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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Online Access: | http://www.mdpi.com/2220-9964/7/9/380 |
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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 |
work_keys_str_mv |
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