Hi FIRMS experts! I'm an extreme stat researcher and find your work impressive and would like to go deeper.
1. The archived FIRMS MODIS data (https://firms.modaps.eosdis.nasa.gov/country/) has columns 'brightness' and 'bright_t31'. May I assume both of them are temperatures in Kelvin measured by different wavelengths (4 or 11 um as in the paper)?
2. Would like to consult if the FRP data is mainly for comparison with background or can be individually used to quantify fire magnitude or energy release?
3. By document I presume an observation with confidence>=80 and type==0 can be taken as 'almost' a vegetation fire event?
4. BTW would suggest a readme.txt file with minimal column explanations to accompany your archived data. It should maximize the impact of your product and let it reachable to layman but interested users like me.
Thx & Regards.
On annual summary data (FIRM MODIS)
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LANCE & FIRMS - ddavies
- User Services
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- Joined: Thu Jun 18, 2020 4:44 am America/New_York
Re: On annual summary data (FIRM MODIS)
Hi - Thanks for your interest in FIRMS.
1. You are correct - the archived FIRMS MODIS data colums columns 'brightness' and 'bright_t31' are both temperatures in Kelvin measured by different wavelengths (4 or 11 um as in the paper). You can find out about the attributes here: https://www.earthdata.nasa.gov/learn/find-data/near-real-time/firms/mcd14dl-nrt#ed-firms-attributes
Bright_T31 = Brightness temperature 31 (Kelvin)
Channel 31 brightness temperature of the fire pixel measured in Kelvin.
Brightness = Brightness temperature 21 (Kelvin)
Channel 21/22 brightness temperature of the fire pixel measured in Kelvin.
We recommend you look at the Active fire user guides (https://www.earthdata.nasa.gov/faq/firms-faq#ed-user-guides)
2. You ask if the FRP data is mainly for comparison with background or can be individually used to quantify fire magnitude or energy release?
Fire Radiative Power (FRP) is the rate of radiative energy emission per time unit from all fires within a pixel. FRP has been extensively used as a proxy of fire intensity to characterize fire types and is related to the rate of biomass combustion and rate of emissions. FRP estimates are provided for active fire data from MODIS, VIIRS and geostationary sensors used in FIRMS. Sensor spatial resolution, saturation temperature of thermal bands, satellite view zenith angle, time of satellite observation, etc. can affect the accuracy and variability of FRP estimates. Users should consider these factors whether comparing FRP information from a specific sensor or multiple sensors.
3. You ask about confidence values: The confidence value was added to help users gauge the quality of individual fire pixels is included in the Level 2 fire product. They are different for MODIS and VIIRS.
For MODIS the confidence value ranges between 0% and 100% and can be used to assign one of the three fire classes (low-confidence fire, nominal-confidence fire, or high-confidence fire) to all fire pixels within the fire mask. In some applications errors of commission (or false alarms) are particularly undesirable, and for these applications one might be willing to trade a lower detection rate to gain a lower false alarm rate. Conversely, for other applications missing any fire might be especially undesirable, and one might then be willing to tolerate a higher false alarm rate to ensure that fewer true fires are missed. Users requiring fewer false alarms may wish to retain only nominal- and high-confidence fire pixels, and treat low-confidence fire pixels as clear, non-fire, land pixels. Users requiring maximum fire detectability who are able to tolerate a higher incidence of false alarms should consider all three classes of fire pixels.
For VIIRS: This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence values are set to low, nominal and high. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (<15K) in the mid-infrared channel I4. Nominal confidence pixels are those free of potential sun glint contamination during the day and marked by strong (>15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.
The confidence value is application specific. This isn't very helpful, I know, but unfortunately there's no way to establish an optimal cutoff a priori. Users have to adopt an empirical approach -- what threshold works best for what I'm trying to do? Unfortunately the confidence values in the product do not directly correspond to the statistical confidence levels in reference to Type I and Type II errors.
4. Great suggestion re: adding the readme.txt file to the country download files. We have these for other downloads and agree this will be helpful.
Again - thanks for the feedback. Let us know if you have further questions.
1. You are correct - the archived FIRMS MODIS data colums columns 'brightness' and 'bright_t31' are both temperatures in Kelvin measured by different wavelengths (4 or 11 um as in the paper). You can find out about the attributes here: https://www.earthdata.nasa.gov/learn/find-data/near-real-time/firms/mcd14dl-nrt#ed-firms-attributes
Bright_T31 = Brightness temperature 31 (Kelvin)
Channel 31 brightness temperature of the fire pixel measured in Kelvin.
Brightness = Brightness temperature 21 (Kelvin)
Channel 21/22 brightness temperature of the fire pixel measured in Kelvin.
We recommend you look at the Active fire user guides (https://www.earthdata.nasa.gov/faq/firms-faq#ed-user-guides)
2. You ask if the FRP data is mainly for comparison with background or can be individually used to quantify fire magnitude or energy release?
Fire Radiative Power (FRP) is the rate of radiative energy emission per time unit from all fires within a pixel. FRP has been extensively used as a proxy of fire intensity to characterize fire types and is related to the rate of biomass combustion and rate of emissions. FRP estimates are provided for active fire data from MODIS, VIIRS and geostationary sensors used in FIRMS. Sensor spatial resolution, saturation temperature of thermal bands, satellite view zenith angle, time of satellite observation, etc. can affect the accuracy and variability of FRP estimates. Users should consider these factors whether comparing FRP information from a specific sensor or multiple sensors.
3. You ask about confidence values: The confidence value was added to help users gauge the quality of individual fire pixels is included in the Level 2 fire product. They are different for MODIS and VIIRS.
For MODIS the confidence value ranges between 0% and 100% and can be used to assign one of the three fire classes (low-confidence fire, nominal-confidence fire, or high-confidence fire) to all fire pixels within the fire mask. In some applications errors of commission (or false alarms) are particularly undesirable, and for these applications one might be willing to trade a lower detection rate to gain a lower false alarm rate. Conversely, for other applications missing any fire might be especially undesirable, and one might then be willing to tolerate a higher false alarm rate to ensure that fewer true fires are missed. Users requiring fewer false alarms may wish to retain only nominal- and high-confidence fire pixels, and treat low-confidence fire pixels as clear, non-fire, land pixels. Users requiring maximum fire detectability who are able to tolerate a higher incidence of false alarms should consider all three classes of fire pixels.
For VIIRS: This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence values are set to low, nominal and high. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (<15K) in the mid-infrared channel I4. Nominal confidence pixels are those free of potential sun glint contamination during the day and marked by strong (>15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.
The confidence value is application specific. This isn't very helpful, I know, but unfortunately there's no way to establish an optimal cutoff a priori. Users have to adopt an empirical approach -- what threshold works best for what I'm trying to do? Unfortunately the confidence values in the product do not directly correspond to the statistical confidence levels in reference to Type I and Type II errors.
4. Great suggestion re: adding the readme.txt file to the country download files. We have these for other downloads and agree this will be helpful.
Again - thanks for the feedback. Let us know if you have further questions.