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High resolution burn severity data (derived from satellite imagery) for the South Fork McKenzie River in Oregon, USA, before and after a wildfire event, 2020 and 2021

The data comprise Sentinel-2 derived burn severity rasters covering restored and unrestored reaches of the South Fork McKenzie river, Oregon USA. The data were collected in order to quantify differences in burn severity in restored and unrestored river reaches following the Holiday Farm wildfire in 2020. Raw satellite imagery acquired in June 2020 and June 2021 was processed to calculate Normalised Burn Ratio (NBR), giving pre- and post-fire burn severity information. Data consist of 10 m .TIF raster imagery where a digital number gives a measure of burn severity; high NBR values indicate healthy vegetation, whereas lower values indicate burnt areas or bare ground. The study was conducted by the University of Nottingham, in partnership with the US Forest Service, Portland State University, Washington State University and Colorado State University. Funding for the work was received from the Natural Environment Research Council. Full details about this dataset can be found at https://doi.org/10.5285/8162887a-5481-440f-a7f2-427eee793efd

Simple

Date (Publication)
2023-01-17
Identifier
https://catalogue.ceh.ac.uk/id/8162887a-5481-440f-a7f2-427eee793efd
Identifier
doi: / 10.5285/8162887a-5481-440f-a7f2-427eee793efd
Other citation details
Dugdale, S.J., Field, R., Johnson, M., Mariani, M., Pugh, B., Schrodt, F., Thorne, C. (2023). High resolution burn severity data (derived from satellite imagery) for the South Fork McKenzie River in Oregon, USA, before and after a wildfire event, 2020 and 2021. NERC EDS Environmental Information Data Centre 10.5285/8162887a-5481-440f-a7f2-427eee793efd
Author
  University of Nottingham - Dugdale, S.J.
Author
  University of Nottingham - Field, R.
Author
  University of Nottingham - Johnson, M.
Author
  University of Nottingham - Mariani, M.
Author
  University of Nottingham - Pugh, B.
Author
  University of Nottingham - Schrodt, F.
Author
  University of Nottingham - Thorne, C.
Point of contact
  University of Nottingham - Dugdale, S.J.
Owner
  University of Nottingham
Custodian
  NERC EDS Environmental Information Data Centre
Publisher
  NERC EDS Environmental Information Data Centre
Access constraints
otherRestrictions Other restrictions
Other constraints
Registration is required to access this data
Use constraints
otherRestrictions Other restrictions
Other constraints
This resource is available under the terms of the Open Government Licence
Use constraints
otherRestrictions Other restrictions
Other constraints
Contains modified Copernicus Sentinel data [2020, 2021]
Use constraints
otherRestrictions Other restrictions
Other constraints
If you reuse this data, you should cite: Dugdale, S.J., Field, R., Johnson, M., Mariani, M., Pugh, B., Schrodt, F., Thorne, C. (2023). High resolution burn severity data (derived from satellite imagery) for the South Fork McKenzie River in Oregon, USA, before and after a wildfire event, 2020 and 2021. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/8162887a-5481-440f-a7f2-427eee793efd
Spatial representation type
grid Grid
Distance
10  urn:ogc:def:uom:EPSG::9001
Metadata language
EnglishEnglish
Character set
utf8 UTF8
Topic category
  • Imagery base maps earth cover
Begin date
2020-01-01
End date
2021-12-30
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Unique resource identifier
WGS 84
Distribution format
  • TIFF ()

Distributor
  NERC EDS Environmental Information Data Centre
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dataset Dataset
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dataset

Conformance result

Date (Publication)
2010-12-08
Statement
20 m bands of Two Sentinel-2A images of study site (pre/post-fire; June 2020 and 2021) were super-resolved to 10m following Lanaras et al (2018) These data were subsequently used to generate raster files depicting 10m resolution Normalised Burn Ratio (NBR) across South Fork McKenzie River, where NBR = (Sentinel Band B08 - B12) / (B08 + B12), following the methodology outlined in Keeley (2009). Subtraction of postfire from prefire NBR rasters facilitates estimation of burn severity by highlighting vegetation burn in relation to pre-burnt state. Lanaras, C., Bioucas-Dias, J., Galliani, S., Baltsavias, E., & Schindler, K. (2018). Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 305-319 https://doi.org/10.1016/j.isprsjprs.2018.09.018 Keeley, J.E. (2009). Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18, 116-126. https://doi.org/10.1071/WF07049
File identifier
8162887a-5481-440f-a7f2-427eee793efd XML
Metadata language
EnglishEnglish
Character set
ISO/IEC 8859-1 (also known as Latin 1) 8859 Part 1
Hierarchy level
dataset Dataset
Hierarchy level name
dataset
Date stamp
2025-03-21T09:34:32
Metadata standard name
UK GEMINI
Metadata standard version
2.3
Point of contact
  NERC EDS Environmental Information Data Centre
Lancaster Environment Centre, Library Avenue, Bailrigg , Lancaster , LA1 4AP , UK
https://eidc.ac.uk/
 
 

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