Yıl 2020, Cilt 21 , Sayı 1, Sayfalar 15 - 24 2020-03-26

Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey
Uzaktan algılama ve CBS yöntemleri ile orman yangını risk alanlarının haritalanması: Manisa örneği

Derya GÜLÇİN [1] , Bülent DENİZ [2]


The aim of this research is to map the potential forest fire risk zones using various landscape analysis techniques in Manisa province, Turkey. Forest fire, which is defined as an ecological disaster caused by natural processes or as a result of human activities, causes environmental degradation and fragmentation of the landscape. Therefore, it is very important to produce a fire risk zone map that can be used to minimize the frequency of fire, to prevent damage, to provide a prediction for the problems that may cause fire and to form a decision mechanism for the solution methods. This research utilized CORINE 2018 produced under the framework of the Copernicus Program which is the European Union's Earth Observation Programme coordinated and managed by the European Commission, ASTER Global DEM digital elevation model data obtained from the website of NASA Earthdata, fire archive records based on MODIS satellite images, digital stand map displaying the spatial distribution of tree species, and the OpenStreetMap (OSM) which were used for mapping the existing road network. Vegetation cover, slope, aspect, elevation, distance to settlement, and distance to road variables were used to determine risk zones. The specific weights were assigned to each thematic map layer according to their capacity on fire ignition. The slope, aspect, and elevation maps were generated from the digital elevation model. The distance to settlement map was generated from the CORINE database while the distance to road map was produced from OSM. The Fire Risk Zone Index (FRZI) was utilized to determine forest fire risk zones. According to the generated final fire risk map, almost 25.8% of the study area was predicted to be under very high and highrisk zones. The final forest fire risk model was validated with past fire incidents data that was acquired from MODIS images as fire points. The result of this research showed that out of 149 fire incidents in Manisa between 2001 and 2018, 97 incidents had occurred in very high and highrisk areas. This finding supports that the presented methodology based on RS and GIS techniques is reliable and can be effectively used in the process of delineation of the forest fire risk zones.

Bu araştırmanın amacı, çeşitli peyzaj analiz tekniklerini kullanarak Manisa ilindeki potansiyel orman yangın risk bölgelerini haritalamaktır. Doğal olarak veya insan faaliyetlerinin sonucunda ortaya çıkan orman yangını, ekolojik bağlantılılığın azalmasına ve peyzajın parçalanmasına neden olur. Bu nedenle, yangın sıklığını en aza indirmek, hasarı önlemek, yangına neden olabilecek sorunlara yönelik tahmin yapmak ve çözüm yöntemlerinde karar mekanizması olarak kullanılabilecek yangın risk bölgesi haritasından yararlanılmaktadır. Bu araştırmanın materyalini, Avrupa Birliği tarafından koordine edilen ve yönetilen Yer Gözlem Programı olan Copernicus Programı çerçevesinde üretilen CORINE 2018 verisi, NASA Earthdata web sitesinden elde edilen ASTER Global DEM sayısal yükseklik modeli verisi, MODIS uydu görüntülerine dayanan yangın arşiv kayıtları, ağaç türlerinin mekânsal dağılımını gösteren sayısal meşcere haritası ve mevcut yol ağını haritalamak için kullanılan OpenStreetMap (OSM) verileri oluşturmaktadır. Risk bölgelerini tanımlamak için bitki örtüsü, eğim, bakı, yükseklik, yerleşim yerine ve yola uzaklık değişkenleri kullanılmıştır. Orman yangını çıkma potansiyeline göre her bir tematik harita katmanındaki öznitelik değerlerine belirli ağırlıklar atanmıştır. Sayısal yükseklik modelinden eğim, bakı ve yükseklik haritaları oluşturulmuştur. Yerleşim haritasına olan mesafe CORINE veri tabanından, yol haritasına olan mesafe ise OSM'den üretilmiştir. Orman yangın riski bölgelerini belirlemek için Yangın Riski Bölge Endeksi kullanılmıştır. Oluşturulan yangın riski haritasına göre, çalışma alanının %25.8’inin çok yüksek ve yüksek seviyede yangın riski taşıdığı ortaya çıkmıştır. MODIS görüntülerinden elde edilen 2001 ve 2018 yılları arasındaki orman yangını verileri ile yüksek ve çok yüksek yangın riski taşıyan alanlar çakıştırılmış, 149 orman yangının 97’sinin yüksek ve çok yüksek risk altındaki alanlarda meydana geldiği ortaya çıkmıştır. Bu bulgu, uzaktan algılama ve CBS tekniklerine dayanan metodolojinin güvenilir olduğunu ve orman yangın riski bölgelerinin tanımlanma sürecinde etkin bir şekilde kullanılabileceğini desteklemektedir.

