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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Published in:Environmental Research Letters
Main Authors: Stein Rune Karlsen, Helen B Anderson, René van der Wal, Brage Bremset Hansen
Format: Article in Journal/Newspaper
Language:English
Published: IOP Publishing 2018
Subjects:
Q
Online Access:https://doi.org/10.1088/1748-9326/aa9f75
https://doaj.org/article/22f92a00fdc94bcda071afcc1f9de984
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spelling ftdoajarticles:oai:doaj.org/article:22f92a00fdc94bcda071afcc1f9de984 2023-09-05T13:16:00+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 Stein Rune Karlsen Helen B Anderson René van der Wal Brage Bremset Hansen 2018-01-01T00:00:00Z https://doi.org/10.1088/1748-9326/aa9f75 https://doaj.org/article/22f92a00fdc94bcda071afcc1f9de984 EN eng IOP Publishing https://doi.org/10.1088/1748-9326/aa9f75 https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/aa9f75 1748-9326 https://doaj.org/article/22f92a00fdc94bcda071afcc1f9de984 Environmental Research Letters, Vol 13, Iss 2, p 025011 (2018) cloud cover plant productivity MODIS NDVI svalbard high arctic Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 article 2018 ftdoajarticles https://doi.org/10.1088/1748-9326/aa9f75 2023-08-13T00:37:31Z 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-Normalised Difference Vegetation Index (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 R ^2 = 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. Article in Journal/Newspaper Arctic Archipelago Arctic Svalbard Directory of Open Access Journals: DOAJ Articles Arctic Svalbard Environmental Research Letters 13 2 025011
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic cloud cover
plant productivity
MODIS
NDVI
svalbard
high arctic
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Science
Q
Physics
QC1-999
spellingShingle cloud cover
plant productivity
MODIS
NDVI
svalbard
high arctic
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Science
Q
Physics
QC1-999
Stein Rune Karlsen
Helen B Anderson
René van der Wal
Brage Bremset Hansen
A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity
topic_facet cloud cover
plant productivity
MODIS
NDVI
svalbard
high arctic
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Science
Q
Physics
QC1-999
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-Normalised Difference Vegetation Index (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 R ^2 = 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.
format Article in Journal/Newspaper
author Stein Rune Karlsen
Helen B Anderson
René van der Wal
Brage Bremset Hansen
author_facet Stein Rune Karlsen
Helen B Anderson
René van der Wal
Brage Bremset Hansen
author_sort Stein Rune Karlsen
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 https://doi.org/10.1088/1748-9326/aa9f75
https://doaj.org/article/22f92a00fdc94bcda071afcc1f9de984
geographic Arctic
Svalbard
geographic_facet Arctic
Svalbard
genre Arctic Archipelago
Arctic
Svalbard
genre_facet Arctic Archipelago
Arctic
Svalbard
op_source Environmental Research Letters, Vol 13, Iss 2, p 025011 (2018)
op_relation https://doi.org/10.1088/1748-9326/aa9f75
https://doaj.org/toc/1748-9326
doi:10.1088/1748-9326/aa9f75
1748-9326
https://doaj.org/article/22f92a00fdc94bcda071afcc1f9de984
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
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