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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Canadian Science Publishing
2022
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Online Access: | https://doi.org/10.1139/as-2021-0061 https://doaj.org/article/8c54ce860c2644c5919a24420dc2be04 |
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ftdoajarticles:oai:doaj.org/article:8c54ce860c2644c5919a24420dc2be04 2023-05-15T14:23:47+02:00 Using drone mapping to evaluate error of plot-based field surveys and its effects on moderate spatial resolution remote sensing retrieval of lichen cover Darren Pouliot Mao Mao Robert H. Fraser Blair Kennedy Sylvain G. Leblanc Liming He Wenjun Chen 2022-12-01T00:00:00Z https://doi.org/10.1139/as-2021-0061 https://doaj.org/article/8c54ce860c2644c5919a24420dc2be04 EN FR eng fre Canadian Science Publishing https://cdnsciencepub.com/doi/10.1139/as-2021-0061 https://doaj.org/toc/2368-7460 doi:10.1139/as-2021-0061 2368-7460 https://doaj.org/article/8c54ce860c2644c5919a24420dc2be04 Arctic Science, Vol 8, Iss 4, Pp 1276-1287 (2022) lichen cover sampling error Landsat Sentinel-2 drones Environmental sciences GE1-350 Environmental engineering TA170-171 article 2022 ftdoajarticles https://doi.org/10.1139/as-2021-0061 2022-12-30T20:12:35Z 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 Directory of Open Access Journals: DOAJ Articles Canada Arctic Science |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English French |
topic |
lichen cover sampling error Landsat Sentinel-2 drones Environmental sciences GE1-350 Environmental engineering TA170-171 |
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lichen cover sampling error Landsat Sentinel-2 drones Environmental sciences GE1-350 Environmental engineering TA170-171 Darren Pouliot Mao Mao Robert H. Fraser Blair Kennedy Sylvain G. Leblanc Liming He Wenjun Chen 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 |
lichen cover sampling error Landsat Sentinel-2 drones Environmental sciences GE1-350 Environmental engineering TA170-171 |
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 |
Darren Pouliot Mao Mao Robert H. Fraser Blair Kennedy Sylvain G. Leblanc Liming He Wenjun Chen |
author_facet |
Darren Pouliot Mao Mao Robert H. Fraser Blair Kennedy Sylvain G. Leblanc Liming He Wenjun Chen |
author_sort |
Darren Pouliot |
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 |
https://doi.org/10.1139/as-2021-0061 https://doaj.org/article/8c54ce860c2644c5919a24420dc2be04 |
geographic |
Canada |
geographic_facet |
Canada |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Arctic Science, Vol 8, Iss 4, Pp 1276-1287 (2022) |
op_relation |
https://cdnsciencepub.com/doi/10.1139/as-2021-0061 https://doaj.org/toc/2368-7460 doi:10.1139/as-2021-0061 2368-7460 https://doaj.org/article/8c54ce860c2644c5919a24420dc2be04 |
op_doi |
https://doi.org/10.1139/as-2021-0061 |
container_title |
Arctic Science |
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1766296274932334592 |