Next Article in Journal
We’re Not Doing Enough Prescribed Fire in the Western United States to Mitigate Wildfire Risk
Previous Article in Journal
The Effect of Ecophysiological Traits on Live Fuel Moisture Content
Open AccessArticle

Prototype Downscaling Algorithm for MODIS Satellite 1 km Daytime Active Fire Detections

ASRC Federal Data Solutions contractor to United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA
USGS EROS Center, Sioux Falls, SD 57198, USA
Author to whom correspondence should be addressed.
Received: 18 April 2019 / Revised: 19 May 2019 / Accepted: 21 May 2019 / Published: 23 May 2019
This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as compared to the non-burning neighborhood components. Active fire presence probability class for each of the 500 m pixels within the 1 km footprint is assigned by locally adaptive contextual tests against its surrounding neighborhood pixels. Accuracy is assessed using gas flares and wildfires in conjunction with available high-resolution imagery. Proof of concept results using MODIS observations over two sites show that under clear sky conditions, over 84% of the 500 m locations that had active fires were correctly assigned to high to medium probabilities, and correspondingly low to poor probabilities were assigned to locations with no visible flaming fronts. Factors limiting the algorithm performance include fire size/temperature distributions, cloud and smoke obscuration, sensor point spread functions, and geolocation errors. Despite these limitations, the resulting finer spatial scale of active fire detections will not only help first responders and managers to locate actively burning fire fronts more precisely but will also be useful for the fire science community. View Full-Text
Keywords: wildfire; ASTER; Sentinel 3; remote sensing wildfire; ASTER; Sentinel 3; remote sensing
Show Figures

Graphical abstract

MDPI and ACS Style

Kumar, S.S.; Picotte, J.J.; Peterson, B. Prototype Downscaling Algorithm for MODIS Satellite 1 km Daytime Active Fire Detections. Fire 2019, 2, 29.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop