A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity
Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity...
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ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2561816 2023-05-15T14:28:58+02:00 A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity Karlsen, Stein Rune Anderson, Helen B. van der Wal, René Hansen, Brage Bremset 2018 http://hdl.handle.net/11250/2561816 https://doi.org/10.1088/1748-9326/aa9f75 eng eng IOP Publishing http://iopscience.iop.org/article/10.1088/1748-9326/aa9f75 Norges forskningsråd: 216051 Norges forskningsråd: 244647 Norges forskningsråd: 223257 urn:issn:1748-9326 http://hdl.handle.net/11250/2561816 https://doi.org/10.1088/1748-9326/aa9f75 cristin:1542498 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no CC-BY 13 Environmental Research Letters Journal article Peer reviewed 2018 ftntnutrondheimi https://doi.org/10.1088/1748-9326/aa9f75 2019-09-17T06:54:01Z Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-NDVI data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R2 = 0.51 and 0.44, respectively). The commonly used 'maximum NDVI' plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images. publishedVersion Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Article in Journal/Newspaper Arctic Archipelago Arctic Svalbard NTNU Open Archive (Norwegian University of Science and Technology) Arctic Svalbard Environmental Research Letters 13 2 025011 |
institution |
Open Polar |
collection |
NTNU Open Archive (Norwegian University of Science and Technology) |
op_collection_id |
ftntnutrondheimi |
language |
English |
description |
Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-NDVI data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R2 = 0.51 and 0.44, respectively). The commonly used 'maximum NDVI' plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images. publishedVersion Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
format |
Article in Journal/Newspaper |
author |
Karlsen, Stein Rune Anderson, Helen B. van der Wal, René Hansen, Brage Bremset |
spellingShingle |
Karlsen, Stein Rune Anderson, Helen B. van der Wal, René Hansen, Brage Bremset A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
author_facet |
Karlsen, Stein Rune Anderson, Helen B. van der Wal, René Hansen, Brage Bremset |
author_sort |
Karlsen, Stein Rune |
title |
A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
title_short |
A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
title_full |
A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
title_fullStr |
A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
title_full_unstemmed |
A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
title_sort |
new ndvi measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity |
publisher |
IOP Publishing |
publishDate |
2018 |
url |
http://hdl.handle.net/11250/2561816 https://doi.org/10.1088/1748-9326/aa9f75 |
geographic |
Arctic Svalbard |
geographic_facet |
Arctic Svalbard |
genre |
Arctic Archipelago Arctic Svalbard |
genre_facet |
Arctic Archipelago Arctic Svalbard |
op_source |
13 Environmental Research Letters |
op_relation |
http://iopscience.iop.org/article/10.1088/1748-9326/aa9f75 Norges forskningsråd: 216051 Norges forskningsråd: 244647 Norges forskningsråd: 223257 urn:issn:1748-9326 http://hdl.handle.net/11250/2561816 https://doi.org/10.1088/1748-9326/aa9f75 cristin:1542498 |
op_rights |
Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1088/1748-9326/aa9f75 |
container_title |
Environmental Research Letters |
container_volume |
13 |
container_issue |
2 |
container_start_page |
025011 |
_version_ |
1766303076892803072 |