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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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 |
_version_ |
1776197764597678080 |