Forest fire risk zone evaluation based on high spatial resolution RS image in Liangyungang Huaguo Mountain Scenic Spot

<p><strong>Abstract.</strong> Forest fire has been regarded as one of the major reasons for the loss of biodiversity and dreadful conditions of environment. Global warming is also increasing the incidence of forest fire at an alarming rate. That’s why, one need to understand the complex biophysical parameters, which are responsible for this disaster. As it is difficult to predict forest fire, fire risk zone map can be useful for combating the forest fire. So the main aim of this study is to generate a Fire risk model to map fire risk zone using Remote Sensing & GIS technique. Pauri Garhwal District, located in Uttarakhand, India, has been selected for this study as it continually faces the problem of forest fire. Landsat-8 data of 18th April, 2016 have been used for land use land cover mapping. Slope and other information have been derived from topographic maps and field information. For thematic and topographic information analysis ArcGIS and ERDAS Imagine software have been used. Forest fire risk model was generated by using AHP method, where each category was assigned subjective weight according to their sensitivity to fire. Three categories of forest fire risk ranging from very high to low were derived. The generated forest fire risk model was found to be in strong agreement with actual fire-affected sites.</p>

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RS and GIS-based forest fire risk zone mapping in da hinggan mountains

Chinese Geographical Science ◽

10.1007/s11769-003-0055-y ◽

2004 ◽

Vol 14 (3) ◽

pp. 251-257 ◽

Cited By ~ 6

Author(s):

Hai-wei Yin ◽

Fan-hua Kong ◽

Xiu-zhen Li

Keyword(s):

Forest Fire ◽

Fire Risk ◽

Risk Zone ◽

Rs And Gis ◽

Da Hinggan Mountains ◽

Forest Fire Risk

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Mapping the Forest Fire Risk Zones Using Artificial Intelligence with Risk Factors Data

10.21203/rs.3.rs-1130891/v1 ◽

2022 ◽

Author(s):

Volkan Sevinc

Keyword(s):

Artificial Intelligence ◽

High Risk ◽

Forest Fire ◽

Forest Fires ◽

Fire Risk ◽

Geographical Information ◽

Data Set ◽

Risk Zone ◽

Risk Zones ◽

Forest Fire Risk

Abstract Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological reasons. Human-induced factors also play an important role in occurrence of forest fires and these factors depend on various social and economic conditions. This article aims to prepare a fire risk zone map by using a data set consisting of nine human-induced factors, three natural factors, and a temperature factor causing forest fires. Moreover, an artificial intelligence method, k-means, clustering algorithm was employed in preparation of the fire risk zone map. Turkey was selected as the study area as there are social and economic varieties among its zones. Therefore, the forestry zones in Turkey were separated into three groups as low, moderate, and high-risk categories and a map was provided for these risk zones. The map reveals that the forestry zones on the west coast of Turkey are under high risk of forest fire while the moderate risk zones mostly exist in the southeastern zones. The zones located in the interior parts, in the east, and on the north coast of Turkey have comparatively lower forest fire risks.

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Utilisation of GIS and remote sensing for forest fire risk zone mapping at Tram Chim National Park

Science and Technology Development Journal ◽

10.32508/stdj.v18i4.952 ◽

2015 ◽

Vol 18 (4) ◽

pp. 221-235

Author(s):

Minh Thanh Vu ◽

Hien Thi Thu Le

Keyword(s):

Remote Sensing ◽

Forest Fire ◽

Rainy Season ◽

National Park ◽

Fire Risk ◽

Dry Season ◽

Risk Zone ◽

Gis And Remote Sensing ◽

Risk Zones ◽

Forest Fire Risk

Identification of areas of high fire risk is extremely important task in fire prevention and fire fighting. This study focuses on utilizing GIS and remote sensing to predict highest forest fire risk zones at Tram Chim National Park. Forest fire risk index was calculated based on forest-fire causing factors. The factors consist of landcover density and types, distance to water and settlements, surface temperature and leaf wetness index. And then, two forest fire risk maps were completed, one of them represented the fire risk in the rainy season in 2013, the other performed the fire risk in the dry season 2014. High fire risk zones locate mostly at the edge of the park where the bionass is rich and are near settlements. According to this fire risk computing, in the rainy season, area of high fire risk zone was 1,014.65 ha, about 14 % natural areas of Tram Chim National Park. In additional, in the dry season, high forest fire risk zones was 3,344.65 ha, and there is no safety zone. Results of the research contribute to the forest protecting at Tram Chim National Park and over the country.

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