MONITORING FIRES IN THE TERRITORY OF FOREST FUND OF REGIONS OF THE RUSSIAN FEDERATION-Reference-Cited by-同舟云学术

MONITORING FIRES IN THE TERRITORY OF FOREST FUND OF REGIONS OF THE RUSSIAN FEDERATION

Published:2020-10-26 Issue:1 Volume:8 Page:329-334
ISSN:2308-8877
Container-title:Actual directions of scientific researches of the XXI century: theory and practice
language:en
Short-container-title:

Author:

Zinoveva Irina,Medvedev P.¹

Affiliation:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov

Abstract

This work is devoted to the consideration of the problems of reducing forest resources, which is largely associated with fires that occur in hard-to-reach areas and in areas with increased recreational load. In this regard, the creation of an effective fire detection system using various types of monitoring – ground, aviation, and space – is of particular relevance and importance. An important monitoring task is not only monitoring the fire situation, but also assessing the effects of fires. To determine the location of forest fires on the lands of the forest fund and other categories of lands, as well as to collect and store data, the Avialesohrana Federal State Budgetary Institution uses remote monitoring of the ISDM-Rosleskhoz system, which helps to quickly detect fires using satellites, record them, and compile information on foci and give them an assessment. According to the ISDM-Rosleskhoz data, a comparative analysis of the dynamics of the number of forest fires in the regions of the Russian Federation for 2017-2019 was carried out, as well as an analysis of the area of forest land covered by fires in 2015-2019, the results of which revealed a growing trend in the number of fires and their increase area. As a result, it was concluded that it is necessary to improve the system of remote monitoring of forest fires with the aim of preventing, timely detecting and preventing spread.

Publisher

Voronezh State University of Forestry and Technologies named after G.F. Morozov

Reference6 articles.

1. Голубева, Е.И. Инновационные технологии в мониторинге лесных пожаров / Е.И. Голубева, С.Н. Жаринов // Вестник российской академии естественных наук. – 2014. – Т.14, №2. – С. 67-72, Golubeva, E.I. Innovacionnye tehnologii v monitoringe lesnyh pozharov / E.I. Golubeva, S.N. Zharinov // Vestnik rossiyskoy akademii estestvennyh nauk. – 2014. – T.14, №2. – S. 67-72

2. Единая межведомственная информационно-статистическая система (ЕМИСС): сайт / Федеральная служба государственной статистики. – URL: https://www.fedstat.ru/organizations/ (дата обращения 08.01.2020). – Текст электронный., Edinaya mezhvedomstvennaya informacionno-statisticheskaya sistema (EMISS): sayt / Federal'naya sluzhba gosudarstvennoy statistiki. – URL: https://www.fedstat.ru/organizations/ (data obrascheniya 08.01.2020). – Tekst elektronnyy.

3. Информационная система дистанционного мониторинга Федерального агентства лесного хозяйства. Блок мониторинга пожарной опасности. – URL: https://nffc.aviales.ru/main_pages/index.shtml (дата обращения 09.01.2020). – Текст электронный., Informacionnaya sistema distancionnogo monitoringa Federal'nogo agentstva lesnogo hozyaystva. Blok monitoringa pozharnoy opasnosti. – URL: https://nffc.aviales.ru/main_pages/index.shtml (data obrascheniya 09.01.2020). – Tekst elektronnyy.

4. Лесной Кодекс Российской Федерации: принят Государственной думой 8 ноября 2006 года: одобрен Советом Федерации 24 ноября 2006 года. – URL: http://www.consultant.ru/document/cons_doc_LAW_64299/ (дата обращения 08.01.2020). – Текст электронный., Lesnoy Kodeks Rossiyskoy Federacii: prinyat Gosudarstvennoy dumoy 8 noyabrya 2006 goda: odobren Sovetom Federacii 24 noyabrya 2006 goda. – URL: http://www.consultant.ru/document/cons_doc_LAW_64299/ (data obrascheniya 08.01.2020). – Tekst elektronnyy.

5. Srinivas, K. Fog Computing and Deep CNN Based Efficient Approach to Early Forest Fire Detection with Unmanned Aerial Vehicles / К. Srinivas, M. Dua // Lecture Notes in Networks and Systems – 2020. – Volume 98. – Pages 646-652. – URL: https://www.scopus.com/record/display.uri?eid=2-s2.0-85075056956&origin=resultslist&sort=plf-f&src=s&st1=+forest+fire+monitoring&st2=&sid=188d7df55a014120dba62c1c222a73dd&sot=b&sdt=b&sl=38&s=TITLE-ABS-KEY%28+forest+fire+monitoring%29&relpos=12&citeCnt=0&searchTerm= (дата обращения 10.01.2020). – Текст электронный., Srinivas, K. Fog Computing and Deep CNN Based Efficient Approach to Early Forest Fire Detection with Unmanned Aerial Vehicles / K. Srinivas, M. Dua // Lecture Notes in Networks and Systems – 2020. – Volume 98. – Pages 646-652. – URL: https://www.scopus.com/record/display.uri?eid=2-s2.0-85075056956&origin=resultslist&sort=plf-f&src=s&st1=+forest+fire+monitoring&st2=&sid=188d7df55a014120dba62c1c222a73dd&sot=b&sdt=b&sl=38&s=TITLE-ABS-KEY%28+forest+fire+monitoring%29&relpos=12&citeCnt=0&searchTerm= (data obrascheniya 10.01.2020). – Tekst elektronnyy.