Greg Dillon

Mr. Greg Dillon


Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 February 2014 in Remote Sensing
Verified
Journal Article
Open access
PDF file
SPSean Parks
Sean Parks
GDGreg Dillon
Greg Dillon
CMCarol Miller
Carol Miller
Satellite-inferred burn severity data have become increasingly popular over the last decade for management and research purposes. These data typically quantify spectral change between pre-and post-fire satellite images (usually Landsat). There is an active debate regarding which of the two main equations, the delta normalized burn ratio (dNBR) and its relativized form (RdNBR), is most suitable for quantifying burn severity; each has its critics. In this study, we propose and evaluate a new Landsat-based burn severity metric, the relativized burn ratio (RBR), that provides an alternative to dNBR and RdNBR. For 18 fires in the western US, we compared the performance of RBR to both dNBR and RdNBR by evaluating the agreement of these metrics with field-based burn severity measurements. Specifically, we evaluated (1) the correspondence between each metric and a continuous measure of burn severity (the composite burn index) and (2) the overall accuracy of each metric when classifying into discrete burn severity classes (i.e., unchanged, low, moderate, and high). Results indicate that RBR corresponds better to field-based measurements (average R2 among 18 fires = 0.786) than both dNBR (R2 = 0.761) and RdNBR (R2 = 0.766). Furthermore, the overall classification accuracy achieved with RBR (average among 18 fires = 70.5%) was higher than both dNBR (68.4%) and RdNBR (69.2%). Consequently, we recommend RBR as a robust alternative to both dNBR and RdNBR for measuring and classifying burn severity.

1 December 2011 in Ecosphere
Verified
Journal Article
Open access
PDF file
GDGreg Dillon
Greg Dillon
ZHZachary A. Holden
Zachary A. Holden
PMPenelope Morgan
Penelope Morgan
MCMichael A. Crimmins
Michael A. Crimmins
EHEmily K. Heyerdahl
Emily K. Heyerdahl
CLCharles H. Luce
Charles H. Luce
Fire is a keystone process in many ecosystems of western North America. Severe fires kill and consume large amounts of above- and belowground biomass and affect soils, resulting in long-lasting conse...

1 January 2005
Verified
Report
Open access
PDF file
GDGreg Dillon
Greg Dillon
DKDennis H. Knight
Dennis H. Knight
CMCarolyn B. Meyer
Carolyn B. Meyer

1 January 2005
Verified
Report
Open access
PDF file
CMCarolyn B. Meyer
Carolyn B. Meyer
DKDennis H. Knight
Dennis H. Knight
GDGreg Dillon
Greg Dillon
An approach for synthesizing the results of ecological research pertinent to land management is the analysis of the historic range of variability (HRV) for key ecosystem variables that are affected by management activities. This report provides an HRV analysis for the upland vegetation of the Bighorn National Forest in northcentral Wyoming. The variables include live tree density, dead tree (snag) density, canopy cover, abundance of coarse woody debris, species diversity, fire return intervals, the abundance of various diseases, the proportion of the landscape in different land cover types, and the degree of patchiness in the landscape. The variables were examined at the stand and landscape scales, using information available in the literature and USFS databases. High-elevation landscapes were considered separately from low-elevation landscapes. Much of the report pertains to forests dominated by lodgepole pine, subalpine fir, and Engelmann spruce at high elevations, and by ponderosa pine, aspen, and Douglas-fir at lower elevations. We defined the HRV reference period for the BNF as approximately 1600 to 1890.

5 December 2013
Verified
Dataset
Closed access
PSPamela G. Sikkink
Pamela G. Sikkink
GDGreg Dillon
Greg Dillon
RKRobert Keane
Robert Keane
PMPenelope Morgan
Penelope Morgan
EKEva C. Karau
Eva C. Karau
RSRobin P. Silverstein
Robin P. Silverstein
This archive contains research data collected and/or funded by Forest Service Research and Development (FS R&D), U.S. Department of Agriculture. It is a resource for accessing both short and long-term FS R&D research data, which includes Experimental Forest and Range data. It is a way to both preserve and share the quality science of our researchers.

9 July 2018
Verified
Dataset
Closed access
DBDonovan S. Birch
Donovan S. Birch
PMPenelope Morgan
Penelope Morgan
CKCrystal Kolden
Crystal Kolden
JAJohn Abatzoglou
John Abatzoglou
GDGreg Dillon
Greg Dillon
Alistair SmithAlistair Smith
Alistair Smith