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  "Title": "fire_perimeters.mxd",
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  "Comments": "<DIV STYLE=\"text-align:Left;\"><DIV><DIV><P><SPAN STYLE=\"font-weight:bold;\">Dates of Imagery:<\/SPAN><\/P><P><SPAN>4/1/20 to 5/5/20<\/SPAN><\/P><P><SPAN STYLE=\"font-weight:bold;\">Date of Next Image:<\/SPAN><SPAN>None expected<\/SPAN><\/P><P><SPAN STYLE=\"font-weight:bold;\">Summary:<\/SPAN><\/P><P><SPAN /><SPAN>The support vector machine method is used to process Active Fires L2 satellite data to estimate the fire evolution. A unique visualization of the fire detections shows how the size of the pixel depends on the product and the scan angle. The confidence level and FRP are also used to illustrate the pixels. Hotspot fire detections and clear ground observations are used to drive the machine learning technique and draw fire perimeters at different times. <\/SPAN><\/P><P><SPAN /><\/P><P><SPAN STYLE=\"font-weight:bold;\">Suggested Usage:<\/SPAN><\/P><P><SPAN>Tracking fire perimeters and initialization and data assimilation for fire modeling.<\/SPAN><\/P><P><SPAN /><\/P><P><SPAN STYLE=\"font-weight:bold;\">Satellite/Sensor:<\/SPAN><\/P><P><SPAN>L2 Active Fires data from MODIS and VIIRS satellites (MOD14, MYD14, and VNP14).<\/SPAN><\/P><P><SPAN /><\/P><P><SPAN STYLE=\"font-weight:bold;\">Resolution:<\/SPAN><\/P><P><SPAN>750m to 1km<\/SPAN><\/P><P><SPAN /><\/P><P><SPAN STYLE=\"font-weight:bold;\">Credits:<\/SPAN><\/P><P><SPAN>NASA, NSF<\/SPAN><\/P><P><SPAN /><\/P><P><SPAN STYLE=\"font-weight:bold;\">ESRI REST Endpoint:<\/SPAN><\/P><P><SPAN>See URL section on the right side of page.<\/SPAN><\/P><P><SPAN /><\/P><P><SPAN STYLE=\"font-weight:bold;\">WMS Endpoint:<\/SPAN><\/P><P><SPAN /><\/P><\/DIV><\/DIV><\/DIV>",
  "Subject": "Fire perimeters for the Guatamala Fires April/May 2020 derived by machine learning.",
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  "Version": "10.1",
  "Keywords": "NASA,NASA Disasters Program,Fire,Fires,Wildfire,Wildfires,Perimeter,Guatemala,2020"
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