Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables
It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodo...
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ftqueensuniv:oai:https://qspace.library.queensu.ca:1974/15920 2024-06-02T08:00:29+00:00 Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables Liu, Nanfeng Geography and Planning Treitz, Paul 2017-06-29T22:05:43Z application/pdf http://hdl.handle.net/1974/15920 eng eng Canadian theses http://hdl.handle.net/1974/15920 CC0 1.0 Universal Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada ProQuest PhD and Master's Theses International Dissemination Agreement Intellectual Property Guidelines at Queen's University Copying and Preserving Your Thesis This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner. http://creativecommons.org/publicdomain/zero/1.0/ Remote sensing Arctic Percent vegetation cover fAPAR Vegetation thesis 2017 ftqueensuniv 2024-05-06T10:47:32Z It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic overestimation of 0.08, which was attributed to PAR ... Thesis Arctic Baffin Island Baffin Climate change Melville Island Queen's University, Ontario: QSpace Arctic Baffin Island Cape Bounty ENVELOPE(-109.542,-109.542,74.863,74.863) Sabine Peninsula ENVELOPE(-109.505,-109.505,76.335,76.335) |
institution |
Open Polar |
collection |
Queen's University, Ontario: QSpace |
op_collection_id |
ftqueensuniv |
language |
English |
topic |
Remote sensing Arctic Percent vegetation cover fAPAR Vegetation |
spellingShingle |
Remote sensing Arctic Percent vegetation cover fAPAR Vegetation Liu, Nanfeng Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables |
topic_facet |
Remote sensing Arctic Percent vegetation cover fAPAR Vegetation |
description |
It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic overestimation of 0.08, which was attributed to PAR ... |
author2 |
Geography and Planning Treitz, Paul |
format |
Thesis |
author |
Liu, Nanfeng |
author_facet |
Liu, Nanfeng |
author_sort |
Liu, Nanfeng |
title |
Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables |
title_short |
Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables |
title_full |
Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables |
title_fullStr |
Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables |
title_full_unstemmed |
Remote Sensing of the Canadian Arctic: Modelling Biophysical Variables |
title_sort |
remote sensing of the canadian arctic: modelling biophysical variables |
publishDate |
2017 |
url |
http://hdl.handle.net/1974/15920 |
long_lat |
ENVELOPE(-109.542,-109.542,74.863,74.863) ENVELOPE(-109.505,-109.505,76.335,76.335) |
geographic |
Arctic Baffin Island Cape Bounty Sabine Peninsula |
geographic_facet |
Arctic Baffin Island Cape Bounty Sabine Peninsula |
genre |
Arctic Baffin Island Baffin Climate change Melville Island |
genre_facet |
Arctic Baffin Island Baffin Climate change Melville Island |
op_relation |
Canadian theses http://hdl.handle.net/1974/15920 |
op_rights |
CC0 1.0 Universal Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada ProQuest PhD and Master's Theses International Dissemination Agreement Intellectual Property Guidelines at Queen's University Copying and Preserving Your Thesis This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner. http://creativecommons.org/publicdomain/zero/1.0/ |
_version_ |
1800744501382217728 |