scholarly journals Development of natural fire prevention method based on remote sensing data: case study of Krasnoyarsk region forests

Author(s):  
Almaz Gizatullin

The stages of development of natural fire prevention method based on remote sensing data were considered. The case study is focused on Krasnoyarsk region forests. There was a rationale for selecting a study area on the basis of statistical fire data (FIRMS thermal hot spots 2016–2018) and a variety of fire conditions. The fire assessment was founded on the most informative fire factors—surface temperature, vegetation cover inhomogenuity and man-made load, which are derived by the natural-fire characteristics of the territory. These factors were evaluated by measuring parameters closed to them, respectively—radiobrightness temperature based on thermal emission, vegetation index NDVI and integral indicator of distance to settlements and roads. Materials from the Terra/Aqua, Sentinel-3, Landsat-8, Sentinel-2 satellites and Open Street Maps vector map layers were used as data sources. With use of statistical data, the relationship between above parameters and the present fire danger of Krasnoyarsk region was analyzed. Based on the results, we obtained different by forest rayon and fire season month correlation coefficients that described the contribution of individual factors to a fire danger, and threshold values of parameters for preventing fires. Then a sequence of stages of analytical and synthetic fire danger assessment as a study method was built. Validation of the method was performed in the most fire dangerous and representative in terms of fire conditions area in the south-west of the Krasnoyarsk Territory from April 1 to May 10, 2019. It showed sufficient accuracy (65 %) and reliability (58 %) of fire forecast.

2019 ◽  
Vol 943 (1) ◽  
pp. 102-109 ◽  
Author(s):  
A.T. Gizatullin ◽  
N.A. Alekseenko ◽  
V.S. Moiseeva

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.


2019 ◽  
Vol 11 (2) ◽  
pp. 115-124
Author(s):  
hamid reza sadeghi ◽  
jafar masoompour ◽  
Morteza miri

2016 ◽  
Vol 33 ◽  
pp. 600-606 ◽  
Author(s):  
Dominggus Samuel H.L.M.K. Awak ◽  
Jonson Lumban Gaol ◽  
Beginer Subhan ◽  
Hawis H. Madduppa ◽  
Dondy Arafat

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