Award Abstract # 2148788
RII Track-1: Harnessing the Data Revolution for Fire Science

NSF Org: OIA
OIA-Office of Integrative Activities
Recipient: BOARD OF REGENT, NEVADA SYSTEM OF HIGHER EDUCATION
Initial Amendment Date: May 16, 2022
Latest Amendment Date: June 15, 2023
Award Number: 2148788
Award Instrument: Cooperative Agreement
Program Manager: Jeanne Small
jsmall@nsf.gov
 (703)292-8623
OIA
 OIA-Office of Integrative Activities
O/D
 Office Of The Director
Start Date: June 1, 2022
End Date: May 31, 2027 (Estimated)
Total Intended Award Amount: $20,000,000.00
Total Awarded Amount to Date: $7,992,269.00
Funds Obligated to Date: FY 2022 = $3,767,932.00
FY 2023 = $4,224,337.00
History of Investigator:
  • Frederick Harris (Principal Investigator)
    fredh@cse.unr.edu
  • Hans Moosmuller (Co-Principal Investigator)
  • Alireza Tavakkoli (Co-Principal Investigator)
  • Haroon Stephen (Co-Principal Investigator)
  • Scotty Strachan (Co-Principal Investigator)
Recipient Sponsored Research Office: Nevada System of Higher Education
2601 ENTERPRISE RD
RENO
NV  US  89512-1666
(702)522-7070
Sponsor Congressional District: 02
Primary Place of Performance: Nevada System of Higher Education
2601 Enterprise Road
Reno
NV  US  89512-1666
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): F995DBS4SRN3
Parent UEI: F995DBS4SRN3
NSF Program(s): EPSCoR RII Track-1
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 062Z, 132Z, 7715, 9150, SMET
Program Element Code(s): 193Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.083

ABSTRACT

The frequency and severity of wildfires in the western U.S. has increased over the last forty years, caused by changes in climate, fuel buildup, and invasive species. As a result, wildfires are now the most prevalent type of natural disaster in the southwestern U.S. and are detrimental to human health and ecosystem services (including water availability, visibility, and recreation). The Harnessing the Data Revolution for Fire Science (HDRFS) project aims to understand the ?wildland fire continuum,? the process in which an ecosystem?s pre-fire state (plant community composition, ecology, hydrological state, etc.) determines the level of fuel buildup and thereby helps determine the conditions of the eventual wildfire. Post-fire recovery in turn sets the initial condition for establishing the pre-fire state for the next fire in the cycle. The HDRFS research and capacity-building program is organized around interconnected elements of the wildland fire continuum and aligned efforts in research computing and data. Along with its research and capacity-building agenda, the HDRFS project includes an ambitious education and workforce development focus aimed at expanding opportunities for Nevadans at the K-12 and community college levels. HDRFS is administered by the Nevada System for Higher Education in collaboration with the University of Nevada, Reno; the University of Nevada, Las Vegas; and the Desert Research Institute. Additional institutions involved include Nevada State College and four community colleges (College of Southern Nevada, Truckee Meadows Community College, Western Nevada College, and Great Basin College).

Harnessing the Data Revolution for Fire Science (HDRFS) will explore the fire continuum of diverse processes interacting across scales in the sagebrush ecosystem. Goals include: 1) improving understanding of fire processes and effects over spatial scales; 2) determining fire?s interactions with carbon cycling, water balance, fuel buildup, and invasive species; 3) increasing our mechanistic understanding of fire-induced soil hydrophobicity and its influence on hydrology; 4) improving models of fire processes and eco-hydrological fire effects; 5) improving characterization and modeling of fire emissions and their aging; 6) adapting aerial robots for greatly improved data collection under hazardous or challenging conditions (e.g., characterizing smoke plumes, fire processes, and ecohydrology); and 7) developing computer vision/machine learning data fusion to process and assimilate multisensory data into fire and ecosystem models. HDRFS research will contribute to understanding the spatial scaling of fire processes and effects over ~eight orders of magnitude in area, with the goal of using laboratory and other small-scale results for predicting and modeling large scale wildland fire processes and effects. In parallel with its research and capacity-building program, HDRFS will also engage students, educators, and practitioners via a series of outreach and workforce development activities aimed at achieving a more diverse, STEM-capable population and workforce in Nevada.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Kamran, S.A and Hossain, K.F and Tavakkoli, A. and Bebis, G. and Baker, S. "SWIN-SFTNET : SPATIAL FEATURE EXPANSION AND AGGREGATION USING SWIN TRANSFORMER FOR WHOLE BREAST MICRO-MASS SEGMENTATION" IEEE International Symposium on Biomedical Imaging , 2023 Citation Details
Li, Jiaxin and Lin, Fuhong and Yang, Lei and Huang, Daochao "AI Service Placement for Multi-Access Edge Intelligence Systems in 6G" IEEE Transactions on Network Science and Engineering , 2023 https://doi.org/10.1109/TNSE.2022.3228815 Citation Details
Liu, Yunchuan and Ghasemkhani, Amir and Yang, Lei "Drifting Streaming Peaks-over-Threshold-Enhanced Self-Evolving Neural Networks for Short-Term Wind Farm Generation Forecast" Future Internet , v.15 , 2023 https://doi.org/10.3390/fi15010017 Citation Details
Sengupta, Deep and Samburova, Vera and Bhattarai, Chiranjivi and Moosmüller, Hans and Khlystov, Andrey "Emission factors for polycyclic aromatic hydrocarbons from laboratory biomass-burning and their chemical transformations during aging in an oxidation flow reactor" Science of The Total Environment , v.870 , 2023 https://doi.org/10.1016/j.scitotenv.2023.161857 Citation Details
Dahl, Joshua and Marsh, Erik and Lewis, Christopher and Harris, Frederick "MuVR: A Multiuser Virtual Reality Framework for Unity" EPiC Series in Computing , v.88 , 2023 https://doi.org/10.29007/jdlg Citation Details
Hui, Hongwen and Lin, Fuhong and Meng, Lei and Yang, Lei and Zhou, Xianwei "Many-to-many matching based task allocation for dispersed computing" Computing , 2023 https://doi.org/10.1007/s00607-023-01160-2 Citation Details
Sion, Brad and Samburova, Vera and Berli, Markus and Baish, Christopher and Bustarde, Janelle and Houseman, Sally "Assessment of the Effects of the 2021 Caldor Megafire on Soil Physical Properties, Eastern Sierra Nevada, USA" Fire , v.6 , 2023 https://doi.org/10.3390/fire6020066 Citation Details
Lewis, Christopher and Harris, Frederick "An Overview of Virtual Reality" EPiC Series in Computing , v.88 , 2023 https://doi.org/10.29007/5k67 Citation Details

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