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Birincil Dil en
Konular Fen
Bölüm Orijinal Araştırma Makalesi
Yazarlar

Orcid: 0000-0001-7118-0174
Yazar: Derya GÜLÇİN (Sorumlu Yazar)
Kurum: ADNAN MENDERES ÜNİVERSİTESİ
Ülke: Turkey


Yazar: Bülent DENİZ
Kurum: ZİRAAT FAKÜLTESİ
Ülke: Turkey


Teşekkür We would like to express our special thanks to Assoc. Prof. Dr. Cumhur Gungoroglu for his guidance to this research paper and sharing his knowledge and experience with us, for his contributions. We also thank the academic staff of Forest Engineering Department of Suleyman Demirel University who organized the scientific activity entitled “Preparing Environmental Databases Using GIS and Satellite Imagery for Natural Ecosystems” (Project No: 1059B291500065), supported by TUBITAK.
Tarihler

Yayımlanma Tarihi : 26 Mart 2020

Bibtex @araştırma makalesi { tjf649747, journal = {Turkish Journal of Forestry}, issn = {}, eissn = {2149-3898}, address = {}, publisher = {Isparta Uygulamalı Bilimler Üniversitesi}, year = {2020}, volume = {21}, pages = {15 - 24}, doi = {10.18182/tjf.649747}, title = {Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey}, key = {cite}, author = {GÜLÇİN, Derya and DENİZ, Bülent} }
APA GÜLÇİN, D , DENİZ, B . (2020). Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey. Turkish Journal of Forestry , 21 (1) , 15-24 . DOI: 10.18182/tjf.649747
MLA GÜLÇİN, D , DENİZ, B . "Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey". Turkish Journal of Forestry 21 (2020 ): 15-24 <https://dergipark.org.tr/tr/pub/tjf/issue/53386/649747>
Chicago GÜLÇİN, D , DENİZ, B . "Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey". Turkish Journal of Forestry 21 (2020 ): 15-24
RIS TY - JOUR T1 - Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey AU - Derya GÜLÇİN , Bülent DENİZ Y1 - 2020 PY - 2020 N1 - doi: 10.18182/tjf.649747 DO - 10.18182/tjf.649747 T2 - Turkish Journal of Forestry JF - Journal JO - JOR SP - 15 EP - 24 VL - 21 IS - 1 SN - -2149-3898 M3 - doi: 10.18182/tjf.649747 UR - https://doi.org/10.18182/tjf.649747 Y2 - 2020 ER -
EndNote %0 Türkiye Ormancılık Dergisi Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey %A Derya GÜLÇİN , Bülent DENİZ %T Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey %D 2020 %J Turkish Journal of Forestry %P -2149-3898 %V 21 %N 1 %R doi: 10.18182/tjf.649747 %U 10.18182/tjf.649747
ISNAD GÜLÇİN, Derya , DENİZ, Bülent . "Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey". Turkish Journal of Forestry 21 / 1 (Mart 2020): 15-24 . https://doi.org/10.18182/tjf.649747
AMA GÜLÇİN D , DENİZ B . Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey. Turkish Journal of Forestry. 2020; 21(1): 15-24.
Vancouver GÜLÇİN D , DENİZ B . Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey. Turkish Journal of Forestry. 2020; 21(1): 24-15.