Sevinç Volkan
Faculty of Science, Department of Statistics, Muğla Sıtkı Koçman University, 48000, Muğla, Turkey.
Environ Sci Pollut Res Int. 2023 Jan;30(2):4721-4732. doi: 10.1007/s11356-022-22515-w. Epub 2022 Aug 16.
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 11 human-induced factors, a natural factor, and temperature, which is one of the risk factors that determine the conditions for the occurrence of forest fires. Moreover, k-means clustering algorithm, which is an artificial intelligence method, was employed in preparation of the fire risk zone map. Turkey was selected as the study area because there are social and economic variations among its regions. Thus, the regional forest directorates in Turkey were separated into four clusters as extreme-risk zone, high-risk zone, moderate-risk zone, and low-risk zone. Also, a map presenting these risk zones were provided. The map reveals that, in general, the western and southwestern coastal areas of Turkey are at high risk of forest fires. On the other hand, the fire risk is relatively low in the northern, central, and eastern areas.
地理信息系统数据在森林火灾风险区域制图研究中已被广泛使用。然而，森林火灾是由多种因素引起的，不能仅用地理和气象原因来解释。人为因素在森林火灾的发生中也起着重要作用，而这些因素取决于各种社会和经济条件。本文旨在利用一个由11个人为因素、一个自然因素以及温度（温度是决定森林火灾发生条件的风险因素之一）组成的数据集绘制火灾风险区域图。此外，在绘制火灾风险区域图时采用了人工智能方法——k均值聚类算法。选择土耳其作为研究区域是因为其各地区存在社会和经济差异。因此，土耳其的区域森林管理局被分为四个类别，即极高风险区、高风险区、中风险区和低风险区。同时，还提供了一张展示这些风险区域的地图。该地图显示，总体而言，土耳其西部和西南部沿海地区森林火灾风险较高。另一方面，北部、中部和东部地区的火灾风险相对较低。
