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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Language: | English |
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Canadian Science Publishing
2022
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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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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 |
_version_ |
1785551411390447616 |