In urban microclimate research, ground-based thermography is used to gain insight into the spatial distribution of surface temperatures of various materials. Taking snapshots over a certain time span helps experts to observe the temporal thermo-radiative behavior of the monitored surface elements and therefore supports decisions on possible optimizations, e.g., improving the thermal comfort in a neighborhood. Appropriate visualization techniques facilitate decision-making and are thus crucial in the optimization process. In this study, we present a tool that eases the extraction of thermo-radiative features from multi-temporal thermographs taken from a monitored scene. Assisted by our tool, users can identify, choose, and register thermo-radiative features for each time step according to their individual research needs. The features’ temporal development is then visualized using a directed graph that encodes topological events as well as each feature’s size and summarizing statistics. To enhance this summary, a comprehensive animated sequence emphasizes the spatiotemporal behavior of the most significant thermo-radiative features. Salient developments are visually embedded and highlighted in the original infrared images, which are blended in an animation from time step to time step. Since we enable the user to interact with the data in a flexible way, noisy and low resolution image data sets can also be processed.
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The authors would like to thank the anonymous reviewers of this paper for their valuable feedback. This research was supported by the German Science Foundation (DFG, Grant 1131) as part of the International Graduate School (IRTG 1131) at University of Kaiserslautern, Germany. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsoring agency.
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Häb, K., Feige, N.H., Huettenberger, L.S. et al. Visualizing the temporal development of thermo-radiative features on ground-based thermographs. Environ Earth Sci 72, 3781–3793 (2014). https://doi.org/10.1007/s12665-014-3472-6