Welcome!
Thank you for visiting. Please note this project was completed in 2021, and much of the data hosted by SDSU is no longer available. As such, the application may not work as intended in certain circumstances. Please reach out directly to Keaton with any questions about the data or project.
Tool Background and Study Context
You may find it useful to review the following background information before interacting with the tools. I recommend viewing this application in a browser on a desktop computer. For more detailed information on how the features are derived from the ATIR imagery and the data used in this study, please see Schag et al. 2021, and Stow et al. 2014, 2019 (cited below).
The purpose of this graphical application is to visualize features of wildfire spread and behavior that have been derived from repeat pass airborne thermal infrared (ATIR) imagery. The primary features used in visualizations are active fire front polylines and rate of spread (ROS) vectors. There may be potential to apply these tools to fire spread model simulations and satellite-derived perimeter sequences in addition to feature derived from ATIR imagery. I used the ESRI ArcGIS API 4.18 for JavaScript (JS) for the map-based visualizations and developed a JS module using Three.js for the Rate of Spread Sphere (ROSS). The code and data used are available upon request. For any additional questions or comments please contact me (Keaton Shennan) at kshennan1233@sdsu.edu.
The data and application context demonstrated with these visualization tools focus on the fire spread behavior of the Thomas and Detwiler fires which occurred in California in 2017. The Thomas fire began December 4th, 2017 in Santa Barbara and Ventura Counties. The imagery used to derive the fire features is from geoprocessed FireMapper 2.0 sequences captured between December 7-10, 2017. The passes occurred at roughly seven-minute intervals. Santa Ana wind conditions with easterly flow were present December 10 whereas the winds on December 9th were milder with a predominantly westerly flow. The Detwiler fire began July 7th, 2017 in Mariposa County, California. The time sequence for Detwiler was captured using repeat pass ATIR imagery on July 20, 2017. It primarily captured downhill spread through herbaceous vegetation into an area with denser shrub coverage.
Again, the goal of these web application is to create an interactive environment for exploratory analysis of fire spread features derived from ATIR imagery.
Please take the survey (select the “Provide Feedback!” button at the top right of the browser) to provide feedback (5-10 minutes est. time) about your experience.
Thank you, Keaton
Coming Soon:
- Imagery (NAIP)
- Time Dimension and Animation
General User Interface
The general layout has the ROSS on the left, a map display on the right, and a table listing feature attributes below (when visible). In the map interface, a few tools are available. Box A contains the navigation interface. You can left-click and drag to pan, or right-click and drag to orbit in 3D. You may also toggle the basemap between satellite imagery and a topographic map by clicking the thumbnail in box "B". Layer visibility controls are available in box C. Click on a fire for a drop-down menu containing the individual fire front and ROS vector sequences or to view examples of the ATIR imagery. "D" shows the location of the attribute tables for the spread vectors and fire fronts. They can be toggled on and off and will be displayed below the map (Note: you may need to scroll down to see the tables once they are turned on). To edit features, select the tile next to "E" to open the feature editor widget. Elevation Profiles will be displayed by selecting the button in the window labeled with "F".
Rate of Spread Sphere (ROSS) User Guide
Begin by selecting one of buttons for the fire sequences below the blank visualization on the left side of the page (see below image).
After selecting a fire sequence, you will see individual ROS vectors populate for that sequence. The arrows in the ROSS correspond to the spread vectors in the map for whichever sequence was selected. The currently selected sequence's button will orange. The red concentric rings can be selected to display the ROS magnitude at that distance from the center of the sphere. The Y-axis represents the directional slope of the spread vector in degrees, which ranges between 90 (upslope) and -90 (downslope). The perimeter of the circle represents the direction of the spread vector in bearing degrees (0-360) and cardinal directions are noted in red around the exterior of the sphere. Green ROS vectors represent upslope movement, and blue ROS vectors represent downslope movement. The green text near the perimeter of the sphere is the maximum ROS for that sequence.
Each ROS vector can be selected, and the selected vector will turn cyan. Information about the selected ROS vector is displayed above the ROSS (above image, ROSS Box A). You can cycle through each time step of the sequence using the slider (above image, ROSS Box B). If you would like to see the spread vector in the map on the right, select the "Zoom Selected Feature" button and the map extent will zoom to the selected ROS vector which will be highlighted. The orange vector represents the average hourly wind direction. The hourly wind data from the nearest Remote Automated Weather Station (RAWS) can be viewed by selecting the orange vector. The hourly wind data from the FireBuster model can be viewed by selecting the gold vector. If you do not see a wind vector, try moving the slider.
References:
- Schag, G. M., Stow, D. A., Riggan, P. J., Tissell, R. G., & Coen, J. L. 2021.
Examining Landscape-Scale Fuel and Terrain Controls of Wildfire Spread Rates Using
Repetitive Airborne Thermal Infrared (ATIR) Imagery.
Fire 4(1), 6.
https://doi.org/10.3390/fire4010006 - Stow, D., P. Riggan, G. Schag, W. Brewer, R. Tissell, J. Coen, and E. Storey. 2019.
Assessing uncertainty and demonstrating potential for estimating fire rate of spread at
landscape scales based on time sequential airborne thermal infrared imaging.
International Journal of Remote Sensing 40 (13):4876–4897.
doi: https://doi.org/10.1080/01431161.2019.1574995. - Stow, D. A., P. J. Riggan, E. J. Storey, and L. L. Coulter. 2014.
Measuring fire spread rates from repeat pass airborne thermal infrared imagery.
Remote Sensing Letters Remote Sensing Letters 5(9):803–812.
doi: https://doi.org/10.1080/2150704X.2014.967882.