Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

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Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R-2 0.21-0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R-2 0.33-0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.

Alkuperäiskielienglanti
LehtiInternational Journal of Remote Sensing
Vuosikerta40
Numero3
Sivut1175-1199
Sivumäärä25
ISSN0143-1161
DOI - pysyväislinkit
TilaJulkaistu - 1 helmikuuta 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

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title = "Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling",
abstract = "Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R-2 0.21-0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R-2 0.33-0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.",
keywords = "LEAF-AREA INDEX, SPECTRAL REFLECTANCE, VEGETATION INDEX, HERSCHEL ISLAND, TUNDRA, CARBON, PHYTOMASS, SOIL, STORAGE, COVER, 1172 Environmental sciences",
author = "Tuomas R{\"a}s{\"a}nen and Sari Juutinen and Mika Aurela and Tarmo Virtanen",
year = "2019",
month = "2",
day = "1",
doi = "10.1080/01431161.2018.1524176",
language = "English",
volume = "40",
pages = "1175--1199",
journal = "International Journal of Remote Sensing",
issn = "0143-1161",
publisher = "TAYLOR & FRANCIS LTD",
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Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling. / Räsänen, Tuomas; Juutinen, Sari; Aurela, Mika; Virtanen, Tarmo.

julkaisussa: International Journal of Remote Sensing, Vuosikerta 40, Nro 3, 01.02.2019, s. 1175-1199.

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling

AU - Räsänen, Tuomas

AU - Juutinen, Sari

AU - Aurela, Mika

AU - Virtanen, Tarmo

PY - 2019/2/1

Y1 - 2019/2/1

N2 - Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R-2 0.21-0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R-2 0.33-0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.

AB - Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R-2 0.21-0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R-2 0.33-0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.

KW - LEAF-AREA INDEX

KW - SPECTRAL REFLECTANCE

KW - VEGETATION INDEX

KW - HERSCHEL ISLAND

KW - TUNDRA

KW - CARBON

KW - PHYTOMASS

KW - SOIL

KW - STORAGE

KW - COVER

KW - 1172 Environmental sciences

U2 - 10.1080/01431161.2018.1524176

DO - 10.1080/01431161.2018.1524176

M3 - Article

VL - 40

SP - 1175

EP - 1199

JO - International Journal of Remote Sensing

JF - International Journal of Remote Sensing

SN - 0143-1161

IS - 3

ER -