The 'FireAlarm' system transfers all the meteorological information to the Ministry of Interior and dispatching centres on FMI´s web pages. Fire index tables including wind forecasts are also sent via fax to dispatching centres. Satellite based alarm maps are presented on the same web service (daily fire maps). Most of the data are also available for the public via the same web pages. Lightning information is the only service that is not in the public web-domain. It is available only for the Ministry of the Interior and dispatching centres.
Table 7 describes the structure of the 'FireAlarm' web service and the Internet addresses of 'FireAlarm' web pages and their contents.
Table 7. 'FireAlarm' operational web-service.
Public Web service: metsapalo.fmi.fi
• AVHRR and ATSR daily fire map
• fire index maps
• fire indices combined with weather information
Web service with a password:
ilmanet.fmi.fi
• lightning maps
Figure 9 shows the process chains for computing the web pages. There are two basic databases, Climate Database and Real Time Database, that are used when computing fire indices, wind forecasts and lightning.
Fire index &
wind tables Synoptic
Observations
HIRLAM forecasts
Lightning
Databases
Processing
Web-service
Lightning maps
Climate Data base Finnish Data
Real time Data base
LIGHTNING PROCESS - data combined with map
information
- conversion to gif-images - output for web pages
Fire index maps
Daily fire map
SATELLITE BASED ALARMS FIRE INDEX PROCESS
- interpolation
- evaporation calculation - surface moisture calculation - output for web pages
Figure 9. System architecture of the production of fire indices ad meteorological information.
5.6.2 Fire indices and wind forecasts
A forest fire index is produced at FMI twice a day (Figure 9). The process starts every three hours after the synoptic weather observation time with a data query from the Climate database.
Interpolation is then performed of temperature, humidity, wind speed, precipitation and global radiation (estimated from cloud observations for the manually operated weather stations, and measured directly at automatic stations). The interpolation extends over the whole of Finland using a grid cell size of 10 x 10 km. The interpolation method used (‘kriging’) takes into account the mean surface elevation of the grid cell, as well as the percentage of lake and sea in each cell. The interpolated data are used as input for evaporation calculation. All information are then loaded into the Climate database for further use.
6 EVALUATION OF 'FIRE ALARM' SYSTEM
6.1 DATA COLLECTED FROM THE FIRE SEASON 1999 - 2000 6.1.1 Description of the burning seasons 1999 and 2000
In the years 1999 and 2000, the number of reported wildfires and also the size of the burned area have been below the long-term average values. With 1212 reported forest fires burning a total area of 550 ha, the summer of 1999 has been slightly above the average of the last decade. However the number of big fires larger than 10 ha was only 7 in 1999 and 1 in 2000.
Table 8 shows a comparison between the big wild fires detected by the 'FireAlarm' satellite system and fires documented by the rescue departments. Most of these fires were ground fires, which means that the active fire size might have been smaller and also the intensity lower than in forest fires.
The 'FireAlarm' system can detect the large fires reliably. In Table 8, the number of documented fires of size 10-50 ha is less than observed, mainly because not all of the rescue departments had reported their forest fires of year 2000 by the end of the evaluation period. For small fires of size 3-6 ha the number of satellite detected fires was less than the number of reported fires, because the spatial resolution and temporal coverage of satellites was not good enough. Cloud cover (or fire location in an area prone to sun glint problems) may also have prevented the observation of some of these small, short-duration fires.
Table 8. Comparison between large forest fires documented by the rescue departments and found by the 'FireAlarm' system.
Fires 1999-2000 Size of the
burned area - A
Fires
documented by rescue
department
Fires detected by the 'FireAlarm' system (including prescribed burnings)
A > 50 ha 1 1
50 > A > 10 ha 8 14
10 > A > 6 ha 7 9
6 > A > 3 ha 26 9
6.1.2 Fires detected by the 'FireAlarm' system in 1999-2000 Figure 10 shows the fires detected using AVHRR data in summer 1999.
Figure 10. Fires detected from 5.5.1999 to 4.10.1999 by AVHRR. The locations of fires are marked with a red triangle.
There were in total 372 fires that produced an alarm telefax in 1999. The satellite system detected a total of 1971 fires in the whole monitoring area, but telefaxes were produced only for fires detected in Finland, Estonia, Sweden, Norway, Latvia and Russian Carelia. A response (to a verification request) was obtained to 104 faxes, which means that 28 percent of the fires were verified. In the
year 2000, a total of 200 fire alarm faxes were sent. Table 9 shows a summary of fires and response faxes by country, summed over the summers of 1999 and 2000.
