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Publication Details

Title:
Camp Swift Fire Experiment 2014: Pre-fire unmanned aerial vehicle (UAV) imagery Data publication contains GIS data
Author(s):
McNamara, Derek J.
Publication Year:
2018
How to Cite:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
McNamara, Derek J. 2018. Camp Swift Fire Experiment 2014: Pre-fire unmanned aerial vehicle (UAV) imagery. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2018-0049
Abstract:
This data publication contains raw and georeferenced pre-fire aerial imagery collected as part of a prescribed fire research campaign conducted at the Camp Swift Military Base in Bastrop County, Texas on January 15, 2014. The Camp Swift Fire Experiment 2014 consisted of three fires ignited in burn blocks of dimensions 100 meters (m) by 100 m on January 15, 2014. Fires were ignited on relatively flat areas of grass vegetation in moderate winds. Pre-fire aerial imagery was collected from a Canon©T3i mounted on a MLB Company SuperBat III unmanned aerial vehicle (UAV) before the three burns on January 14, 2014. This data package contains five distinct georeferenced pre-fire images and one mosaiced image of these five distinct images covering the three burn blocks.

Keywords:
environment; biota; imageryBaseMapsEarthCover; UAS; JFSP; Joint Fire Science Program; Camp Swift Fire Experiment 2014; UAV; unmanned aerial vehicle; fire behavior; remote sensing; multispectral; aerial imagery; multispectral imagery; unmanned aerial system; wildland fire; wind; pre-fire; Fire effects on environment; Prescribed fire; Fire ecology; Ecology, Ecosystems, & Environment; Fire; Bastrop County; Texas; Camp Swift Army Base
Related publications:
  • Derek McNamara, Geospatial Measurement Solutions, LLC, GIS Analyst; William Mell, United States Forest Service, Combustion Engineer. 2018. Camp Swift Fire Experiment 2014: Integrated Data Quality Assessment. https://usfs.maps.arcgis.com/home/item.html?id=aa3726577d9549a2a26b7d000fb98512
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