Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space

We presented a methodology for estimating building heights in downtown Vancouver, British Columbia, Canada, using a high definition video (HDV) recorded from the International Space Station. We developed an iterative routine based on multiresolution image segmentation to track the radial displacemen...

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Bibliographic Details
Main Authors: Andrew Plowright, Riccardo Tortini, Nicholas C. Coops
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/7/9/380
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spelling doaj-17b79a90e3f94c70979b9ed92eb515cd2020-11-24T21:51:18ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-09-017938010.3390/ijgi7090380ijgi7090380Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from SpaceAndrew Plowright0Riccardo Tortini1Nicholas C. Coops2Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, CanadaIntegrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, CanadaIntegrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, CanadaWe presented a methodology for estimating building heights in downtown Vancouver, British Columbia, Canada, using a high definition video (HDV) recorded from the International Space Station. We developed an iterative routine based on multiresolution image segmentation to track the radial displacement of building roofs over the course of the HDV, and to predict the building heights using an ordinary least-squares regression model. The linear relationship between the length of the tracking vector and the height of the buildings was excellent (r2 ≤ 0.89, RMSE ≤ 8.85 m, p < 0.01). Notably, the accuracy of the height estimates was not improved considerably beyond 10 s of outline tracking, revealing an optimal video length for estimating the height or elevation of terrestrial features. HDVs are demonstrated to be a viable and effective data source for target tracking and building height prediction when high resolution imagery, spectral information, and/or topographic data from other sources are not available.http://www.mdpi.com/2220-9964/7/9/380high definition videoInternational Space Station (ISS)multiresolution segmentationbuilding trackingheight estimate
collection DOAJ
language English
format Article
sources DOAJ
author Andrew Plowright
Riccardo Tortini
Nicholas C. Coops
spellingShingle Andrew Plowright
Riccardo Tortini
Nicholas C. Coops
Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space
ISPRS International Journal of Geo-Information
high definition video
International Space Station (ISS)
multiresolution segmentation
building tracking
height estimate
author_facet Andrew Plowright
Riccardo Tortini
Nicholas C. Coops
author_sort Andrew Plowright
title Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space
title_short Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space
title_full Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space
title_fullStr Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space
title_full_unstemmed Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space
title_sort determining optimal video length for the estimation of building height through radial displacement measurement from space
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2018-09-01
description We presented a methodology for estimating building heights in downtown Vancouver, British Columbia, Canada, using a high definition video (HDV) recorded from the International Space Station. We developed an iterative routine based on multiresolution image segmentation to track the radial displacement of building roofs over the course of the HDV, and to predict the building heights using an ordinary least-squares regression model. The linear relationship between the length of the tracking vector and the height of the buildings was excellent (r2 ≤ 0.89, RMSE ≤ 8.85 m, p < 0.01). Notably, the accuracy of the height estimates was not improved considerably beyond 10 s of outline tracking, revealing an optimal video length for estimating the height or elevation of terrestrial features. HDVs are demonstrated to be a viable and effective data source for target tracking and building height prediction when high resolution imagery, spectral information, and/or topographic data from other sources are not available.
topic high definition video
International Space Station (ISS)
multiresolution segmentation
building tracking
height estimate
url http://www.mdpi.com/2220-9964/7/9/380
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