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Sensors 2018, 18(11), 3960; https://doi.org/10.3390/s18113960

Roof Shape Classification from LiDAR and Satellite Image Data Fusion Using Supervised Learning

Robotics Program, University of Michigan, Ann Arbor, MI 48109, USA
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Received: 9 October 2018 / Revised: 3 November 2018 / Accepted: 13 November 2018 / Published: 15 November 2018
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Abstract

Geographic information systems (GIS) provide accurate maps of terrain, roads, waterways, and building footprints and heights. Aircraft, particularly small unmanned aircraft systems (UAS), can exploit this and additional information such as building roof structure to improve navigation accuracy and safely perform contingency landings particularly in urban regions. However, building roof structure is not fully provided in maps. This paper proposes a method to automatically label building roof shape from publicly available GIS data. Satellite imagery and airborne LiDAR data are processed and manually labeled to create a diverse annotated roof image dataset for small to large urban cities. Multiple convolutional neural network (CNN) architectures are trained and tested, with the best performing networks providing a condensed feature set for support vector machine and decision tree classifiers. Satellite image and LiDAR data fusion is shown to provide greater classification accuracy than using either data type alone. Model confidence thresholds are adjusted leading to significant increases in models precision. Networks trained from roof data in Witten, Germany and Manhattan (New York City) are evaluated on independent data from these cities and Ann Arbor, Michigan. View Full-Text
Keywords: geographical information system (GIS); LiDAR; machine vision; machine learning; unmanned aircraft systems (UAS); drones; maps; safety geographical information system (GIS); LiDAR; machine vision; machine learning; unmanned aircraft systems (UAS); drones; maps; safety
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Castagno, J.; Atkins, E. Roof Shape Classification from LiDAR and Satellite Image Data Fusion Using Supervised Learning. Sensors 2018, 18, 3960.

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