10 Jun 2022

Inland Waterway Network Mapping of AIS Data for Freight Transportation Planning

Abstract: Travel demand models (TDMs) with freight forecasts estimate performance metrics for competing infrastructure investments and potential policy changes. Unfortunately, freight TDMs fail to represent non-truck modes with levels of detail adequate for multi-modal infrastructure and policy evaluation. Recent expansions in the availability of maritime movement data, i.e. Automatic Identification System (AIS), make it possible to expand and improve representation of maritime modes within freight TDMs. AIS may be used to track vessel locations as timestamped latitude–longitude points. For estimation, calibration and validation of freight TDMs, this work identifies vessel trips by applying network mapping (map-matching) heuristics to AIS data. The automated methods are evaluated on a 747-mile inland waterway network, with AIS data representing 88% of vessel activity. Inspection of 3820 AIS trajectories was used to train the heuristic parameters including stop time, duration and location. Validation shows 84·0% accuracy in detecting stops at ports and 83·5% accuracy in identifying trips crossing locks. The resulting map-matched vessel trips may be applied to generate origin–destination matrices, calculate time impedances, etc. The proposed methods are transferable to waterways or maritime port systems, as AIS continues to grow.

31 Mar 2022

Continued Investigation of Thermal and Lidar Surveys of Building Infrastructure

ABSTRACT: We conducted a combined lidar and thermal infrared survey from both ground-based and Unmanned Aerial System (UAS) platforms at McMurdo Station, Antarctica, in February 2020 to assess the building thermal envelope and infrastructure of the Crary Lab and the wet utility corridor (utilidor). These high-accuracy, coregistered data produced a 3-D model with assigned temperature values for measured surfaces, useful in identifying thermal anomalies and areas for potential improvements and for assessing building and utilidor infrastructure by locating and quantifying areas settlement and structural anomalies. The ground-based survey of the Crary Lab was similar to previous work performed by the team at both Palmer (2015) and South Pole (2017) Stations. The UAS platform focused on approximately 10,500 linear-feet of utilidor throughout McMurdo Station. The datasets of the two survey areas overlapped, allowing us to combine them into a single, georeferenced 3-D model of McMurdo Station. Coincident exterior temperature and atmospheric measurements and Global Navigation Satellite System real-time kinematic surveys provided further insights. Finally, we assessed the thermal envelope of the Crary Lab and the structural features of the utilidor. The resulting dataset is available for analysis and quantification.

14 Apr 2020

PUBLICATION NOTIFICATION: Coincidence Processing of Photon-Sensitive Mapping Lidar Data

 Link: http://dx.doi.org/10.21079/11681/35599 Report Number: ERDC/GRL TR-20-1Title: Coincidence Processing of Photon-Sensitive Mapping Lidar DataBy Christian Marchant, Ryan Kirkpatrick, and David OberApproved for Public Release; Distribution is Unlimited February 2020Abstract: Photon-sensitive mapping lidar systems are able to image at greater