Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation
To remotely monitor vegetation at temporal and spatial resolutions unobtainable with satellite-based systems, near remote sensing systems must be employed. To this extent we used Normalized Difference Vegetation Index NDVI sensors and normal digital cameras to monitor the greenness of six different...
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Online Access: | http://hdl.handle.net/11250/2422469 https://doi.org/10.3390/rs8100847 |
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ftninstnf:oai:brage.nina.no:11250/2422469 2023-05-15T14:54:26+02:00 Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation Anderson, Helen Nilsen, Lennart Tømmervik, Hans Karlsen, Stein Rune Nagai, Shin Cooper, Elisabeth J. Svalbard 2016 application/pdf http://hdl.handle.net/11250/2422469 https://doi.org/10.3390/rs8100847 eng eng Remote Sensing 2016, 8(10) urn:issn:2072-4292 http://hdl.handle.net/11250/2422469 https://doi.org/10.3390/rs8100847 cristin:1393448 Navngivelse-Ikkekommersiell 3.0 Norge http://creativecommons.org/licenses/by-nc/3.0/no/ CC-BY-NC 8 Remote Sensing NDVI greenness index RGB camera vegetation phenology active sensors passive sensor Svalbard VDP::Mathematics and natural science: 400::Zoology and botany: 480 Journal article Peer reviewed 2016 ftninstnf https://doi.org/10.3390/rs8100847 2021-12-23T07:17:12Z To remotely monitor vegetation at temporal and spatial resolutions unobtainable with satellite-based systems, near remote sensing systems must be employed. To this extent we used Normalized Difference Vegetation Index NDVI sensors and normal digital cameras to monitor the greenness of six different but common and widespread High Arctic plant species/groups (graminoid/Salix polaris; Cassiope tetragona; Luzula spp.; Dryas octopetala/S. polaris; C. tetragona/D. octopetala; graminoid/bryophyte) during an entire growing season in central Svalbard. Of the three greenness indices (2G_RBi, Channel G% and GRVI) derived from digital camera images, only GRVI showed significant correlations with NDVI in all vegetation types. The GRVI (Green-Red Vegetation Index) is calculated as (GDN ????��������� RDN)/(GDN + RDN) where GDN is Green digital number and RDN is Red digital number. Both NDVI and GRVI successfully recorded timings of the green-up and plant growth periods and senescence in all six plant species/groups. Some differences in phenology between plant species/groups occurred: the mid-season growing period reached a sharp peak in NDVI and GRVI values where graminoids were present, but a prolonged period of higher values occurred with the other plant species/groups. Unlike the other plant species/groups, C. tetragona experienced increased NDVI and GRVI values towards the end of the season. NDVI measured with active and passive sensors were strongly correlated (r2 > 0.70) for the same plant species/groups. Although NDVI recorded by the active sensor was consistently lower than that of the passive sensor for the same plant species/groups, differences were small and likely due to the differing light sources used. Thus, it is evident that GRVI and NDVI measured with active and passive sensors captured similar vegetation attributes of High Arctic plants. Hence, inexpensive digital cameras can be used with passive and active NDVI devices to establish a near remote sensing network for monitoring changing vegetation dynamics in the High Arctic. NDVI; greenness index; RGB camera; vegetation; phenology; active sensor; passive sensor; Svalbard Article in Journal/Newspaper Arctic Cassiope tetragona Dryas octopetala Salix polaris Svalbard Norwegian Institute for Nature Research: Brage NINA Arctic Svalbard Sharp Peak ENVELOPE(-37.900,-37.900,-54.050,-54.050) Remote Sensing 8 10 847 |
institution |
Open Polar |
collection |
Norwegian Institute for Nature Research: Brage NINA |
op_collection_id |
ftninstnf |
language |
English |
topic |
NDVI greenness index RGB camera vegetation phenology active sensors passive sensor Svalbard VDP::Mathematics and natural science: 400::Zoology and botany: 480 |
spellingShingle |
