Abstract
Fighting forest fires not only depends on the forest type, topography, and weather conditions, but is also closely related to the technical properties of fire-fighting equipment. Firefighting is an important part of fire management planning. However, because of the complex nature of forests, creating thematic layers to generate potential fire risk maps is difficult. The use of remote sensing data has become an efficient method for the discrete classification of potential fire risks. The study was located in the Central District of the Kastamonu Regional Forest Directorate, covering an area of 24,320 ha, 15,685 ha of which is forested. On the basis of stand age, crown closure, and tree species, the sizes and distributions of potential fire risk zones within the study area were determined using high-resolution GeoEye satellite imagery and geographical information system data. The status of pumper truck intervention in zones with high fire risk and the sufficiency of existing forest roads within an existing forest network were discussed based on combustible matter characteristics. Pumper truck intervention was 83% for high-risk zones, 79% for medium-risk zones, and 78% for low-risk zones. A pumper truck intervention area map along existing roads was also created.
Highlights
Fire plays a key role as a disturbance factor in many ecosystems throughout the world
The study zone boundary was created based on the digitized stand map for the Central District of the Kastamonu Regional Forest Directorate
The GeoEye satellite image of the study area was classified using a maximum likelihood algorithm with a controlled classification method based on tree species, crown closure, and Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Applied-Remote-Sensing on 02 Nov 2021 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use stand development age
Summary
Fire plays a key role as a disturbance factor in many ecosystems throughout the world. An important benefit provided by GIS is the perfect integration of attribute features and data with a graphics database. This feature has led to the creation and use of fire databases as an important technological tool in the fire hazard ratio system, as in other environmental sciences.[13] One study[14] in eastern Texas investigated modeling outputs by using fuel model maps with different accuracies. The study showed the significance of using accurate input data layers derived from LIDAR remote sensing techniques with Fire Area Simulator software for realistic predictions of fire growth
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