Figure 7. Burnt area by JERS composed data on 24 may 1996.
We have tried to estimate the burnt area by the Remote sensing and GIS integrated data. For this purpose used JERS satellite data and forest and selected area had 1:1000000 scale. The selected area had 266596.34 hectares, were not burnt.


Figure 8. Burnt soil and forest condition maps.

8a – burnt and not burnt area of the selected area

8b – forest map of selected area

8c – soil amp of selected area

Depending on the map scale we have estimate that 2 types of forest and 7 types of soil was burnt. In Tables 1, 2 are some statistics of burnt forest and soil characteristics.

Table 1. The Burnt forest type

Forest type	None forest	Fir	Birch
Total area (ha)	468534.83	608413.45	8439.11
In selected area (ha)	72181.02	192095.71	2319.61
Not burnt area (ha)	7036.28	18505.77	128.54
Burnt area (ha)	65144.75	173589.93	2191.07

Table 2. Burnt soil type

No	1	2	3	4	5	6	7
Soil type (code number)	22	25	26	101	193	194	205
Total area (ha)	147042.59	90133.50	308550	8906.44	21083.3	2735.01	49592.75
Selected area (ha)	34141.19	81637.36	126306	2108.5	5606.21	1443.69	15353.66
Not burnt area (ha)	6129.72	5669.20	11401.4	165.14	99.59	256.22	1949.32
Burnt area (ha)	28011.47	75968.15	114904	1943.36	5506.62	1187.47	13404.34

Description of soil type code:

22 – Mountain cryomorphic – taiga with mountain soddy – taiga
25 – Mountain derno – taiga with mountain cryomorphic – taiga
26 – Mountain, soddy – taiga with mountain forest dark coloured
101 – Typical chernorem with meadow cryomorphic
193 – Meadow swamp cryomorphic with swamp cryomorphic
194 – Meadow swamp cryomorphic with meadow cryomorphic
205– Meadow alluvial with alluvial weakly developed and meadow swamp alluvial

According to the above results, within the selected area included 72.1% of fir and 0.5% of birch forests and after the fire burnt 90.4% of fir forest and 94.5% of birch forest (See Table 1). From the included soil types within selected area, the Mountain forest dark coloured soil types are biggest by burnt area and Meadow swamp cryomorphic with meadow cryomorphic type is smallest. But there was 93-98% of Meadow swamp cryomorphic with meadow cryomorphic and Meadow swamp cryomorphic with swamp cryomorphic types.

Conclusion
The remote sensing system is a efficient tool for permanent control for detection and monitoring wildfires and also reducing their ecological and economical damages in the country. But there are several difficulties for establishment of early warning mechanism in order organize effectively fire agains activities. One of them is a communication system in Mongolia. Another problem is a data resolution. NOAA AVHRR data has 1.1 km resolution and it is impossible to detect small fires.

For the study of the ecological damage estimation of fire there was selected the JERS satellite data and the 1:1,000,000 scale of GIS data and tried to integrate them. If the scale of GIS data is more smaller, like 1:100,000 we have possibility to make such kind of estimation more accurately.

Reference:

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• Alcira Kreimer, Mohan Munasinghe. Managing Natural Disasters and the Environment, Washington, D.C. June 27-28, 1990.
• Erdenetuya M. Report on “Fire monitoring of Mongolia”, 1997 and 1998.
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