Predicting fire behaviour (in-)directly via plant traits and Remote Sensing

Luuk Blauw, R.S.P. van Logtestijn, H.M. Bartholomeus, L. Kooistra, Hans Cornelissen, R. Aerts

Research output: Contribution to conferenceAbstractAcademic

Abstract

Wildfires have been thoroughly investigated over the past decades and its drivers are well known. That knowledge is important to accurately define carbon emission models and conduct efficient fire management. Although both of these operate on a large scale, most fire research is based on smallscale laboratory experiments and occasionally large-scale field experiments. Yet, satellite RS images are already used to determine global and local fire frequencies, but satellites have a low spatial resolution and cannot be used in fire management. Therefore, airborne RS is used to accurately estimate plant traits and vegetation indices and that could be used to determine plant flammability traits. Accurate RS estimates of flammability traits could provide indirect predictions of fire behaviour. In dry and fire-prone areas, airborne RS could measure plant traits and estimate its sensitivity to fire and associated fire behaviour. We carried out 12 prescribed fires in young and old Scottish heathland, similar to Dutch heathlands, to determine the relation between plant traits, fire behaviour and remote sensing. Our results indicate a strong effect of plant traits on fire behaviour and that fire behaviour could be estimated based on the RS images.
Original languageEnglish
Publication statusPublished - 2017
EventNetherlands Annual Ecology Meeting 2017 - Conference Centre "De Werelt", Lunteren, Netherlands
Duration: 14 Feb 201715 Feb 2017

Conference

ConferenceNetherlands Annual Ecology Meeting 2017
CountryNetherlands
CityLunteren
Period14/02/1715/02/17

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fire behavior
remote sensing
fire management
heathland
carbon emission
vegetation index
wildfire
spatial resolution
prediction

Cite this

Blauw, L., van Logtestijn, R. S. P., Bartholomeus, H. M., Kooistra, L., Cornelissen, H., & Aerts, R. (2017). Predicting fire behaviour (in-)directly via plant traits and Remote Sensing. Abstract from Netherlands Annual Ecology Meeting 2017, Lunteren, Netherlands.
Blauw, Luuk ; van Logtestijn, R.S.P. ; Bartholomeus, H.M. ; Kooistra, L. ; Cornelissen, Hans ; Aerts, R. / Predicting fire behaviour (in-)directly via plant traits and Remote Sensing. Abstract from Netherlands Annual Ecology Meeting 2017, Lunteren, Netherlands.
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title = "Predicting fire behaviour (in-)directly via plant traits and Remote Sensing",
abstract = "Wildfires have been thoroughly investigated over the past decades and its drivers are well known. That knowledge is important to accurately define carbon emission models and conduct efficient fire management. Although both of these operate on a large scale, most fire research is based on smallscale laboratory experiments and occasionally large-scale field experiments. Yet, satellite RS images are already used to determine global and local fire frequencies, but satellites have a low spatial resolution and cannot be used in fire management. Therefore, airborne RS is used to accurately estimate plant traits and vegetation indices and that could be used to determine plant flammability traits. Accurate RS estimates of flammability traits could provide indirect predictions of fire behaviour. In dry and fire-prone areas, airborne RS could measure plant traits and estimate its sensitivity to fire and associated fire behaviour. We carried out 12 prescribed fires in young and old Scottish heathland, similar to Dutch heathlands, to determine the relation between plant traits, fire behaviour and remote sensing. Our results indicate a strong effect of plant traits on fire behaviour and that fire behaviour could be estimated based on the RS images.",
author = "Luuk Blauw and {van Logtestijn}, R.S.P. and H.M. Bartholomeus and L. Kooistra and Hans Cornelissen and R. Aerts",
year = "2017",
language = "English",
note = "Netherlands Annual Ecology Meeting 2017 ; Conference date: 14-02-2017 Through 15-02-2017",

}

Blauw, L, van Logtestijn, RSP, Bartholomeus, HM, Kooistra, L, Cornelissen, H & Aerts, R 2017, 'Predicting fire behaviour (in-)directly via plant traits and Remote Sensing' Netherlands Annual Ecology Meeting 2017, Lunteren, Netherlands, 14/02/17 - 15/02/17, .

Predicting fire behaviour (in-)directly via plant traits and Remote Sensing. / Blauw, Luuk; van Logtestijn, R.S.P.; Bartholomeus, H.M.; Kooistra, L.; Cornelissen, Hans ; Aerts, R.

2017. Abstract from Netherlands Annual Ecology Meeting 2017, Lunteren, Netherlands.

Research output: Contribution to conferenceAbstractAcademic

TY - CONF

T1 - Predicting fire behaviour (in-)directly via plant traits and Remote Sensing

AU - Blauw, Luuk

AU - van Logtestijn, R.S.P.

AU - Bartholomeus, H.M.

AU - Kooistra, L.

AU - Cornelissen, Hans

AU - Aerts, R.

PY - 2017

Y1 - 2017

N2 - Wildfires have been thoroughly investigated over the past decades and its drivers are well known. That knowledge is important to accurately define carbon emission models and conduct efficient fire management. Although both of these operate on a large scale, most fire research is based on smallscale laboratory experiments and occasionally large-scale field experiments. Yet, satellite RS images are already used to determine global and local fire frequencies, but satellites have a low spatial resolution and cannot be used in fire management. Therefore, airborne RS is used to accurately estimate plant traits and vegetation indices and that could be used to determine plant flammability traits. Accurate RS estimates of flammability traits could provide indirect predictions of fire behaviour. In dry and fire-prone areas, airborne RS could measure plant traits and estimate its sensitivity to fire and associated fire behaviour. We carried out 12 prescribed fires in young and old Scottish heathland, similar to Dutch heathlands, to determine the relation between plant traits, fire behaviour and remote sensing. Our results indicate a strong effect of plant traits on fire behaviour and that fire behaviour could be estimated based on the RS images.

AB - Wildfires have been thoroughly investigated over the past decades and its drivers are well known. That knowledge is important to accurately define carbon emission models and conduct efficient fire management. Although both of these operate on a large scale, most fire research is based on smallscale laboratory experiments and occasionally large-scale field experiments. Yet, satellite RS images are already used to determine global and local fire frequencies, but satellites have a low spatial resolution and cannot be used in fire management. Therefore, airborne RS is used to accurately estimate plant traits and vegetation indices and that could be used to determine plant flammability traits. Accurate RS estimates of flammability traits could provide indirect predictions of fire behaviour. In dry and fire-prone areas, airborne RS could measure plant traits and estimate its sensitivity to fire and associated fire behaviour. We carried out 12 prescribed fires in young and old Scottish heathland, similar to Dutch heathlands, to determine the relation between plant traits, fire behaviour and remote sensing. Our results indicate a strong effect of plant traits on fire behaviour and that fire behaviour could be estimated based on the RS images.

M3 - Abstract

ER -

Blauw L, van Logtestijn RSP, Bartholomeus HM, Kooistra L, Cornelissen H, Aerts R. Predicting fire behaviour (in-)directly via plant traits and Remote Sensing. 2017. Abstract from Netherlands Annual Ecology Meeting 2017, Lunteren, Netherlands.