Rapid Spaceborne Mapping of Wildfire Retardant Drops for Active Wildfire Management

被引:1
|
作者
Tagestad, Jerry D. [1 ]
Saltiel, Troy M. [1 ]
Coleman, Andre M. [1 ]
机构
[1] Pacific Northwest Natl Lab, Earth Syst Predictabil & Resiliency Grp, Richland, WA 99352 USA
关键词
wildfire; wildland fire management; remote sensing; fire retardant; CLASSIFICATION; RESOLUTION; ACCURACY; QUALITY; MACHINE; FOREST;
D O I
10.3390/rs15020342
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] ANNUAL GRASSLAND RESPONSE TO FIRE RETARDANT AND WILDFIRE
    LARSON, JR
    DUNCAN, DA
    JOURNAL OF RANGE MANAGEMENT, 1982, 35 (06): : 700 - 703
  • [2] Framing the need for active management for wildfire mitigation and forest restoration
    Burns, Michele
    Cheng, Antony S.
    SOCIETY & NATURAL RESOURCES, 2007, 20 (03) : 245 - 259
  • [3] Studying the Synoptic Wildfire Climatology in Greece. Implications to Wildfire Management
    Kassomenos, P.
    Paschalidou, A. K.
    PERSPECTIVES ON ATMOSPHERIC SCIENCES, 2017, : 733 - 739
  • [4] Exploring Wildfire-Prone Community Trust in Wildfire Management Agencies
    Rasch, Rebecca
    McCaffrey, Sarah
    FOREST SCIENCE, 2019, 65 (05) : 652 - 663
  • [5] Mapping wildfire occurrence at regional scale
    de la Riva, J
    Pérez-Cabello, F
    Lana-Renault, N
    Koutsias, N
    REMOTE SENSING OF ENVIRONMENT, 2004, 92 (02) : 288 - 294
  • [6] Mapping wildfire occurrence at regional scale
    de la Riva, J
    Pérez-Cabello, F
    Lana-Renault, N
    Koutsias, N
    REMOTE SENSING OF ENVIRONMENT, 2004, 92 (03) : 363 - 369
  • [7] Getting Ahead of the Wildfire Problem: Quantifying and Mapping Management Challenges and Opportunities
    O'Connor, Christopher D.
    Thompson, Matthew P.
    Rodriguez y Silva, Francisco
    GEOSCIENCES, 2016, 6 (03)
  • [8] Comparison of homeowner response to wildfire risk among towns with and without wildfire management
    Faulkner, Hilary
    Mcfarlane, Bonita L.
    Mcgee, Tara K.
    ENVIRONMENTAL HAZARDS-HUMAN AND POLICY DIMENSIONS, 2009, 8 (01): : 38 - 51
  • [9] Integrating hydrological parameters in wildfire risk assessment: a machine learning approach for mapping wildfire probability
    Khodaee, Mahsa
    Easterday, Kelly
    Klausmeyer, Kirk
    ENVIRONMENTAL RESEARCH LETTERS, 2024, 19 (11):
  • [10] Spatiotemporal analysis of wildfire in the Tigris and Euphrates basin: A remote sensing based wildfire potential mapping
    Velayati, Amir Hossein
    Boloorani, Ali Darvishi
    Kiavarz, Majid
    Samani, Najmeh Neysani
    Alavipanah, Seyed Kazem
    REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2024, 34