NDVI greenness index RGB camera vegetation phenology active sensors passive sensor Svalbard VDP::Mathematics and natural science: 400::Zoology and botany: 480 Anderson, Helen Nilsen, Lennart Tømmervik, Hans Karlsen, Stein Rune Nagai, Shin Cooper, Elisabeth J. Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
topic_facet |
NDVI greenness index RGB camera vegetation phenology active sensors passive sensor Svalbard VDP::Mathematics and natural science: 400::Zoology and botany: 480 |
description |
To remotely monitor vegetation at temporal and spatial resolutions unobtainable with satellite-based systems, near remote sensing systems must be employed. To this extent we used Normalized Difference Vegetation Index NDVI sensors and normal digital cameras to monitor the greenness of six different but common and widespread High Arctic plant species/groups (graminoid/Salix polaris; Cassiope tetragona; Luzula spp.; Dryas octopetala/S. polaris; C. tetragona/D. octopetala; graminoid/bryophyte) during an entire growing season in central Svalbard. Of the three greenness indices (2G_RBi, Channel G% and GRVI) derived from digital camera images, only GRVI showed significant correlations with NDVI in all vegetation types. The GRVI (Green-Red Vegetation Index) is calculated as (GDN ????��������� RDN)/(GDN + RDN) where GDN is Green digital number and RDN is Red digital number. Both NDVI and GRVI successfully recorded timings of the green-up and plant growth periods and senescence in all six plant species/groups. Some differences in phenology between plant species/groups occurred: the mid-season growing period reached a sharp peak in NDVI and GRVI values where graminoids were present, but a prolonged period of higher values occurred with the other plant species/groups. Unlike the other plant species/groups, C. tetragona experienced increased NDVI and GRVI values towards the end of the season. NDVI measured with active and passive sensors were strongly correlated (r2 > 0.70) for the same plant species/groups. Although NDVI recorded by the active sensor was consistently lower than that of the passive sensor for the same plant species/groups, differences were small and likely due to the differing light sources used. Thus, it is evident that GRVI and NDVI measured with active and passive sensors captured similar vegetation attributes of High Arctic plants. Hence, inexpensive digital cameras can be used with passive and active NDVI devices to establish a near remote sensing network for monitoring changing vegetation dynamics in the High Arctic. NDVI; greenness index; RGB camera; vegetation; phenology; active sensor; passive sensor; Svalbard |
format |
Article in Journal/Newspaper |
author |
Anderson, Helen Nilsen, Lennart Tømmervik, Hans Karlsen, Stein Rune Nagai, Shin Cooper, Elisabeth J. |
author_facet |
Anderson, Helen Nilsen, Lennart Tømmervik, Hans Karlsen, Stein Rune Nagai, Shin Cooper, Elisabeth J. |
author_sort |
Anderson, Helen |
title |
Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
title_short |
Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
title_full |
Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
title_fullStr |
Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
title_full_unstemmed |
Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
title_sort |
using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation |
publishDate |
2016 |
url |
http://hdl.handle.net/11250/2422469 https://doi.org/10.3390/rs8100847 |
op_coverage |
Svalbard |
long_lat |
ENVELOPE(-37.900,-37.900,-54.050,-54.050) |
geographic |
Arctic Svalbard Sharp Peak |
geographic_facet |
Arctic Svalbard Sharp Peak |
genre |
Arctic Cassiope tetragona Dryas octopetala Salix polaris Svalbard |
genre_facet |
Arctic Cassiope tetragona Dryas octopetala Salix polaris Svalbard |
op_source |
8 Remote Sensing |
op_relation |
Remote Sensing 2016, 8(10) urn:issn:2072-4292 http://hdl.handle.net/11250/2422469 https://doi.org/10.3390/rs8100847 cristin:1393448 |
op_rights |
Navngivelse-Ikkekommersiell 3.0 Norge http://creativecommons.org/licenses/by-nc/3.0/no/ |
op_rightsnorm |
CC-BY-NC |
op_doi |
https://doi.org/10.3390/rs8100847 |
container_title |
Remote Sensing |
container_volume |
8 |
container_issue |
10 |
container_start_page |
847 |
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1766326168626135040 |