There are various resources and toolkits available to perform this task.

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Rebecca Hopkins
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1 Hands-On Exercise: Wildfires in Chile, January 2017 Task description Imagine you are analyst that has been assigned to the fire Las Maquinas burning in the vicinity of Constitución, in the Maule region of Chile in January The Las Máquinas fire event occurred approximately between January 20 and 31, The task is analyze satellite-based information to help make tactical decisions on deployment of resources based on information on fire intensity and progression determined from VIIRS active fire observations, complemented with select measurements of atmospheric conditions. Resources and data There are various resources and toolkits available to perform this task. 1. VIIRSFIRE website online mapping tool to plot daily fire detections and fire radiative power viirsfire.geog.umd.edu 2. Other online mapping tools, such as NASA WorldView or LANCE worldview.earthdata.nasa.gov earthdata.nasa.gov/earth-observation-data/near-real-time/rapid-response 3. Digital data files from the NOAA NDE system, posted on the training website The files are in netcdf4 format. If you have software to read such files on your computer, you can plot and analyze the fire mask for detailed information Extracts of text files for the same data granules are also available PNG images of fire masks (if no image processing software is available) The data are provided for January only 4. Digital image files of VIIRS spectral measurements, posted on the training website The imagery files are mapped onto a common projection for easy comparison I4, M13, I5, DNB and I1 images are available 5. Plots representing radiosonde (RAOB) observations and NUCAPS atmospheric soundings from Suomi NPP and Metop-B measurements, including vertical profiles and maps of low level satellite retrievals 6. Auxiliary information maps, photos etc.

2 Questions: 1. What are the periods and areas of the most intense burning? 2. What are the periods and areas of the fastest fire spread? 3. What are the atmospheric conditions during the fire event? 4. (Optional) What are the priority areas that need to be protected? Specific activities Analysis of fire radiative power (FRP) data on the viirsfire website (viirsfire.geog.umd.edu) On the viirsfire website go Get Data -> Global Active Fire Map the zoom in to the Maule region of Chile, near the town Constitución (the region is to the south of Santiago) Select January 20, Locations of daily VIIRS fire detections will load. The color code represents FRP values. If preferred, use the slider bar to select only the higher range of data. This was you can delineate the areas of the most intense burning Now select January 21, Locations of daily VIIRS fire detections will load again. Now you can determine the progression of fires between January 20 and 21 and the most intense burning on January 21 also. Using this information, also incorporating local expert knowledge you may have, determine the most critical area(s) that require action. Now repeat loading data for consecutive days until January 31. Analysis of spectral VIIRS images provided on the training website You can look at the following image sequences: o I4, I5 and M13 - daytime and nighttime o DNB nighttime only o I1 - daytime only. Analysis of atmospheric sounding plots provided on the training website Determine conditions of atmospheric temperature and humidity, in particular near the surface and at low levels of the atmosphere Note that the NUCAPS/RAOB observations are from the Santo Domingo, Chile area, which is located along the Chilean coast, southwest of Santiago, Chile (i.e. to the north of the Maule region)

3 Look at the maps of low level satellite retrievals of temperature and humidity for any spatial signal and differences between the fire locations and the profiles at Santo Domingo From the analyses described above, provide a description of the fire event, answering questions 1-3 (or 1-4) above as well as any additional feedback, such as the relative merits of spectral observations of the fires. Additional data analysis: a detailed look at the NDE VIIRS active fire product 1. Determine the actual numerical value of FRP over the most intense burning 2. Determine possible cloud/smoke obscuration (and loss of VIIRS fire information) Digital data files of the NOAA NDE VIIRS active fire product are provided. The files correspond to 85.6 second granules. If you have software to load netcdf4 files you can open the file and look at the content. Select the file below: AF_v1r0_npp_s _e _c nc o Display the fire_mask layer within the Fire Mask group. Use the table below to determine the classification result for each pixel within the granule. The value of 4 indicates cloud, where no fire detection was attempted. A suggested color table is also provided as a text file and a table below. Attempt to import / type in the color table to visualization. o The FRP information is in the Fire Pixels sparse array. List the numerical values for these variables FP_power FP_latitude FP_longitude FP_line FP_element Alternatively, open the text files provided also for each granule. The files include only data for the fire pixels, so only the FRP and location information can be analyzed. Digital images of the fire masks are also provided in PNG format. You can load the images in your image viewer and zoom in to the Maule. The color table for the fire mask is provided below.

4 What is the highest FRP value you found? What was the corresponding M13 brightness temperature measurement for that pixel? Did you find any cloud obscuration and potential loss of fire information? You can repeat the exercise for additional granules if you have time.

5 Table 1. Content of the NOAA NDE VIIRS active fire product (from ATBD) Data Set Name Description Dimension Range of Values & Classes Fire Mask Algorithm QA Image classification product Fire algorithm quality flags [3200, n4816] 0 not processed (missing input data) 1 not processed (obsolete) 2 not processed (obsolete) 3 water 4 cloud 5 non-fire clear land 6 unknown 7 low-confidence fire 8 nominal-confidence fire 9 high-confidence fire [3200, n4816] Bit Field 2 land/water state 2 atmospheric correction 1 day/night state 1 potential fire pixel flag 5 background window size parameter 6 detection test states 3 not used 1 adjacent cloud flag 1 adjacent water flag 2 sun glint level 4 rejection test stats 4 not used FP Line Fire pixel line [N] (number of fire pixels) Min = 0; Max = (n4816) -1 FP Column Fire pixel column [N] (number of fire pixels) Min = 0; Max = 3199 FP Longitude Fire pixel longitude [N] (number of fire pixels) Min = 0; Max = 180 degrees FP Latitude Fire pixel latitude [N] (number of fire pixels) Min = 0; Max = 90 degrees FP Power Fire radiative power [N] (number of fire pixels) Scene-dependent (in megawatts) FP Confidence Fire pixel confidence [N] (number of fire pixels) Min = 0; Max = 100 % FP Land Land pixel flag [N] (number of fire pixels) 1 land, 0 water 18 FP diagnostic variables Variables to describe observing and environmental conditions, and results of algorithm tests [N] (number of fire pixels) See netcdf4 metadata Table 2 Suggested color table for visualization of the VIIRS fire mask variable Data value Red Green Blue

6 Figure 1. Color table for the fire mask PNG images

GOES-R AWG Land Team: Fire Detection and Characterization

GOES-R AWG Land Team: Fire Detection and Characterization June 8, 2010 Presented By: Christopher C. Schmidt 1 1 UW-Madison/SSEC/CIMSS 1 FIRE Product Team AWG Land Team Chair: Yunyue (Bob) Yu FIRE Product