The high complexity of modern large‐scale construction projects leads their schedules to be sensitive to delays. At underground construction sites, the earthwork processes are vital, as most of the following tasks depend on them. This article presents a method for estimating the productivity of soil removal by combining two technologies based on computer vision: photogrammetry and video analysis. Photogrammetry is applied to create a time series of point clouds throughout excavation, which are used to measure the volume of the excavated soil for daily estimates of productivity. Video analysis is used to generate statistics regarding the construction activities for estimating productivity at finer time scales, when combined with the output from the photogrammetry pipeline. As there may be multiple causes for specific productivity levels, the automated generation of progress and activity statistics from both measurement methods supports interpretation of the productivity estimates. Comparison to annotated ground truth for the tracking and activity monitoring method highlights the reliability of the extracted information. The suitability of the approach is demonstrated by two case studies of real‐world urban excavation projects.

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This paper considers the problem of rapidly generating aircraft trajectories and providing visual tools for analyzing airspace in the presence of convective weather. When strong convective weather elements are present within an airspace, nominal operations are disrupted. Often, such disruptions result in the closure of arrival and departure routes, or major jetways. Partial recovery from disturbances can take the form of ground delay programs and diversions, re-routing of flights to adjacent airspaces, or utilization of other standard arrival and departure fixes. The work presented here proposes two decision support tools to aid air traffic controllers and managers in re-routing traffic. Starting from weather information, partitions of the airspace are constructed whose boundaries and junctions form a Voronoi graph. The graph is used for path planning and provides information on optimal routing policies. Furthermore, the partitions are also used to identify the set of reachable space by airplanes. A key feature of the tool is that a set of optimal solutions and/or informational content is provided, as opposed to simply providing a single optimal trajectory solution or output with limited informative content. The sets of optimal solutions are obtained by finding homotopy classes for flight routing, leading to greater flexibility in decision making. The central thesis of this paper is that graph-based and continuous trajectory-based path planning algorithms can provide the necessary information for strategic and tactical path planning through weather, and are thus well suited as decision support tools for enhancing air traffic management.