Abstract
The web-oriented geoinformation system for forest fire danger prediction based on a probabilistic fire danger criteria is described in the paper. The new method of the calculation of the probabilistic fire danger criteria is depicted. А new formula for fire danger assessment for a certain time interval of forest fire season is obtained using the basic principles of the probability theory. A definition of the probability using frequency of events is used to calculate fire danger. The statistical data for certain forestry is used to determine all the multipliers in the formula of fire danger. The geoinformation system for forest fire danger assessment based on the method described here is developed by the Django platform in the programming language Python. The system architecture based on Django’s Model-View-Template is described in the paper. The software package that runs on the server allows to get and visualize a set of parameters describing forest fire danger. The GeoDjango framework was used for realization of cartographic functions. A fragment of a forest fire risk map which corresponds to certain value of fire danger is depicted. The estimation of the fire risk and visualization it on the map help to identify areas most prone to fire ignition and spread and to allocate forest fire fighting resources efficiently.
| Original language | English |
|---|---|
| Pages (from-to) | 737-744 |
| Number of pages | 8 |
| Journal | International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM |
| Volume | 1 |
| Issue number | 2 |
| Publication status | Published - 2014 |
| Event | 14th International Multidisciplinary Scientific Geoconference and EXPO, SGEM 2014 - Albena, Bulgaria Duration: 17 Jun 2014 → 26 Jun 2014 |
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Keywords
- Django
- Fire danger criteria
- Fire risk
- Forest fire danger
- GeoDjango
- Geoinfomation system
- Model-View-Template
- Python
ASJC Scopus subject areas
- Geology
- Geotechnical Engineering and Engineering Geology
Cite this
Program components for web-oriented geoinformation system of forest fire danger prediction. / Baranovskiy, Nikolay V.; Zharikova, Marina V.
In: International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, Vol. 1, No. 2, 2014, p. 737-744.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Program components for web-oriented geoinformation system of forest fire danger prediction
AU - Baranovskiy, Nikolay V.
AU - Zharikova, Marina V.
PY - 2014
Y1 - 2014
N2 - The web-oriented geoinformation system for forest fire danger prediction based on a probabilistic fire danger criteria is described in the paper. The new method of the calculation of the probabilistic fire danger criteria is depicted. А new formula for fire danger assessment for a certain time interval of forest fire season is obtained using the basic principles of the probability theory. A definition of the probability using frequency of events is used to calculate fire danger. The statistical data for certain forestry is used to determine all the multipliers in the formula of fire danger. The geoinformation system for forest fire danger assessment based on the method described here is developed by the Django platform in the programming language Python. The system architecture based on Django’s Model-View-Template is described in the paper. The software package that runs on the server allows to get and visualize a set of parameters describing forest fire danger. The GeoDjango framework was used for realization of cartographic functions. A fragment of a forest fire risk map which corresponds to certain value of fire danger is depicted. The estimation of the fire risk and visualization it on the map help to identify areas most prone to fire ignition and spread and to allocate forest fire fighting resources efficiently.
AB - The web-oriented geoinformation system for forest fire danger prediction based on a probabilistic fire danger criteria is described in the paper. The new method of the calculation of the probabilistic fire danger criteria is depicted. А new formula for fire danger assessment for a certain time interval of forest fire season is obtained using the basic principles of the probability theory. A definition of the probability using frequency of events is used to calculate fire danger. The statistical data for certain forestry is used to determine all the multipliers in the formula of fire danger. The geoinformation system for forest fire danger assessment based on the method described here is developed by the Django platform in the programming language Python. The system architecture based on Django’s Model-View-Template is described in the paper. The software package that runs on the server allows to get and visualize a set of parameters describing forest fire danger. The GeoDjango framework was used for realization of cartographic functions. A fragment of a forest fire risk map which corresponds to certain value of fire danger is depicted. The estimation of the fire risk and visualization it on the map help to identify areas most prone to fire ignition and spread and to allocate forest fire fighting resources efficiently.
KW - Django
KW - Fire danger criteria
KW - Fire risk
KW - Forest fire danger
KW - GeoDjango
KW - Geoinfomation system
KW - Model-View-Template
KW - Python
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JO - International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
JF - International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
SN - 1314-2704
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