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Remotely sensed fine fuel data for Buenos Aires National Wildlife Refuge (BANWR) from 2015 to 2020

Data for journal manuscript: Remotely Sensed Fine-Fuel Changes from Wildfire and Prescribed Fire in a Semi-Arid Grassland

Dates

Publication Date
Start Date
2015
End Date
2020

Citation

Wells, A.G., and Munson, S.M., 2022, Remotely sensed fine-fuel data for Buenos Aires National Wildlife Refuge (BANWR) from 2015 to 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9347I2H.

Summary

These data were compiled to estimate fine-fuel abundance and distribution across the Buenos Aires National Wildlife Refuge in southern Arizona, USA. The objectives of the study were to develop and validate annual estimates of fine fuel (biomass of herbaceous vegetation) for the refuge and to assess changes in fine fuels through time in response to wildfire and prescribed fire. These data represent the amount of herbaceous biomass or fine fuels (kg/ha) present at a 10-m resolution derived from in-situ estimates of ground cover modeled with satellite imagery. These satellite image data were collected over the Buenos Aires National Wildlife Refuge during leaf-on (August) and leaf-off (November) time periods annually from 2015-2020, by [...]

Contacts

Point of Contact :
Seth M Munson
Originator :
Adam G Wells, Seth M Munson
Metadata Contact :
Adam G Wells
Publisher :
U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase
SDC Data Owner :
Southwest Biological Science Center
USGS Mission Area :
Ecosystems

Attached Files

Click on title to download individual files attached to this item.

Raster_Data.zip 129.73 MB application/zip
Version History 2.0.txt 2.15 KB text/plain

Purpose

The purpose of these data are to estimate changes in the distribution of fine fuels through time. These data were created to assist in management of fire at the Buenos Aires National Wildlife Refuge. These data could be used by future researchers to plan management scenarios for mitigating wildfire risk and develop longer intervals of pre-fire conditions for future events and to inform a mixed-modeling approach to derive an inferential capacity of predicting future outcomes of prescribed fires based on observed events.

Rights

The author(s) of these data request that data users contact them regarding intended use and to assist with understanding limitations and interpretation. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P9347I2H

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