6. Remote Sensing Techniques for Forest Fire Disaster Management: The FireHub Operational Platform

2016 ◽  
pp. 157-188
Author(s):  
Charalampos Kontoes ◽  
Ioannis Papoutsis ◽  
Themistocles Herekakis ◽  
Emmanuela Ieronymidi ◽  
Iphigenia Keramitsoglou
Keyword(s):  
Remote Sensing ◽  
Disaster Management ◽  
Forest Fire ◽  
Fire Disaster ◽  
Remote Sensing Techniques ◽  
Forest Fire Disaster

scholarly journals The model of community empowerment in fire forest disaster prevention in Indonesia

2022 ◽  
Vol 2 (1) ◽  
pp. 38-45
Author(s):  
Husmiati Yusuf ◽  
Fahmi Ilman Fahrudin ◽  
Adi Fahrudin ◽  
Abu Huraerah ◽  
Kiyah George Albert Wanda
Keyword(s):  
Disaster Management ◽  
Forest Fire ◽  
Community Involvement ◽  
Forest Fires ◽  
Community Empowerment ◽  
Disaster Prevention ◽  
Fire Disaster ◽  
In Fire ◽  
Forest Fire Disaster

This paper will look into the topic of community involvement in forest fire disaster prevention, specifically in Indonesia. To begin, the paper will discuss the problem of forest fires in Indonesia, which occur frequently. The study also addressed issues related to disaster management, such as a lack of competence and knowledge, which resulted in disaster management ineffectiveness. The paper's third portion discusses the government's involvement in catastrophe management. Several initiatives and support have been implemented.

scholarly journals Understanding Forest Fire Management in Indonesia from a Global Perspective

2020 ◽  
Vol 37 (1) ◽  
Author(s):  
Indra Agus Riyanto ◽  
Ahmad Cahyadi ◽  
Faricha Kurniadhini ◽  
Hafidz Bachtiar ◽  
Dwiki Apriyana ◽  
...  
Keyword(s):  
United States ◽  
Disaster Management ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Management ◽  
The United States ◽  
Global Perspective ◽  
Forest Fire Management ◽  
Fire Disaster ◽  
Forest Fire Disaster

Forest fires are one of the global issues that attract worldwide attention. Russia, Brazil, Canada, the United States, and Indonesia are among the countries with the largest forest cover and long records of massive forest fires. Forest fire management is, therefore, critical to decreasing the severity level of these fires. Current conditions indicate that, compared with the four other countries, Indonesia has significantly reduced forest fires within the past five years. Consequently, adopting a global perspective to study the characteristics of forest fire disaster management has become necessary. For each management parameter, this research employed a literature review and descriptive analysis. The results showed that Indonesia had an advantage in the field of legal regulation. Indonesia tends to change its regulations within a short span of time, resulting in the number of forest fire incidents decreasing significantly compared with Russia, Brazil, Canada, and the United States. However, the country still has several weaknesses, namely in emergency responses, forest fire monitoring technology, and inter-institutional integration in forest fire disaster management.

Research on the Algorithm of Prevention Forest Fire Disaster in the Poyang Lake Ecological Economic Zone

2012 ◽  
Vol 518-523 ◽  
pp. 5257-5260 ◽  
Author(s):  
Ying Lian Wang ◽  
Jun Yao Ye
Keyword(s):  
Forest Fire ◽  
Clustering Algorithm ◽  
Poyang Lake ◽  
Ecological Economic ◽  
Fire Disaster ◽  
Economic Zone ◽  
The Time Domain ◽  
Forest Fire Disaster ◽  
Disaster System ◽  
Suspicious Area

Poyang Lake Ecological Economic Zone has large forest area, so it's very important to construct prevention forest fire disaster system. This paper presents an algorithm for prevention forest fire disaster based on digital image processing technology. The algorithm distinguishes the realtime forest video by smoke and fire. To determine whether there are some suspicious area in the image in the spatial domain by judging the color properties of smoke and fire through Clustering Algorithm. If it detects any suspicious circumstances, then fixes ccd and detects the suspicious areas in the time domain. In this step, firstly get the initial detect results by wavelet decomposition , then use the k-means clustering algorithm for the spread detection of smoke. Experimental results show that the algorithm is ideal for the experimental video. It alarms before the fire disaster occurs to avoid major fire disaster, which protects the forest resources in the Poyang Lake Ecological Economic Zone.

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