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Using High Resolution LiDAR Data and a Flux Footprint Parameterization to Scale Evapotranspiration Estimates to Lower Pixel Resolutions

Sutherland, George ; Chasmer, Laura ; Kljun, Natascha LU orcid ; Devito, Kevin J. and Petrone, Richard M. (2017) In Canadian Journal of Remote Sensing 43(2). p.215-229
Abstract
Over the last several decades the hydrologically sensitive Boreal Plains ecoregion of Western Canada has experienced significant warming and drying. To better predict implications of land cover changes on evapotranspiration (ET) and future water resources in this region, high resolution light detection and ranging and energy balance data are used here to spatially parameterize the Penman-Monteith ET model. Within a 5 km × 5 km area of peatland ecosystems, riparian boundaries, and upland mixedwood forests, the influence of land cover heterogeneity on the accuracy of modeled ET is examined at pixel sizes of 1, 10, 25, 250, 500, and 1,000 m, representing resolutions common to popular satellite products (SPOT, Landsat, and MODIS). Modeled ET... (More)
Over the last several decades the hydrologically sensitive Boreal Plains ecoregion of Western Canada has experienced significant warming and drying. To better predict implications of land cover changes on evapotranspiration (ET) and future water resources in this region, high resolution light detection and ranging and energy balance data are used here to spatially parameterize the Penman-Monteith ET model. Within a 5 km × 5 km area of peatland ecosystems, riparian boundaries, and upland mixedwood forests, the influence of land cover heterogeneity on the accuracy of modeled ET is examined at pixel sizes of 1, 10, 25, 250, 500, and 1,000 m, representing resolutions common to popular satellite products (SPOT, Landsat, and MODIS). Modeled ET was compared with tower-based eddy covariance measurements using a weighted flux footprint model. Errors range from 10% to 36% of measured fluxes and results indicate that sensors with small pixel sizes (1 m) offer significantly better accuracy in large heterogeneous flux footprints, while a wider range of pixel sizes (<25 m) can be suitably applied to smaller homogeneous footprints. Mid (250 m) and coarse (>500 m) pixel sizes offered significantly less accuracy, although changes in pixel size within this range offered comparable results. (Less)
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author
; ; ; and
publishing date
type
Contribution to journal
publication status
published
subject
in
Canadian Journal of Remote Sensing
volume
43
issue
2
pages
215 - 229
publisher
Taylor & Francis
external identifiers
  • scopus:85014790503
ISSN
1712-7971
DOI
10.1080/07038992.2017.1291338
language
English
LU publication?
no
id
5cd71531-a99c-490f-88d6-e9d7d2283dc1
date added to LUP
2018-04-16 14:40:17
date last changed
2022-02-22 17:37:40
@article{5cd71531-a99c-490f-88d6-e9d7d2283dc1,
  abstract     = {{Over the last several decades the hydrologically sensitive Boreal Plains ecoregion of Western Canada has experienced significant warming and drying. To better predict implications of land cover changes on evapotranspiration (ET) and future water resources in this region, high resolution light detection and ranging and energy balance data are used here to spatially parameterize the Penman-Monteith ET model. Within a 5 km × 5 km area of peatland ecosystems, riparian boundaries, and upland mixedwood forests, the influence of land cover heterogeneity on the accuracy of modeled ET is examined at pixel sizes of 1, 10, 25, 250, 500, and 1,000 m, representing resolutions common to popular satellite products (SPOT, Landsat, and MODIS). Modeled ET was compared with tower-based eddy covariance measurements using a weighted flux footprint model. Errors range from 10% to 36% of measured fluxes and results indicate that sensors with small pixel sizes (1 m) offer significantly better accuracy in large heterogeneous flux footprints, while a wider range of pixel sizes (&lt;25 m) can be suitably applied to smaller homogeneous footprints. Mid (250 m) and coarse (&gt;500 m) pixel sizes offered significantly less accuracy, although changes in pixel size within this range offered comparable results.}},
  author       = {{Sutherland, George and Chasmer, Laura and Kljun, Natascha and Devito, Kevin J. and Petrone, Richard M.}},
  issn         = {{1712-7971}},
  language     = {{eng}},
  month        = {{03}},
  number       = {{2}},
  pages        = {{215--229}},
  publisher    = {{Taylor & Francis}},
  series       = {{Canadian Journal of Remote Sensing}},
  title        = {{Using High Resolution LiDAR Data and a Flux Footprint Parameterization to Scale Evapotranspiration Estimates to Lower Pixel Resolutions}},
  url          = {{http://dx.doi.org/10.1080/07038992.2017.1291338}},
  doi          = {{10.1080/07038992.2017.1291338}},
  volume       = {{43}},
  year         = {{2017}},
}