UDC: 
DOI: 
10.22389/0016-7126-2019-943-1-102-109
1 Gizatullin A.T.
2 Alekseenko N.A.
3 Moiseeva V.S.
Year: 
№: 
943
Pages: 
102-109

Lomonosov Moscow State University (MSU)

1, 

Institute of Geography, Russian Academy of Sciences

2, 

SCANEX Research and Development Center

3, 
Abstract:
This article is devoted to the development of an algorithm for the preventive assessment of the fire danger of natural areas using remote sensing data (the preventive natural fire danger assessment algorithm). The problems of the current state of the remote sensing materials use for fires researches as a justification for the need of the algorithm are considered. A review of existing methods and algorithms of natural fire danger assessment is done. The algorithm development includes description of the general structure and the content filling process of different algorithm components. The algorithm is a stages sequence of remote sensing data processing and analysis in terms of fire danger. As a result of algorithm, the fire danger assessment of the observed territory is formed. A special feature of the algorithm is its preventiveness, universality (applicability for any territory), practical automatability (the ability to represent in the form of a program code for the processing of RSD) and flexibility (the ability to add and branch the sequence). In the end, general conclusions and recommendations on the use of the algorithm are given.
The work was carried out within the framework of the State Code “Geoinformation-cartographic analysis and remote monitoring of the interaction between nature and society”.
References: 
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Citation:
Gizatullin A.T., 
Alekseenko N.A., 
Moiseeva V.S., 
(2019) Razrabotka algoritma preventivnoj otsenki pozharnoj opasnosti prirodnyh territorij po dannym distantsionnogo zondirovaniya [Development of the preventive natural fire danger assessment algorithm using remote sensing data]. Geodesy and Cartography = Geodezija i kartografija, 80, 1, pp. 102-109. (In Russian). DOI: 10.22389/0016-7126-2019-943-1-102-109
ARTICLE
Received: 25.07.2018
Accepted: 14.11.2018
Published: 20.02.2019

Content

2019 January DOI:
10.22389/0016-7126-2019-943-1

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