Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing

NOAA Remote Sensing Division’s North Slope, Alaska airborne imaging data is a fantastic geospatial resource for a data-poor coastal region of the Arctic. This collection provides a high-resolution snapshot of a rapidly changing environment that is exhibiting some of highest coastal retreat rates in...

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Main Author: Escarzaga, Stephen
Format: Text
Language:unknown
Published: figshare 2019
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.10325855.v1
https://figshare.com/articles/Recommendations_to_the_Collection_of_Airborne_Imaging_Data_for_the_Optimization_of_Structure-from-Motion_Processing/10325855/1
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spelling ftdatacite:10.6084/m9.figshare.10325855.v1 2023-05-15T15:06:21+02:00 Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing Escarzaga, Stephen 2019 https://dx.doi.org/10.6084/m9.figshare.10325855.v1 https://figshare.com/articles/Recommendations_to_the_Collection_of_Airborne_Imaging_Data_for_the_Optimization_of_Structure-from-Motion_Processing/10325855/1 unknown figshare https://dx.doi.org/10.6084/m9.figshare.10325855 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Environmental Science 90905 Photogrammetry and Remote Sensing FOS Environmental engineering Text article-journal Journal contribution ScholarlyArticle 2019 ftdatacite https://doi.org/10.6084/m9.figshare.10325855.v1 https://doi.org/10.6084/m9.figshare.10325855 2021-11-05T12:55:41Z NOAA Remote Sensing Division’s North Slope, Alaska airborne imaging data is a fantastic geospatial resource for a data-poor coastal region of the Arctic. This collection provides a high-resolution snapshot of a rapidly changing environment that is exhibiting some of highest coastal retreat rates in the United States (Jones et al., 2008; Lantuit et al., 2012; Barnhart et al, 2014; Gibbs & Richmond, 2015). To better understand how raw imaging data from this collection will perform with Structure-from-Motion (SfM) photogrammetry in this area, initial work has been carried out to better understand its strengths and weaknesses in the context of DEM production through SfM workflows. Informed by the results of this initial work and a review of current best practices in the field of SfM photogrammetry for the geosciences, this document presents a collection of recommendations to enhance RSD airborne image collection, processing and dissemination. The goal of this document is to assist in expanding the utility and value of future RSD collections across the Nation’s many coastlines by promoting optimal data collection parameters for SfM photogrammetry. Text Arctic north slope Alaska DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Environmental Science
90905 Photogrammetry and Remote Sensing
FOS Environmental engineering
spellingShingle Environmental Science
90905 Photogrammetry and Remote Sensing
FOS Environmental engineering
Escarzaga, Stephen
Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing
topic_facet Environmental Science
90905 Photogrammetry and Remote Sensing
FOS Environmental engineering
description NOAA Remote Sensing Division’s North Slope, Alaska airborne imaging data is a fantastic geospatial resource for a data-poor coastal region of the Arctic. This collection provides a high-resolution snapshot of a rapidly changing environment that is exhibiting some of highest coastal retreat rates in the United States (Jones et al., 2008; Lantuit et al., 2012; Barnhart et al, 2014; Gibbs & Richmond, 2015). To better understand how raw imaging data from this collection will perform with Structure-from-Motion (SfM) photogrammetry in this area, initial work has been carried out to better understand its strengths and weaknesses in the context of DEM production through SfM workflows. Informed by the results of this initial work and a review of current best practices in the field of SfM photogrammetry for the geosciences, this document presents a collection of recommendations to enhance RSD airborne image collection, processing and dissemination. The goal of this document is to assist in expanding the utility and value of future RSD collections across the Nation’s many coastlines by promoting optimal data collection parameters for SfM photogrammetry.
format Text
author Escarzaga, Stephen
author_facet Escarzaga, Stephen
author_sort Escarzaga, Stephen
title Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing
title_short Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing
title_full Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing
title_fullStr Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing
title_full_unstemmed Recommendations to the Collection of Airborne Imaging Data for the Optimization of Structure-from-Motion Processing
title_sort recommendations to the collection of airborne imaging data for the optimization of structure-from-motion processing
publisher figshare
publishDate 2019
url https://dx.doi.org/10.6084/m9.figshare.10325855.v1
https://figshare.com/articles/Recommendations_to_the_Collection_of_Airborne_Imaging_Data_for_the_Optimization_of_Structure-from-Motion_Processing/10325855/1
geographic Arctic
geographic_facet Arctic
genre Arctic
north slope
Alaska
genre_facet Arctic
north slope
Alaska
op_relation https://dx.doi.org/10.6084/m9.figshare.10325855
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.10325855.v1
https://doi.org/10.6084/m9.figshare.10325855
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