Optical remote sensing for estimating fuel moisture content in upland vegetation
Almoustafa, TA 2011, Optical remote sensing for estimating fuel moisture content in upland vegetation , PhD thesis, University of Salford.
Restricted to Repository staff only until 03 October 2014.
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In the United Kingdom (UK) uncontrolled fires in upland moorlands have a negative effect on biodiversity, soil stability and nutrient dynamics. The control of these fires may be problematic because of the inaccessibility of the terrain. This research aims to investigate whether vegetation Fuel Moisture Content (FMC), a key variable influencing fire ignition probability and rate of fire spread, varies temporally and between species types in the UK uplands and whether FMC can be estimated using optical remote sensing. Ground-based measurements of vegetation variables, including FMC and spectral reflectance, were collected on a monthly basis from March 2008 to March 2009 for six study plots at Burbage Moor in the Peak District, United Kingdom. The FMC for the study plots was calculated and compared to the ground-based spectra directly, and correlated with first derivative and narrow-band vegetation indices. FMC was found to vary temporally and with vegetation type. Reflectance variability with FMC was strongest in the near infrared and shortwave infrared regions. The correlation between reflectance and FMC was higher when the first derivative and narrow-band vegetation indices and in particular Moisture Stress Index (MSI) were used. To extrapolate the results to a landscape scale, two hyperspectral images, for May 6 th and July 1 st 2008, were obtained by the Natural Environment Research Council Airborne Research and Survey Facility (NERC ARSF). Concurrently with the flights, in-situ field measurements were made. With the airborne data, the strength of the relationships between FMC and the spectral data sets were also explored using linear regression. Results from the airborne data confirm the results of ground-based measurements in terms of reflectance variability with FMC and in terms of the strength of the spectral correlation with FMC, FMC correlation with the first derivative and FMC correlation with narrow-band vegetation indices. Within the airborne data, the broad band MSI, which was calculated based on the spectral wavebands of Landsat ETM, was also found to have a significant correlation with FMC. This relationship, which was unknown before the current study was performed, offers the potential for operational application of remotely sensed data for FMC estimation at landscape scales. The implication of this is that remote sensing could have a role in timely mapping of fire risk for large areas of moorland.
|Item Type:||Thesis (PhD)|
|Schools:||Colleges and Schools > College of Science & Technology|
Colleges and Schools > College of Science & Technology > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Colleges and Schools > College of Science & Technology > School of Environment and Life Sciences
|Depositing User:||Institutional Repository|
|Date Deposited:||03 Oct 2012 14:34|
|Last Modified:||18 Feb 2014 11:23|
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