under the URL https://ccctool.com, for creating, editing, and analyzing such application-specific colormaps. We introduce the notion of “colormap pecification (CMS)” that maintains the essential semantics required for defining a color mapping scheme. We provide users with a set of advanced utilities for constructing CMS’s with various levels of complexity, examining their quality attributes using different plots, and exporting them to external application software. We present two case studies, demonstrating that the CCC-Tool can help domain scientists as well as visualization experts in designing semantically-rich colormaps.