Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Modelling and upscaling ecosystem respiration using thermal cameras and UAVs : Application to a peatland during and after a hot drought

Kelly, Julia LU ; Kljun, Natascha LU orcid ; Eklundh, Lars LU orcid ; Klemedtsson, Leif ; Liljebladh, Bengt ; Olsson, Per Ola LU ; Weslien, Per and Xie, Xianghua (2021) In Agricultural and Forest Meteorology 300.
Abstract

Field-based thermal infrared cameras provide surface temperature information at very high spatial and temporal resolution and could complement existing phenological camera and spectral sensor networks. Since temperature is one of the main drivers of ecosystem respiration (ER), field-based thermal cameras offer a new opportunity to model and upscale ER in unprecedented detail. We present such an approach based on manual chamber CO2 flux measurements and thermal imagery from a tower-based camera and from Unmanned Aerial Vehicle (UAV) flights. Data were collected over two growing seasons, including the hot drought of 2018, for the two main vegetation microforms (hummock and hollow) of a hemi-boreal peatland in Sweden. Thermal... (More)

Field-based thermal infrared cameras provide surface temperature information at very high spatial and temporal resolution and could complement existing phenological camera and spectral sensor networks. Since temperature is one of the main drivers of ecosystem respiration (ER), field-based thermal cameras offer a new opportunity to model and upscale ER in unprecedented detail. We present such an approach based on manual chamber CO2 flux measurements and thermal imagery from a tower-based camera and from Unmanned Aerial Vehicle (UAV) flights. Data were collected over two growing seasons, including the hot drought of 2018, for the two main vegetation microforms (hummock and hollow) of a hemi-boreal peatland in Sweden. Thermal imagery proved suitable for modelling ER in this ecosystem: ER model accuracies were similar when air, soil or surface temperature measurements were used as input. Our findings allowed us to upscale ER using UAV-derived thermal images and we present maps of ER at sub-decimeter resolution (<7 cm). The significantly different ER measured for each microform highlighted the importance of modelling their ER separately. Not accounting for these differences and the microforms' spatial distribution across the peatland led to a bias in upscaled ER of up to 18%. As a result of the severity and timing of the hot drought in 2018, we observed reductions in the ER of both microforms, but more so for hummocks (-48%) than for hollows (-15%), and modelled ER leveled off at high temperatures. These findings indicate that peatland carbon loss during hot droughts may be lower than expected and strongly relates to vegetation composition. The presented upscaling approach offers a new method to analyse how ER varies across a peatland or within a flux-tower footprint, and to interpret biases that occur when using coarse resolution satellite data to upscale chamber or tower-based flux measurements.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
2018 drought, Heatwave, Remote sensing, Spatial heterogeneity, Surface temperature, Thermal imaging
in
Agricultural and Forest Meteorology
volume
300
article number
108330
pages
14 pages
publisher
Elsevier
external identifiers
  • scopus:85099855284
ISSN
0168-1923
DOI
10.1016/j.agrformet.2021.108330
project
GREEN GAP: GREENhouse GAs flux uPscaling - improved understanding of key ecosystem processes using remote sensing and ground-based measurements
language
English
LU publication?
yes
id
3e4f0539-82c8-4b72-bc54-bdb21fe80093
date added to LUP
2021-02-07 14:56:49
date last changed
2022-04-27 00:06:34
@article{3e4f0539-82c8-4b72-bc54-bdb21fe80093,
  abstract     = {{<p>Field-based thermal infrared cameras provide surface temperature information at very high spatial and temporal resolution and could complement existing phenological camera and spectral sensor networks. Since temperature is one of the main drivers of ecosystem respiration (ER), field-based thermal cameras offer a new opportunity to model and upscale ER in unprecedented detail. We present such an approach based on manual chamber CO<sub>2</sub> flux measurements and thermal imagery from a tower-based camera and from Unmanned Aerial Vehicle (UAV) flights. Data were collected over two growing seasons, including the hot drought of 2018, for the two main vegetation microforms (hummock and hollow) of a hemi-boreal peatland in Sweden. Thermal imagery proved suitable for modelling ER in this ecosystem: ER model accuracies were similar when air, soil or surface temperature measurements were used as input. Our findings allowed us to upscale ER using UAV-derived thermal images and we present maps of ER at sub-decimeter resolution (&lt;7 cm). The significantly different ER measured for each microform highlighted the importance of modelling their ER separately. Not accounting for these differences and the microforms' spatial distribution across the peatland led to a bias in upscaled ER of up to 18%. As a result of the severity and timing of the hot drought in 2018, we observed reductions in the ER of both microforms, but more so for hummocks (-48%) than for hollows (-15%), and modelled ER leveled off at high temperatures. These findings indicate that peatland carbon loss during hot droughts may be lower than expected and strongly relates to vegetation composition. The presented upscaling approach offers a new method to analyse how ER varies across a peatland or within a flux-tower footprint, and to interpret biases that occur when using coarse resolution satellite data to upscale chamber or tower-based flux measurements.</p>}},
  author       = {{Kelly, Julia and Kljun, Natascha and Eklundh, Lars and Klemedtsson, Leif and Liljebladh, Bengt and Olsson, Per Ola and Weslien, Per and Xie, Xianghua}},
  issn         = {{0168-1923}},
  keywords     = {{2018 drought; Heatwave; Remote sensing; Spatial heterogeneity; Surface temperature; Thermal imaging}},
  language     = {{eng}},
  month        = {{04}},
  publisher    = {{Elsevier}},
  series       = {{Agricultural and Forest Meteorology}},
  title        = {{Modelling and upscaling ecosystem respiration using thermal cameras and UAVs : Application to a peatland during and after a hot drought}},
  url          = {{http://dx.doi.org/10.1016/j.agrformet.2021.108330}},
  doi          = {{10.1016/j.agrformet.2021.108330}},
  volume       = {{300}},
  year         = {{2021}},
}