Ghent University Academic Bibliography

Advanced

Thermal remote sensing imagery in permafrost studies

Ruben Van De Kerchove UGent, Rudi Goossens UGent, Alain De Wulf UGent, Jean Bourgeois UGent and Wouter Gheyle UGent (2009) REMOTE SENSING FOR A CHANGING EUROPE. p.313-320
abstract
Mountain permafrost modelling in remote, continental mountain ranges (e.g. Russian Altai Mountains) holds several difficulties due to the limitations these environments pose. The lack of meteorological input data and impossibilities for BTS-validations (Bottom Temperatures of winter Snow cover) makes conventional modelling strategies inapplicable. Statistical methods, however, based on correlation coefficients between different parameters, offers good alternative but requires lots of observations to be significant. As a solution, spatially covering land surface temperature (LST) values might be used as a proxy replacing the interpolated air and near ground surface temperatures. This article proposes 2 strategies, one statistical and one adapted TTOP (temperature at the top of permafrost), based on remote sensing data and ground measurements. Although these methods seem promising, they require a detailed understanding of the relation between LST and the air and near ground surface temperature. Therefore, before installing field equipment, we compared filtered MODIS LST time-series with corresponding ground temperature measurements recorded by Sergei Marchenko (Geophysical institute of Alaska, Fairbanks) in the Ulandryk Valley. Despite the cloudy conditions of this test site, a good correlation is showed between both time-series.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
MODIS, LST, Altai, modelling, Permafrost, DERIVATION, BTS MEASUREMENTS, SATELLITE SENSOR DATA, TIME-SERIES
in
REMOTE SENSING FOR A CHANGING EUROPE
editor
Derya Maktav
pages
313 - 320
publisher
IOS Press
place of publication
Amsterdam, The Netherlands
conference name
28th European-Association-of-Remote-Sensing-Laboratories (EARSeL) Symposium and Workshops on Remote Sensing for a Changing Europe
conference location
Istanbul, Turkey
conference start
2008-06-02
conference end
2008-06-05
Web of Science type
Proceedings Paper
Web of Science id
000342298700043
ISBN
9781586039868
DOI
10.3233/978-1-58603-986-8-313
language
English
UGent publication?
yes
classification
P1
VABB id
c:vabb:281803
VABB type
VABB-5
id
806173
handle
http://hdl.handle.net/1854/LU-806173
date created
2009-12-09 20:39:43
date last changed
2014-11-10 13:33:55
@inproceedings{806173,
  abstract     = {Mountain permafrost modelling in remote, continental mountain ranges (e.g. Russian Altai Mountains) holds several difficulties due to the limitations these environments pose. The lack of meteorological input data and impossibilities for BTS-validations (Bottom Temperatures of winter Snow cover) makes conventional modelling strategies inapplicable. Statistical methods, however, based on correlation coefficients between different parameters, offers good alternative but requires lots of observations to be significant. As a solution, spatially covering land surface temperature (LST) values might be used as a proxy replacing the interpolated air and near ground surface temperatures. This article proposes 2 strategies, one statistical and one adapted TTOP (temperature at the top of permafrost), based on remote sensing data and ground measurements. Although these methods seem promising, they require a detailed understanding of the relation between LST and the air and near ground surface temperature. Therefore, before installing field equipment, we compared filtered MODIS LST time-series with corresponding ground temperature measurements recorded by Sergei Marchenko (Geophysical institute of Alaska, Fairbanks) in the Ulandryk Valley. Despite the cloudy conditions of this test site, a good correlation is showed between both time-series.},
  author       = {Van De Kerchove, Ruben and Goossens, Rudi and De Wulf, Alain and Bourgeois, Jean and Gheyle, Wouter},
  booktitle    = {REMOTE SENSING FOR A CHANGING EUROPE},
  editor       = {Maktav, Derya},
  isbn         = {9781586039868},
  keyword      = {MODIS,LST,Altai,modelling,Permafrost,DERIVATION,BTS MEASUREMENTS,SATELLITE SENSOR DATA,TIME-SERIES},
  language     = {eng},
  location     = {Istanbul, Turkey},
  pages        = {313--320},
  publisher    = {IOS Press},
  title        = {Thermal remote sensing imagery in permafrost studies},
  url          = {http://dx.doi.org/10.3233/978-1-58603-986-8-313},
  year         = {2009},
}

Chicago
Van De Kerchove, Ruben, Rudi Goossens, Alain De Wulf, Jean Bourgeois, and Wouter Gheyle. 2009. “Thermal Remote Sensing Imagery in Permafrost Studies.” In Remote Sensing for A Changing Europe, ed. Derya Maktav, 313–320. Amsterdam, The Netherlands: IOS Press.
APA
Van De Kerchove, R., Goossens, R., De Wulf, A., Bourgeois, J., & Gheyle, W. (2009). Thermal remote sensing imagery in permafrost studies. In D. Maktav (Ed.), REMOTE SENSING FOR A CHANGING EUROPE (pp. 313–320). Presented at the 28th European-Association-of-Remote-Sensing-Laboratories (EARSeL) Symposium and Workshops on Remote Sensing for a Changing Europe, Amsterdam, The Netherlands: IOS Press.
Vancouver
1.
Van De Kerchove R, Goossens R, De Wulf A, Bourgeois J, Gheyle W. Thermal remote sensing imagery in permafrost studies. In: Maktav D, editor. REMOTE SENSING FOR A CHANGING EUROPE. Amsterdam, The Netherlands: IOS Press; 2009. p. 313–20.
MLA
Van De Kerchove, Ruben, Rudi Goossens, Alain De Wulf, et al. “Thermal Remote Sensing Imagery in Permafrost Studies.” Remote Sensing for A Changing Europe. Ed. Derya Maktav. Amsterdam, The Netherlands: IOS Press, 2009. 313–320. Print.