Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires
Peatlands have been degrading globally, which is increasing pressure on restoration measures and monitoring. New monitoring methods are needed because traditional methods are time-consuming, typically lack a spatial aspect, and are sometimes even impossible to execute in practice. Remote sensing has...
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ftluke:oai:jukuri.luke.fi:10024/553834 2024-02-11T10:07:06+01:00 Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires Isoaho, Aleksi Ikkala, Lauri Marttila, Hannu Hjort, Jan Kumpula, Timo Korpelainen, Pasi Räsänen, Aleksi orcid:0009-0008-0618-0889 orcid:0000-0002-3629-1837 4100311110 Luonnonvarakeskus 12 p. true https://jukuri.luke.fi/handle/10024/553834 en eng Elsevier BV Remote Sensing Applications: Society and Environment 10.1016/j.rsase.2023.101059 2352-9385 32 101059 https://jukuri.luke.fi/handle/10024/553834 URN:NBN:fi-fe20230918130141 CC BY 4.0 Remote sensing Multispectral Thermal Peatland Hydrology Restoration publication fi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|sv=A1 Originalartikel i en vetenskaplig tidskrift|en=A1 Journal article (refereed), original research| fi=Publisher's version|sv=Publisher's version|en=Publisher's version| ftluke 2024-01-25T00:07:23Z Peatlands have been degrading globally, which is increasing pressure on restoration measures and monitoring. New monitoring methods are needed because traditional methods are time-consuming, typically lack a spatial aspect, and are sometimes even impossible to execute in practice. Remote sensing has been implemented to monitor hydrological patterns and restoration impacts, but there is a lack of studies that combine multi-sensor ultra-high-resolution data to assess the spatial patterns of hydrology in peatlands. We combine optical, thermal, and topographic unmanned aerial vehicle data to spatially model the water table level (WTL) in unditched open peatlands in northern Finland suffering from adjacent drainage. We predict the WTL with a linear regression model with a moderate fit and accuracy (R2 = 0.69, RMSE = 3.85 cm) and construct maps to assess the spatial success of restoration. We demonstrate that thermal-optical trapezoid-based wetness models and optical bands are strongly correlated with the WTL, but topography-based wetness indices do not. We suggest that the developed method could be used for quantitative restoration assessment, but before-after restoration imagery is required to verify our findings. 2023 Article in Journal/Newspaper Northern Finland Natural Resources Institute Finland: Jukuri |
institution |
Open Polar |
collection |
Natural Resources Institute Finland: Jukuri |
op_collection_id |
ftluke |
language |
English |
topic |
Remote sensing Multispectral Thermal Peatland Hydrology Restoration |
spellingShingle |
Remote sensing Multispectral Thermal Peatland Hydrology Restoration Isoaho, Aleksi Ikkala, Lauri Marttila, Hannu Hjort, Jan Kumpula, Timo Korpelainen, Pasi Räsänen, Aleksi Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
topic_facet |
Remote sensing Multispectral Thermal Peatland Hydrology Restoration |
description |
Peatlands have been degrading globally, which is increasing pressure on restoration measures and monitoring. New monitoring methods are needed because traditional methods are time-consuming, typically lack a spatial aspect, and are sometimes even impossible to execute in practice. Remote sensing has been implemented to monitor hydrological patterns and restoration impacts, but there is a lack of studies that combine multi-sensor ultra-high-resolution data to assess the spatial patterns of hydrology in peatlands. We combine optical, thermal, and topographic unmanned aerial vehicle data to spatially model the water table level (WTL) in unditched open peatlands in northern Finland suffering from adjacent drainage. We predict the WTL with a linear regression model with a moderate fit and accuracy (R2 = 0.69, RMSE = 3.85 cm) and construct maps to assess the spatial success of restoration. We demonstrate that thermal-optical trapezoid-based wetness models and optical bands are strongly correlated with the WTL, but topography-based wetness indices do not. We suggest that the developed method could be used for quantitative restoration assessment, but before-after restoration imagery is required to verify our findings. 2023 |
author2 |
orcid:0009-0008-0618-0889 orcid:0000-0002-3629-1837 4100311110 Luonnonvarakeskus |
format |
Article in Journal/Newspaper |
author |
Isoaho, Aleksi Ikkala, Lauri Marttila, Hannu Hjort, Jan Kumpula, Timo Korpelainen, Pasi Räsänen, Aleksi |
author_facet |
Isoaho, Aleksi Ikkala, Lauri Marttila, Hannu Hjort, Jan Kumpula, Timo Korpelainen, Pasi Räsänen, Aleksi |
author_sort |
Isoaho, Aleksi |
title |
Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
title_short |
Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
title_full |
Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
title_fullStr |
Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
title_full_unstemmed |
Spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
title_sort |
spatial water table level modelling with multi-sensor unmanned aerial vehicle data in boreal aapa mires |
publisher |
Elsevier BV |
url |
https://jukuri.luke.fi/handle/10024/553834 |
genre |
Northern Finland |
genre_facet |
Northern Finland |
op_relation |
Remote Sensing Applications: Society and Environment 10.1016/j.rsase.2023.101059 2352-9385 32 101059 https://jukuri.luke.fi/handle/10024/553834 URN:NBN:fi-fe20230918130141 |
op_rights |
CC BY 4.0 |
_version_ |
1790605245305323520 |