Your browser doesn't support javascript.
loading
California wildfire spread derived using VIIRS satellite observations and an object-based tracking system.
Chen, Yang; Hantson, Stijn; Andela, Niels; Coffield, Shane R; Graff, Casey A; Morton, Douglas C; Ott, Lesley E; Foufoula-Georgiou, Efi; Smyth, Padhraic; Goulden, Michael L; Randerson, James T.
Afiliación
  • Chen Y; Department of Earth System Science, University of California, Irvine, CA, USA. yang.chen@uci.edu.
  • Hantson S; Department of Earth System Science, University of California, Irvine, CA, USA.
  • Andela N; Earth System Science Program, Faculty of Natural Sciences, Universidad del Rosario, Bogota, Colombia.
  • Coffield SR; School of Earth and Environmental Sciences, Cardiff University, Cardiff, UK.
  • Graff CA; Department of Earth System Science, University of California, Irvine, CA, USA.
  • Morton DC; Department of Computer Science, University of California, Irvine, CA, USA.
  • Ott LE; Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Foufoula-Georgiou E; Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Smyth P; Department of Earth System Science, University of California, Irvine, CA, USA.
  • Goulden ML; Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA.
  • Randerson JT; Department of Computer Science, University of California, Irvine, CA, USA.
Sci Data ; 9(1): 249, 2022 05 30.
Article en En | MEDLINE | ID: mdl-35637186
Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012-2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos