Upscaling leaf area index in an Arctic landscape through multiscale observations
Monitoring and understanding global change requires a detailed focus on upscaling, the process for extrapolating from the site-specific scale to the smallest scale resolved in regional or global models or earth observing systems. Leaf area index (LAI) is one of the most sensitive determinants of pla...
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Online Access: | https://research.wur.nl/en/publications/upscaling-leaf-area-index-in-an-arctic-landscape-through-multisca https://doi.org/10.1111/j.1365-2486.2008.01590.x |
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ftunivwagenin:oai:library.wur.nl:wurpubs/366882 2024-02-04T09:56:23+01:00 Upscaling leaf area index in an Arctic landscape through multiscale observations Williams, M. Bell, R. Spadavecchia, L. Street, L.E. van Wijk, M.T. 2008 application/pdf https://research.wur.nl/en/publications/upscaling-leaf-area-index-in-an-arctic-landscape-through-multisca https://doi.org/10.1111/j.1365-2486.2008.01590.x en eng https://edepot.wur.nl/32208 https://research.wur.nl/en/publications/upscaling-leaf-area-index-in-an-arctic-landscape-through-multisca doi:10.1111/j.1365-2486.2008.01590.x info:eu-repo/semantics/restrictedAccess Wageningen University & Research Global Change Biology 14 (2008) 7 ISSN: 1354-1013 dynamics ecosystems exchange fertilization model ndvi scale tundra vegetation wet sedge info:eu-repo/semantics/article Article/Letter to editor info:eu-repo/semantics/publishedVersion 2008 ftunivwagenin https://doi.org/10.1111/j.1365-2486.2008.01590.x 2024-01-10T23:24:06Z Monitoring and understanding global change requires a detailed focus on upscaling, the process for extrapolating from the site-specific scale to the smallest scale resolved in regional or global models or earth observing systems. Leaf area index (LAI) is one of the most sensitive determinants of plant production and can vary by an order of magnitude over short distances. The landscape distribution of LAI is generally determined by remote sensing of surface reflectance (e.g. normalized difference vegetation index, NDVI) but the mismatch in scales between ground and satellite measurements complicates LAI upscaling. Here, we describe a series of measurements to quantify the spatial distribution of LAI in a sub-Arctic landscape and then describe the upscaling process and its associated errors. Working from a fine-scale harvest LAI¿NDVI relationship, we collected NDVI data over a 500 m × 500 m catchment in the Swedish Arctic, at resolutions from 0.2 to 9.0 m in a nested sampling design. NDVI scaled linearly, so that NDVI at any scale was a simple average of multiple NDVI measurements taken at finer scales. The LAI¿NDVI relationship was scale invariant from 1.5 to 9.0 m resolution. Thus, a single exponential LAI¿NDVI relationship was valid at all these scales, with similar prediction errors. Vegetation patches were of a scale of 0.5 m and at measurement scales coarser than this, there was a sharp drop in LAI variance. Landsat NDVI data for the study catchment correlated significantly, but poorly, with ground-based measurements. A variety of techniques were used to construct LAI maps, including interpolation by inverse distance weighting, ordinary Kriging, External Drift Kriging using Landsat data, and direct estimation from a Landsat NDVI¿LAI calibration. All methods produced similar LAI estimates and overall errors. However, Kriging approaches also generated maps of LAI estimation error based on semivariograms. The spatial variability of this Arctic landscape was such that local measurements assimilated by Kriging ... Article in Journal/Newspaper Arctic Arctic Tundra Wageningen UR (University & Research Centre): Digital Library Arctic Global Change Biology 14 7 1517 1530 |
institution |
Open Polar |
collection |
Wageningen UR (University & Research Centre): Digital Library |
op_collection_id |
ftunivwagenin |
language |
English |
topic |
dynamics ecosystems exchange fertilization model ndvi scale tundra vegetation wet sedge |
spellingShingle |
