Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover

Effective plot-based field sampling involves a trade-off between implementation efficiency and sample error. Optimal field sampling therefore requires quantifying the sample error under various sampling designs. For remote sensing applications, it is also important to understand how field sample err...

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Published in:Arctic Science
Main Authors: Pouliot, Darren, Mao, Mao, Fraser, Robert H., Kennedy, Blair, Leblanc, Sylvain G., He, Liming, Chen, Wenjun
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2022
Subjects:
Online Access:http://dx.doi.org/10.1139/as-2021-0061
https://cdnsciencepub.com/doi/full-xml/10.1139/as-2021-0061
https://cdnsciencepub.com/doi/pdf/10.1139/as-2021-0061
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spelling crcansciencepubl:10.1139/as-2021-0061 2023-12-17T10:22:42+01:00 Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover Pouliot, Darren Mao, Mao Fraser, Robert H. Kennedy, Blair Leblanc, Sylvain G. He, Liming Chen, Wenjun 2022 http://dx.doi.org/10.1139/as-2021-0061 https://cdnsciencepub.com/doi/full-xml/10.1139/as-2021-0061 https://cdnsciencepub.com/doi/pdf/10.1139/as-2021-0061 en eng Canadian Science Publishing https://creativecommons.org/licenses/by/4.0/deed.en_GB Arctic Science ISSN 2368-7460 General Earth and Planetary Sciences General Agricultural and Biological Sciences General Environmental Science journal-article 2022 crcansciencepubl https://doi.org/10.1139/as-2021-0061 2023-11-19T13:38:30Z Effective plot-based field sampling involves a trade-off between implementation efficiency and sample error. Optimal field sampling therefore requires quantifying the sample error under various sampling designs. For remote sensing applications, it is also important to understand how field sample error and training sample size (the number of pixels) affect the retrieval of surface properties. In this research, drone imagery was used to simulate field plots and investigate plot sampling error for forage lichen cover in relation to plot size, number of plots, and sampling strategy. The effect of this error on remote sensing-based lichen cover retrieval was evaluated using varying training sampling sizes in two different study regions in northern Canada. Results showed that cover with high spatial variability increased the number of plots or plot size required to achieve a specified level of error. For lichen cover retrieval at moderate spatial resolution (10–30 m), field sampling (plot size and number of plots) did not have as significant of an effect as regional differences (spectral separability of cover types), sensor, and the number of pixels used for model training. This plot simulation approach using drone images can be applied to other surface properties and regions to provide field sampling guidance. Article in Journal/Newspaper Arctic Canadian Science Publishing (via Crossref) Canada Arctic Science
institution Open Polar
collection Canadian Science Publishing (via Crossref)
op_collection_id crcansciencepubl
language English
topic General Earth and Planetary Sciences
General Agricultural and Biological Sciences
General Environmental Science
spellingShingle General Earth and Planetary Sciences
General Agricultural and Biological Sciences
General Environmental Science
Pouliot, Darren
Mao, Mao
Fraser, Robert H.
Kennedy, Blair
Leblanc, Sylvain G.
He, Liming
Chen, Wenjun
Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
topic_facet General Earth and Planetary Sciences
General Agricultural and Biological Sciences
General Environmental Science
description Effective plot-based field sampling involves a trade-off between implementation efficiency and sample error. Optimal field sampling therefore requires quantifying the sample error under various sampling designs. For remote sensing applications, it is also important to understand how field sample error and training sample size (the number of pixels) affect the retrieval of surface properties. In this research, drone imagery was used to simulate field plots and investigate plot sampling error for forage lichen cover in relation to plot size, number of plots, and sampling strategy. The effect of this error on remote sensing-based lichen cover retrieval was evaluated using varying training sampling sizes in two different study regions in northern Canada. Results showed that cover with high spatial variability increased the number of plots or plot size required to achieve a specified level of error. For lichen cover retrieval at moderate spatial resolution (10–30 m), field sampling (plot size and number of plots) did not have as significant of an effect as regional differences (spectral separability of cover types), sensor, and the number of pixels used for model training. This plot simulation approach using drone images can be applied to other surface properties and regions to provide field sampling guidance.
format Article in Journal/Newspaper
author Pouliot, Darren
Mao, Mao
Fraser, Robert H.
Kennedy, Blair
Leblanc, Sylvain G.
He, Liming
Chen, Wenjun
author_facet Pouliot, Darren
Mao, Mao
Fraser, Robert H.
Kennedy, Blair
Leblanc, Sylvain G.
He, Liming
Chen, Wenjun
author_sort Pouliot, Darren
title Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
title_short Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
title_full Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
title_fullStr Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
title_full_unstemmed Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
title_sort using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover
publisher Canadian Science Publishing
publishDate 2022
url http://dx.doi.org/10.1139/as-2021-0061
https://cdnsciencepub.com/doi/full-xml/10.1139/as-2021-0061
https://cdnsciencepub.com/doi/pdf/10.1139/as-2021-0061
geographic Canada
geographic_facet Canada
genre Arctic
genre_facet Arctic
op_source Arctic Science
ISSN 2368-7460
op_rights https://creativecommons.org/licenses/by/4.0/deed.en_GB
op_doi https://doi.org/10.1139/as-2021-0061
container_title Arctic Science
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