Table 9. Summary of verification faxes by country in 1999-2000 Country Fires Responses Percent
Carelia 156 6 3.9
Estonia 44 34 77.2
Finland 118 76 64.4
Latvia 76 18 23.7
Norway 37 10 27.0
Sweden 141 126 89.3
Total 572 273 47.7
Of the 104 faxes verified (responded to) in 1999, 13% were false alerts. In summer 2000, 12% of the verified fire alert faxes were false alerts according to the responses from the alarm centres. Table 10 gives an overview (summed over summers 1999 and 2000) of the fires according to the response from alarm centres (or corresponding forest fire authorities in countries outside Finland).
Table 10. Classification of verified fire alarms in 1999-2000.
Carelia Estonia Finland Latvia Norway Sweden total
Forest fires 6 19 7 5 - 25 59
Peat fire - 6 4 - - - 10
Prescribed burning
- 2 52 - - 63 117
Field / Straw fire
- 1 - - 7 4 1
Burning building
- 1 2 - 1 1 5
Other - 3 2 6 2 17 30
False alerts 2 9 7 - 16 34
Total 6 34 75 18 10 126 256
Most of the fires, approximately 50%, were prescribed burnings (in forestry or agricultural land), forest fires or some other type of fires, such as houses, landfill sites, or factories.
6.1.3 ATSR observed fires
In order to detect forest fires, the fire detection threshold must be less than the saturation level of the sensor. The saturation limit of ATSR is about 312 K. This means that the effective fire detection threshold is 312 K. Surface temperatures of 312 K or higher cause saturation of the sensor, and so the fire cannot be detected. If the fire detection threshold is lower than the saturation limit, then the saturated pixels are interpreted as fire pixels, whether the fire or the high surface temperature causes the saturation.
Experiments showed that a fire detection threshold of 312 K is likely to produce false alarms due to soil heating/high reflection from dry soil. This happens especially in the hot days in the end of summer, when fields may already be bare soil. Even 314 K was considered too low, and 318 K was selected in summer 2000 to be on the ‘safe’ side for AVHRR data.
To exclude false alarms connected with the fairly low saturation level of the ATSR 3.7 µm band, ATSR scenes are divided into ‘night-time’ and ‘day-time’ scenes. There is no sunlight component in
‘night-time’ scenes. The environmental temperature can also be expected to be much lower in
‘night-time’ scenes. A lower fire detection threshold can therefore be applied to ‘night-time’ scenes.
The division between ‘night-time’ and ‘day-time’ scenes is made on the basis of the maximum sun elevation angle within the scene. If the maximum sun elevation is less than -3 degrees (i.e. 3 degrees below the horizon) the scene is determined to be a ‘night-time’ scene. In nominal atmospheric conditions (refraction at horizon 0.5 degree), clouds above 6 km are illuminated by the sun but clouds below 6 km are not.
A fire detection threshold (in 3.7-µm data) of 305 K was applied to ‘night-time’ ATSR scenes, while a threshold of 318 K was applied to ‘day-time’ ATSR scenes. Because the day-time fire detection threshold is higher than the saturation limit, it is essentially impossible to detect any fires in daytime ATSR scenes.
Between 2 May and 31 October, there were 407 scenes that were considered as ‘night scenes’. In these 407 scenes, a total of 26 fires were detected.
Figure 11. ATSR-detected fires in the grass-burning season (20.3. -20.4.2000).
In early spring, soil is fairly moist. Even in fields that have been ploughed in autumn or spring (bare soil) the reflectance is low. The environmental temperature is also fairly low in early spring. Only very few false alarms are expected. Therefore, a lower fire detection threshold could be used in the grass-burning season in April 2000. A fire detection threshold of 312 K was used in this period.
During the period 20 March to 20 April 2000, 242 ATSR scenes were processed and 24 fires were detected. At the same time, 133 fires were detected in 199 processed AVHRR scenes. The absolute number of fires detected by AVHRR was higher than the number of fires detected by ATSR. The AVHRR system had in spring 2000 three satellites (NOAA-12, NOAA-14, and NOAA-15), each producing nominally one ascending and one descending over-pass per day.
