Direct multispectral photogrammetry for UAV-based snow depth measurements
Due to the changing climate and inherent atypically occurring meteorological events in the Arctic regions, more accurate snow quality predictions are needed in order to support the Sámi reindeer herding communities in northern Sweden that struggle to adapt to the rapidly changing Arctic climate. Sp...
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ftkthstockholm:oai:DiVA.org:kth-254566 2023-05-15T15:01:46+02:00 Direct multispectral photogrammetry for UAV-based snow depth measurements Direkt multispektral fotogrammetri för UAV-baserade snödjupsmätningar Maier, Kathrin 2019 application/pdf http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254566 eng eng KTH, Geoinformatik TRITA-ABE-MBT 19567 http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254566 info:eu-repo/semantics/openAccess Unmanned Aerial Vehicles (UAV) snow depth direct photogrammetry multispectral imagery cryosphere Other Social Sciences not elsewhere specified Övrig annan samhällsvetenskap Student thesis info:eu-repo/semantics/bachelorThesis text 2019 ftkthstockholm 2022-08-11T12:38:40Z Due to the changing climate and inherent atypically occurring meteorological events in the Arctic regions, more accurate snow quality predictions are needed in order to support the Sámi reindeer herding communities in northern Sweden that struggle to adapt to the rapidly changing Arctic climate. Spatial snow depth distribution is a crucial parameter not only to assess snow quality but also for multiple environmental research and social land use purposes. This contrasts with the current availability of affordable and efficient snow monitoring methods to estimate such an extremely variable parameter in both space and time. In this thesis, a novel approach to determine spatial snow depth distribution in challenging alpine terrain is presented and tested during a field campaign performed in Tarfala, Sweden in April 2019. A multispectral camera capturing five spectral bands in wavelengths between 470 and 860 nanometers on board of a small Unmanned Aerial Vehicle is deployed to derive 3D snow surface models via photogrammetric image processing techniques. The main advantage over conventional photogrammetric surveys is the utilization of accurate RTK positioning technology that enables direct georeferencing of the images, and thus eliminates the need for ground control points and dangerous and time-consuming fieldwork. The continuous snow depth distribution is retrieved by differencing two digital surface models corresponding to the snow-free and snow-covered study areas. An extensive error assessment based on ground measurements is performed including an analysis of the impact of multispectral imagery. Uncertainties and non-transparencies due to a black-box environment in the photogrammetric processing are, however, present, but accounted for during the error source analysis. The results of this project demonstrate that the proposed methodology is capable of producing high-resolution 3D snow-covered surface models (< 7 cm/pixel) of alpine areas up to 8 hectares in a fast, reliable and cost-efficient way. The ... Bachelor Thesis Arctic Northern Sweden Tarfala Royal Institute of Technology, Stockholm: KTHs Publication Database DiVA Arctic Tarfala ENVELOPE(18.608,18.608,67.914,67.914) |
institution |
Open Polar |
collection |
Royal Institute of Technology, Stockholm: KTHs Publication Database DiVA |
op_collection_id |
ftkthstockholm |
language |
English |
topic |
Unmanned Aerial Vehicles (UAV) snow depth direct photogrammetry multispectral imagery cryosphere Other Social Sciences not elsewhere specified Övrig annan samhällsvetenskap |
spellingShingle |
Unmanned Aerial Vehicles (UAV) snow depth direct photogrammetry multispectral imagery cryosphere Other Social Sciences not elsewhere specified Övrig annan samhällsvetenskap Maier, Kathrin Direct multispectral photogrammetry for UAV-based snow depth measurements |
topic_facet |
Unmanned Aerial Vehicles (UAV) snow depth direct photogrammetry multispectral imagery cryosphere Other Social Sciences not elsewhere specified Övrig annan samhällsvetenskap |
description |
Due to the changing climate and inherent atypically occurring meteorological events in the Arctic regions, more accurate snow quality predictions are needed in order to support the Sámi reindeer herding communities in northern Sweden that struggle to adapt to the rapidly changing Arctic climate. Spatial snow depth distribution is a crucial parameter not only to assess snow quality but also for multiple environmental research and social land use purposes. This contrasts with the current availability of affordable and efficient snow monitoring methods to estimate such an extremely variable parameter in both space and time. In this thesis, a novel approach to determine spatial snow depth distribution in challenging alpine terrain is presented and tested during a field campaign performed in Tarfala, Sweden in April 2019. A multispectral camera capturing five spectral bands in wavelengths between 470 and 860 nanometers on board of a small Unmanned Aerial Vehicle is deployed to derive 3D snow surface models via photogrammetric image processing techniques. The main advantage over conventional photogrammetric surveys is the utilization of accurate RTK positioning technology that enables direct georeferencing of the images, and thus eliminates the need for ground control points and dangerous and time-consuming fieldwork. The continuous snow depth distribution is retrieved by differencing two digital surface models corresponding to the snow-free and snow-covered study areas. An extensive error assessment based on ground measurements is performed including an analysis of the impact of multispectral imagery. Uncertainties and non-transparencies due to a black-box environment in the photogrammetric processing are, however, present, but accounted for during the error source analysis. The results of this project demonstrate that the proposed methodology is capable of producing high-resolution 3D snow-covered surface models (< 7 cm/pixel) of alpine areas up to 8 hectares in a fast, reliable and cost-efficient way. The ... |
format |
Bachelor Thesis |
author |
Maier, Kathrin |
author_facet |
Maier, Kathrin |
author_sort |
Maier, Kathrin |
title |
Direct multispectral photogrammetry for UAV-based snow depth measurements |
title_short |
Direct multispectral photogrammetry for UAV-based snow depth measurements |
title_full |
Direct multispectral photogrammetry for UAV-based snow depth measurements |
title_fullStr |
Direct multispectral photogrammetry for UAV-based snow depth measurements |
title_full_unstemmed |
Direct multispectral photogrammetry for UAV-based snow depth measurements |
title_sort |
direct multispectral photogrammetry for uav-based snow depth measurements |
publisher |
KTH, Geoinformatik |
publishDate |
2019 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254566 |
long_lat |
ENVELOPE(18.608,18.608,67.914,67.914) |
geographic |
Arctic Tarfala |
geographic_facet |
Arctic Tarfala |
genre |
Arctic Northern Sweden Tarfala |
genre_facet |
Arctic Northern Sweden Tarfala |
op_relation |
TRITA-ABE-MBT 19567 http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254566 |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1766333782371074048 |