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Abstract The Mars 2020 Mastcam‐Z stereo camera investigation enables the generation of three dimension (3D) data products needed to visualize and analyze rocks, outcrops, and other geological and aeolian features. The Planetary Robotics Vision Processing framework “PRoViP” as well as the Instrument Data System on a tactical—sol‐by‐sol—timeframe generate 3D vision products, such as panoramas, distance maps, and textured meshes. Structure‐from‐motion used by the Advanced Science Targeting Toolkit for Robotic Operations (ASTTRO) “Landform” tool and long baseline stereo pipelines add to the 3D vision products' suite on various scales. Data fusion with textured meshes from satellite imagery and 3D data analysis and interpretation of the resulting large 3D data sets is realized by visualization assets like the Planetary Robotics Vision 3D Viewer PRo3D, the 3D Geographical Information System GIS CAMP (Campaign Analysis Mapping and Planning tool), the ASTTRO 3D data presentation and targeting tool, and the Mastcam‐Z planning tool Viewpoint. The pipelines' workflows and the user‐oriented features of the visualization assets, shared across the Mars 2020 mission, are reported. The individual role and interplay, complements and synergies of the individual frameworks are explained. Emphasis is laid on publicly available 3D vision data products and tools. A representative set of scientific use cases from planetary geology, aeolian activity, soil analysis and impact science illustrates the scientific workflow, and public data deployment modes are briefly outlined, demonstrating that 3D vision processing and visualization is an essential mission‐wide asset to solve important planetary science questions such as prevailing wind direction, soil composition, or geologic origin.

The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D visualization techniques, in the environmental domain is unparalleled. Such advanced systems may enable an in-depth interactive exploration of multifaceted geospatial and temporal changes in very large and complex datasets. This is facilitated by a unique synergy of modules for simulation, analysis, and visualization, offering instantaneous visual feedback of transformative changes in the underlying data. However, even if the resulting knowledge holds great potential for supporting decision-making in the environmental domain, the consideration of such techniques still have to find their way to daily practice. To advance these developments, we demonstrate four case studies that portray different opportunities in data visualization and VA in the context of climate research and natural disaster management. Firstly, we focus on 2D data visualization and explorative analysis for climate change detection and urban microclimate development through a comprehensive time series analysis. Secondly, we focus on the combination of 2D and 3D representations and investigations for flood and storm water management through comprehensive flood and heavy rain simulations. These examples are by no means exhaustive, but serve to demonstrate how a VA framework may apply to practical research.