Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets
Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detec...
Published in: | Remote Sensing |
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2021
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Online Access: | http://www.osti.gov/servlets/purl/1328281 https://www.osti.gov/biblio/1328281 https://doi.org/10.3390/rs8090733 |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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54 ENVIRONMENTAL SCIENCES |
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54 ENVIRONMENTAL SCIENCES Langford, Zachary Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Kumar, Jitendra Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Hoffman, Forrest Oak Ridge National Lab. , Oak Ridge, TN . Computer Science and Mathematics Division and Climate Change Science Inst. Norby, Richard J. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Wullschleger, Stan D. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Sloan, Victoria L. Univ. of Bristol, Bristol . Dept. of Civil Engineering Iversen, Colleen M. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover of PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting ... |
author |
Langford, Zachary Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Kumar, Jitendra Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Hoffman, Forrest Oak Ridge National Lab. , Oak Ridge, TN . Computer Science and Mathematics Division and Climate Change Science Inst. Norby, Richard J. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Wullschleger, Stan D. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Sloan, Victoria L. Univ. of Bristol, Bristol . Dept. of Civil Engineering Iversen, Colleen M. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. |
author_facet |
Langford, Zachary Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Kumar, Jitendra Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Hoffman, Forrest Oak Ridge National Lab. , Oak Ridge, TN . Computer Science and Mathematics Division and Climate Change Science Inst. Norby, Richard J. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Wullschleger, Stan D. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Sloan, Victoria L. Univ. of Bristol, Bristol . Dept. of Civil Engineering Iversen, Colleen M. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. |
author_sort |
Langford, Zachary Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. |
title |
Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets |
title_short |
Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets |
title_full |
Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets |
title_fullStr |
Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets |
title_full_unstemmed |
Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets |
title_sort |
mapping arctic plant functional type distributions in the barrow environmental observatory using worldview-2 and lidar datasets |
publishDate |
2021 |
url |
http://www.osti.gov/servlets/purl/1328281 https://www.osti.gov/biblio/1328281 https://doi.org/10.3390/rs8090733 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Tundra |
genre_facet |
Arctic Tundra |
op_relation |
http://www.osti.gov/servlets/purl/1328281 https://www.osti.gov/biblio/1328281 https://doi.org/10.3390/rs8090733 doi:10.3390/rs8090733 |
op_doi |
https://doi.org/10.3390/rs8090733 |
container_title |
Remote Sensing |
container_volume |
8 |
container_issue |
9 |
container_start_page |
733 |
_version_ |
1772812144755081216 |
spelling |
ftosti:oai:osti.gov:1328281 2023-07-30T04:01:24+02:00 Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets Langford, Zachary Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Kumar, Jitendra Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Hoffman, Forrest Oak Ridge National Lab. , Oak Ridge, TN . Computer Science and Mathematics Division and Climate Change Science Inst. Norby, Richard J. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Wullschleger, Stan D. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. Sloan, Victoria L. Univ. of Bristol, Bristol . Dept. of Civil Engineering Iversen, Colleen M. Univ. of Tennessee, Knoxville, TN . Bredesen Center for Interdisciplinary Research and Graduate Education; Oak Ridge National Lab. , Oak Ridge, TN . Environmental Sciences Division and Climate Change Science Inst. 2021-12-30 application/pdf http://www.osti.gov/servlets/purl/1328281 https://www.osti.gov/biblio/1328281 https://doi.org/10.3390/rs8090733 unknown http://www.osti.gov/servlets/purl/1328281 https://www.osti.gov/biblio/1328281 https://doi.org/10.3390/rs8090733 doi:10.3390/rs8090733 54 ENVIRONMENTAL SCIENCES 2021 ftosti https://doi.org/10.3390/rs8090733 2023-07-11T09:15:39Z Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover of PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting ... Other/Unknown Material Arctic Tundra SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic Remote Sensing 8 9 733 |