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Forest fire risk area mapping of GIR - P. A. Integrating Remote Sensing, meteriological and topograpgical data - A GIS approach

Data Inputs
Spatial database: Vegetation and fire frequency map with forest block, Road / Railway network and the most important is existing Water bodies in that area.

Non-spatial data on meteorological data on temperature, relative humidity (min, max, average), rainfall, wind (speed and direction), socio-economic data, other tabular data on litter, duft, humus, mor, mull and slash.

The spatial data will be mainly from RS data and Non-spatial data would be from other sources essentially from local meteorological stations Forest Research Institutes and concerned Forest Departments.

Database Design & Organization In GIS Environment
GIS database design and organization involves a total visualization of an operational system. Database design not only helps for a systematic database organization but also provides a level of flexibility for enhancement/ upgradation/ improvement.

Table 1: Weightage Assignment Pattern For Various Parameters Included In Fire Risk Area Rating Analysis

Fire Rating Class	Vegetation class	Proximity Road/Sett./Fringe	Max. Temp.(oC)	RelativeHumid.(%)	Fire Frequency
Very High	5 or 6	<= 100 mtrs.	> 40oc	<= 35 %	03
High	3 or 4	<= 500 mtrs.	> 40oc	<= 35 %	03
Medium	3 or 4	<= 1000 mtrs.	> 40oc	<= 35 %	< 03
Low	2 or 3	<= 1000 mtrs.	<= 40oc	>= 35 %	<= 02
Very Low	1 or 2	<= 1000 mtrs.	<= 40oc	>= 35 %	0 (Nil)
No Risk	Water Bodies

Spatial Data Domain
The spatial data is mainly from Remote Sensing and ancillary sources. Most of the spatial data source follows the SOI (Latitude-Longitude) polyconic co-ordinate system. Thus the spatial database followed the standards of SOI maps at 1:50,000 scale. The primary data input sets are mainly thematic maps. These data sets have been either interpreted from RS data, prepared from ancillary data, Toposheets etc. or obtained from conventional sources or collected form Gujarat Forest Dept.(GFD).


Fig. 1

Non Spatial Data
The non-spatial data sets were collected for each fire scar that included possible fire causes and meteorological data (max and min temp. and relative humid.) during the peak season. Since settlements or NES are also exists within sanctuary area, socio-economic data pertaining to these settlements were also incorporated in the non-spatial data sets.


Fig. 2

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