Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data
Warming induced changes in Arctic vegetation have to date been studied through observational and experimental field studies, leaving significant uncertainty about the representativeness of selected field sites as well as how these field scale findings scale up to the entire pan-Arctic. The purposes...
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ndltd-LACETR-oai-collectionscanada.gc.ca-OWTU.10012-46562013-10-04T04:09:08ZLuus, Kristina2009-08-31T18:32:24Z2009-08-31T18:32:24Z2009-08-31T18:32:24Z2009-08-28http://hdl.handle.net/10012/4656Warming induced changes in Arctic vegetation have to date been studied through observational and experimental field studies, leaving significant uncertainty about the representativeness of selected field sites as well as how these field scale findings scale up to the entire pan-Arctic. The purposes of this thesis were therefore to 1) analyze remotely-sensed/modeled temperature, Normalized Difference Vegeta- tion Indices (NDVI) and plant Net Primary Productivity (NPP) to assess coarse- scale changes (1982–2006) in vegetation; and 2) compare field, remote sensing and model outputs to estimate limitations, challenges and disagreements between data formats. The following data sources were used: • Advanced Very High Resolution Radiometer Polar Pathfinder Extended (APP- x, temperature & albedo) • Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Dif- ference Vegetation Index (NDVI) & Enhanced Vegetation Index (EVI) ) • Landsat Enhanced Thematic Mapper (Landsat ETM, NDVI) • Global Inventory Modeling and Mapping Studies (GIMMS, NDVI) • Global Productivity Efficiency Model (GloPEM, Net Primary Productivity (NPP)) Over the pan-Arctic (1982-2007), increases in temperature, total annual NPP and maximum annual NDVI were observed. Increases in NDVI and NPP were found to be closely related to increases in temperature according to non-parametric Sen’ slope and Mann Kendall tau tests. Variations in phenology were largely non- significant but related to increases in growing season temperature. Snow melt onset and spring onset correspond closely. MODIS, Landsat and GIMMS NDVI data sets agree well, and MODIS EVI and NDVI are very similar for spring and summer at Fosheim Peninsula. GloPEM NPP and field estimates of NPP are poorly correlated, whereas GIMMS NDVI and GloPEM NPP are well correlated, indicating a need for better calibration of model NPP to field data. In summary, increases in pan-Arctic biological productivity indicators were ob- served, and were found to be closely related to recent circumpolar warming. How- ever, these changes appear to be focused in regions from which recent field studies have found significant ecological changes (Alaska), and coarse resolution remote sensing estimates of ecological changes have been less marked in other regions. Dis- crepancies between results from model, field data and remote sensing, as well as central questions remaining about the impact of increases in productivity on soil- vegetation-atmosphere feedbacks, indicate a clear need for continued research into warming induced changes in pan-Arctic vegetation.enRemote sensingPan-Arctic vegetationNet primary productivityPhenologyImpacts of Arctic warmingClimate changeAnalyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field dataThesis or DissertationGeographyMaster of ScienceGeography |
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en |
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Remote sensing Pan-Arctic vegetation Net primary productivity Phenology Impacts of Arctic warming Climate change Geography |
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Remote sensing Pan-Arctic vegetation Net primary productivity Phenology Impacts of Arctic warming Climate change Geography Luus, Kristina Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
description |
Warming induced changes in Arctic vegetation have to date been studied through
observational and experimental field studies, leaving significant uncertainty about
the representativeness of selected field sites as well as how these field scale findings
scale up to the entire pan-Arctic. The purposes of this thesis were therefore to
1) analyze remotely-sensed/modeled temperature, Normalized Difference Vegeta-
tion Indices (NDVI) and plant Net Primary Productivity (NPP) to assess coarse-
scale changes (1982–2006) in vegetation; and 2) compare field, remote sensing and
model outputs to estimate limitations, challenges and disagreements between data
formats. The following data sources were used:
• Advanced Very High Resolution Radiometer Polar Pathfinder Extended (APP-
x, temperature & albedo)
• Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Dif-
ference Vegetation Index (NDVI) & Enhanced Vegetation Index (EVI) )
• Landsat Enhanced Thematic Mapper (Landsat ETM, NDVI)
• Global Inventory Modeling and Mapping Studies (GIMMS, NDVI)
• Global Productivity Efficiency Model (GloPEM, Net Primary Productivity
(NPP))
Over the pan-Arctic (1982-2007), increases in temperature, total annual NPP and
maximum annual NDVI were observed. Increases in NDVI and NPP were found to
be closely related to increases in temperature according to non-parametric Sen’
slope and Mann Kendall tau tests. Variations in phenology were largely non-
significant but related to increases in growing season temperature.
Snow melt onset and spring onset correspond closely. MODIS, Landsat and
GIMMS NDVI data sets agree well, and MODIS EVI and NDVI are very similar
for spring and summer at Fosheim Peninsula. GloPEM NPP and field estimates
of NPP are poorly correlated, whereas GIMMS NDVI and GloPEM NPP are well
correlated, indicating a need for better calibration of model NPP to field data.
In summary, increases in pan-Arctic biological productivity indicators were ob-
served, and were found to be closely related to recent circumpolar warming. How-
ever, these changes appear to be focused in regions from which recent field studies
have found significant ecological changes (Alaska), and coarse resolution remote
sensing estimates of ecological changes have been less marked in other regions. Dis-
crepancies between results from model, field data and remote sensing, as well as
central questions remaining about the impact of increases in productivity on soil-
vegetation-atmosphere feedbacks, indicate a clear need for continued research into
warming induced changes in pan-Arctic vegetation. |
author |
Luus, Kristina |
author_facet |
Luus, Kristina |
author_sort |
Luus, Kristina |
title |
Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
title_short |
Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
title_full |
Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
title_fullStr |
Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
title_full_unstemmed |
Analyzing pan-Arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
title_sort |
analyzing pan-arctic 1982–2006 trends in temperature and bioclimatological indicators (productivity, phenology and vegetation indices) using remote sensing, model and field data |
publishDate |
2009 |
url |
http://hdl.handle.net/10012/4656 |
work_keys_str_mv |
AT luuskristina analyzingpanarctic19822006trendsintemperatureandbioclimatologicalindicatorsproductivityphenologyandvegetationindicesusingremotesensingmodelandfielddata |
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1716600258977333248 |