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Candaş, A B and Tokdemir, O B (2022) Automated Identification of Vagueness in the FIDIC Silver Book Conditions of Contract. Journal of Construction Engineering and Management, 148(04).

Guevara, J, Herrera, L and Salazar, J (2022) Interorganizational Sponsor Networks in Road and Social Infrastructure PPP Equity Markets. Journal of Construction Engineering and Management, 148(04).

Han, S, Jiang, Y and Bai, Y (2022) Fast-PGMED: Fast and Dense Elevation Determination for Earthwork Using Drone and Deep Learning. Journal of Construction Engineering and Management, 148(04).

  • Type: Journal Article
  • Keywords: Elevation algorithm; Fully convolutional network; Imaging drones; Multiprocessing; Feature matching;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002256
  • Abstract:
    This paper presents a time- and cost-effective elevation determination method for earthwork operations using ready-to-fly imaging drones and deep learning technologies. The proposed method is named the fast pixel grid/group matching and elevation determination (Fast-PGMED) algorithm. The input data are a pair of approximate 2:1-scale top-view images, and the output is the determined elevation map for the scanned station. Feature matching of the two multiscale images is conducted by calculating correlations between target patch predictions (via DeepMatchNet, a fully convolutional network) and potential target patches (via virtual elevation model). The overall processing time is about 21 s (including 5 s for low-high orthoimage assembly, 3 s for patch feature generation, and 13 s for pixel matching) to process a 2,500-pixel grid, and the generated elevation values are as accurate as photogrammetry (within 5-cm error) but took much less time. Moreover, the developed method has been evaluated with two different drones. Volume measurement was quickly conducted via 2D elevation maps and accurately estimated via dense point clouds and Civil 3D.

Hosseinian, S M, Arjomand, A, Li, C Q and Zhang, G (2022) Developing a Model for Assessing Project Completion Time Reliability during Construction Using Time-Dependent Reliability Theory. Journal of Construction Engineering and Management, 148(04).

Liu, Q, Ye, G, Yang, J, Xiang, Q and Liu, Q (2022) Construction Workers’ Representativeness Heuristic in Decision Making: The Impact of Demographic Factors. Journal of Construction Engineering and Management, 148(04).

Ma, L and Fu, H (2022) A Governance Framework for the Sustainable Delivery of Megaprojects: The Interaction of Megaproject Citizenship Behavior and Contracts. Journal of Construction Engineering and Management, 148(04).

Tiruneh, G G and Fayek, A R (2022) Hybrid GA-MANFIS Model for Organizational Competencies and Performance in Construction. Journal of Construction Engineering and Management, 148(04).

Wang, P, Wang, K, Huang, Y, Fenn, P and Stewart, I (2022) Auditing Construction Cost from an In-Process Perspective Based on a Bayesian Predictive Model. Journal of Construction Engineering and Management, 148(04).

Xie, H, Hong, Y and Brilakis, I (2022) Analysis of User Needs in Time-Related Risk Management for Holistic Project Understanding. Journal of Construction Engineering and Management, 148(04).

Zhang, X and Liu, J (2022) Incentive Mechanism and Value-Added in PPP Projects Considering Financial Institutions’ Early Intervention. Journal of Construction Engineering and Management, 148(04).

Zhu, H, Hwang, B, Ngo, J and Tan, J P S (2022) Applications of Smart Technologies in Construction Project Management. Journal of Construction Engineering and Management, 148(04).