The ATSR system had one satellite ERS-2 producing nominally 2 over-passes per day, one ascending and one descending. 2250 km were used of the total 2700... 2800 swath width of the AVHRR system. The false-alarm screening algorithm discarded 100 pixels. The swath of the ATSR system is 500 km wide. If the sensitivity to fires was the same AVHRR should detect 13.5 times (3*2250/500) the number of ATSR-detected fires. The results - 133 AVHRR-detected fires instead of 324 - suggest that ATSR with its constant 1-km2 resolution is more sensitive to small fires than the AVHRR sensor with a resolution of 1.21-km2 at best.
6.1.4 Discussion on fire detection thresholds
The fire detection is based on the use of middle infrared 3.5 µm (AVHRR) or 3.7 µm (ATSR) wavelength radiation. The radiation sensed at these wavelengths consists of a component coming from reflected solar light, background thermal radiation of the soil, and thermal radiation caused by the hot forest fire. Figure 12 shows schematically the proportions of the middle IR radiation, sensed by the sensor onboard a satellite. The calculated spectral radiant exitances are based on the following assumptions:
• the reflected radiation (blue, reflection 3% normally, 30% in winter conditions and in dry summer conditions)
• the thermal background (red, 263 K in winter, 300 K in summer, 318 K in hot summer)
• the fire-induced thermal radiation (yellow, 0.1 ha burning at a time).
If the radiation intensity is above certain thresholds, the source of radiation is interpreted to be a possible hot spot. If this threshold is at a very low level (threshold I, season 3 in Figure 12), even the background radiation can exceed it and cause a false alarm. If this threshold is at a very high level (threshold II, season 1 or small fires), then only very big fires can be detected and a great part of the small fires are not observed.
In cold conditions (season 1 winter or night-time), or when the size of the fire is small, an increase in the sensed radiation level may fail to produce a fire alert if the fire detection threshold II is used. This is not a major drawback since forest fires are not a problem in the boreal forest during the cold period of the year.
In typical summer conditions at day-time (season 2), the sum of the thermal background radiation and the sunlight that is reflected from various green vegetation does not vary dramatically from place to place. This is because the air temperature tends to keep the surface temperature of vegetation- covered areas fairly constant. The reflectance of vegetation-covered surfaces is also very low, and its influence on the sum of the thermal and reflected component is almost constant. The increase of
the radiation intensity above a certain threshold level (threshold I and II) can therefore be interpreted as a sign of a fire event in a pixel.
The problems for fire detection occur in dry summer conditions (Figure 12) at the end of summer.
The surface temperature and therefore also the background thermal radiation are high. Field crops have been harvested and many fields have also been ploughed. Bare soil has a high reflectance for mid-IR radiation, which makes the reflected component high. If the fire threshold is too low (fire threshold I), the high bare-soil radiance and the high temperature alone may be enough to generate a false alert by the fire detection algorithm. A safe fire threshold (fire threshold II) is higher than can be expected at maximum summer-time temperature in dry fields where bare soil is exposed to the sensor.
RADIATION (3.7 um) RECEIVED BY SATELLITE
0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0
1 2 3
Season: 1= winter or night-time, 2= normal summer or day-time, 3= dry and hot summer
SPECTRAL (3.7 um) RADIANT EXITANCE W/m2/um
Threshold II
Saturation
Threshold I
Figure 12. The proportions of reflected radiation (blue), background thermal radiation (red), and the fire thermal radiation (yellow) in mid-IR fire detection.
The experiments made with 1999 NOAA AVHRR data suggested that a safe fire detection threshold for 3.5-µm brightness temperature in the monitoring area is over 314 K. The saturation limit of the ATSR 3.7-µm band is 312 K (blue dashed line in Figure 12). Day-time fire detection with ATSR data may therefore be prone to false alarms except in conditions where a high temperature and high reflectance from dry bare-soil (ploughed) fields can be excluded, e.g. in the grass-burning season in late March and early April.
For ATSR the night-time threshold was decreased down to 305 K, which is clearly less than the saturation level of the sensor. The daytime threshold had to be raised up to 318 K, which was above the saturation level of the sensor thus blocking out the detection of even higher intensities caused by the fires.
6.2 EVALUATION BY USER-REQUIREMENT CRITERIA