Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019
This data set contains the raw files from flight RU_ALN_TR1_FL007R. The remote sensing imagery is collected using uncrewed aerial vehicles at a series of fire perimeters in larch forests located in northeastern Siberia in 2018 and 2019. Images were collected using visible sensors (blue, green, and r...
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NSF Arctic Data Center
2021
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Online Access: | https://dx.doi.org/10.18739/a2k35mf52 https://arcticdata.io/catalog/view/doi:10.18739/A2K35MF52 |
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ftdatacite:10.18739/a2k35mf52 2023-05-15T15:05:21+02:00 Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 Loranty, Michael Forbath, Elena Talucci, Anna Alexander, Heather DeMarco, Jennie Hewitt, Rebecca Lichstein, Jeremy Mack, Michelle Paulson, Alison McEwan, Ryan 2021 text/xml https://dx.doi.org/10.18739/a2k35mf52 https://arcticdata.io/catalog/view/doi:10.18739/A2K35MF52 en eng NSF Arctic Data Center FORESTS FIRE ECOLOGY VEGETATION COVER VEGETATION INDEX REMOTE SENSING UAV dataset Dataset 2021 ftdatacite https://doi.org/10.18739/a2k35mf52 2022-02-08T13:50:26Z This data set contains the raw files from flight RU_ALN_TR1_FL007R. The remote sensing imagery is collected using uncrewed aerial vehicles at a series of fire perimeters in larch forests located in northeastern Siberia in 2018 and 2019. Images were collected using visible sensors (blue, green, and red wavelengths) and multispectral sensors (green, red, red-edge, and near-infrared wavelengths). The data were collected perpendicular to fire perimeter boundaries in order to characterize variation vegetation composition and structure between burned and burned forests, and as a function of distance from the unburned forest edge. The resulting images are co-located with field observations of ecosystem properties collected as part of this project that are posted in a related data set (Alexander et al, 2018). Heather Alexander, Jennie DeMarco, Rebecca Hewitt, Jeremy Lichstein, Michael Loranty, et al. 2018. Fire influences on forest recovery and associated climate feedbacks in Siberian Larch Forests, Russia, June-July 2018. Arctic Data Center. urn:uuid:a5de1514-78d3-449f-aad1-2ff8f8d0fb27. Dataset Arctic Siberia DataCite Metadata Store (German National Library of Science and Technology) Arctic Jeremy ENVELOPE(-68.838,-68.838,-69.402,-69.402) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
FORESTS FIRE ECOLOGY VEGETATION COVER VEGETATION INDEX REMOTE SENSING UAV |
spellingShingle |
FORESTS FIRE ECOLOGY VEGETATION COVER VEGETATION INDEX REMOTE SENSING UAV Loranty, Michael Forbath, Elena Talucci, Anna Alexander, Heather DeMarco, Jennie Hewitt, Rebecca Lichstein, Jeremy Mack, Michelle Paulson, Alison McEwan, Ryan Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 |
topic_facet |
FORESTS FIRE ECOLOGY VEGETATION COVER VEGETATION INDEX REMOTE SENSING UAV |
description |
This data set contains the raw files from flight RU_ALN_TR1_FL007R. The remote sensing imagery is collected using uncrewed aerial vehicles at a series of fire perimeters in larch forests located in northeastern Siberia in 2018 and 2019. Images were collected using visible sensors (blue, green, and red wavelengths) and multispectral sensors (green, red, red-edge, and near-infrared wavelengths). The data were collected perpendicular to fire perimeter boundaries in order to characterize variation vegetation composition and structure between burned and burned forests, and as a function of distance from the unburned forest edge. The resulting images are co-located with field observations of ecosystem properties collected as part of this project that are posted in a related data set (Alexander et al, 2018). Heather Alexander, Jennie DeMarco, Rebecca Hewitt, Jeremy Lichstein, Michael Loranty, et al. 2018. Fire influences on forest recovery and associated climate feedbacks in Siberian Larch Forests, Russia, June-July 2018. Arctic Data Center. urn:uuid:a5de1514-78d3-449f-aad1-2ff8f8d0fb27. |
format |
Dataset |
author |
Loranty, Michael Forbath, Elena Talucci, Anna Alexander, Heather DeMarco, Jennie Hewitt, Rebecca Lichstein, Jeremy Mack, Michelle Paulson, Alison McEwan, Ryan |
author_facet |
Loranty, Michael Forbath, Elena Talucci, Anna Alexander, Heather DeMarco, Jennie Hewitt, Rebecca Lichstein, Jeremy Mack, Michelle Paulson, Alison McEwan, Ryan |
author_sort |
Loranty, Michael |
title |
Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 |
title_short |
Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 |
title_full |
Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 |
title_fullStr |
Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 |
title_full_unstemmed |
Raw files from flight RU_BP_TR2_FL012R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019 |
title_sort |
raw files from flight ru_bp_tr2_fl012r of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in siberian larch forests 2018-2019 |
publisher |
NSF Arctic Data Center |
publishDate |
2021 |
url |
https://dx.doi.org/10.18739/a2k35mf52 https://arcticdata.io/catalog/view/doi:10.18739/A2K35MF52 |
long_lat |
ENVELOPE(-68.838,-68.838,-69.402,-69.402) |
geographic |
Arctic Jeremy |
geographic_facet |
Arctic Jeremy |
genre |
Arctic Siberia |
genre_facet |
Arctic Siberia |
op_doi |
https://doi.org/10.18739/a2k35mf52 |
_version_ |
1766337057941094400 |