dynamics ecosystems exchange fertilization model ndvi scale tundra vegetation wet sedge Williams, M. Bell, R. Spadavecchia, L. Street, L.E. van Wijk, M.T. Upscaling leaf area index in an Arctic landscape through multiscale observations |
topic_facet |
dynamics ecosystems exchange fertilization model ndvi scale tundra vegetation wet sedge |
description |
Monitoring and understanding global change requires a detailed focus on upscaling, the process for extrapolating from the site-specific scale to the smallest scale resolved in regional or global models or earth observing systems. Leaf area index (LAI) is one of the most sensitive determinants of plant production and can vary by an order of magnitude over short distances. The landscape distribution of LAI is generally determined by remote sensing of surface reflectance (e.g. normalized difference vegetation index, NDVI) but the mismatch in scales between ground and satellite measurements complicates LAI upscaling. Here, we describe a series of measurements to quantify the spatial distribution of LAI in a sub-Arctic landscape and then describe the upscaling process and its associated errors. Working from a fine-scale harvest LAI¿NDVI relationship, we collected NDVI data over a 500 m × 500 m catchment in the Swedish Arctic, at resolutions from 0.2 to 9.0 m in a nested sampling design. NDVI scaled linearly, so that NDVI at any scale was a simple average of multiple NDVI measurements taken at finer scales. The LAI¿NDVI relationship was scale invariant from 1.5 to 9.0 m resolution. Thus, a single exponential LAI¿NDVI relationship was valid at all these scales, with similar prediction errors. Vegetation patches were of a scale of 0.5 m and at measurement scales coarser than this, there was a sharp drop in LAI variance. Landsat NDVI data for the study catchment correlated significantly, but poorly, with ground-based measurements. A variety of techniques were used to construct LAI maps, including interpolation by inverse distance weighting, ordinary Kriging, External Drift Kriging using Landsat data, and direct estimation from a Landsat NDVI¿LAI calibration. All methods produced similar LAI estimates and overall errors. However, Kriging approaches also generated maps of LAI estimation error based on semivariograms. The spatial variability of this Arctic landscape was such that local measurements assimilated by Kriging ... |
format |
Article in Journal/Newspaper |
author |
Williams, M. Bell, R. Spadavecchia, L. Street, L.E. van Wijk, M.T. |
author_facet |
Williams, M. Bell, R. Spadavecchia, L. Street, L.E. van Wijk, M.T. |
author_sort |
Williams, M. |
title |
Upscaling leaf area index in an Arctic landscape through multiscale observations |
title_short |
Upscaling leaf area index in an Arctic landscape through multiscale observations |
title_full |
Upscaling leaf area index in an Arctic landscape through multiscale observations |
title_fullStr |
Upscaling leaf area index in an Arctic landscape through multiscale observations |
title_full_unstemmed |
Upscaling leaf area index in an Arctic landscape through multiscale observations |
title_sort |
upscaling leaf area index in an arctic landscape through multiscale observations |
publishDate |
2008 |
url |
https://research.wur.nl/en/publications/upscaling-leaf-area-index-in-an-arctic-landscape-through-multisca https://doi.org/10.1111/j.1365-2486.2008.01590.x |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic Tundra |
genre_facet |
Arctic Arctic Tundra |
op_source |
Global Change Biology 14 (2008) 7 ISSN: 1354-1013 |
op_relation |
https://edepot.wur.nl/32208 https://research.wur.nl/en/publications/upscaling-leaf-area-index-in-an-arctic-landscape-through-multisca doi:10.1111/j.1365-2486.2008.01590.x |
op_rights |
info:eu-repo/semantics/restrictedAccess Wageningen University & Research |
op_doi |
https://doi.org/10.1111/j.1365-2486.2008.01590.x |
container_title |
Global Change Biology |
container_volume |
14 |
container_issue |
7 |
container_start_page |
1517 |
op_container_end_page |
1530 |
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1789960918662119424 |