Browsing by Author "Sivrikaya, F."

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Assessing Spatio-Temporal Change and Dynamics of Forest Ecosystem Succession Using Patch Analysis
(2023.01.01) Sivrikaya, F.; Çakir, G.
Aim of study: This study focuses on creating a secondary forest succession (SFS) map between 1972 and 2014 according to the Clementsian theory based on land cover, assessing the spatio-temporal pattern of forest succession change, and determining the factors affecting the forest ecosystem.Area of study: This study was conducted at the cermik Forest Enterprise (FE) in Diyarbakir city, located in the Southeastern Anatolia Region of Turkiye.Material and methods: Clementsian theory, Remote Sensing (RS), and Geographical Information System (GIS) were used to generate the SFS map. Patch Analyst 4.0 was used to determine changes in spatiotemporal patterns with landscape indices.Main results: The total forested area increased from 32405.1 ha (13% of the study area) in 1972 to 45054.7 ha (18% of the study area) in 2014, with a net increase of 12649.6 ha. It was determined that the progressive succession area was 87736.7 ha, the regressive succession area was 39216.5 ha, and the unchanged succession area was approximately 129989.6 ha. The number of patches increased over a 42 -year period.Research highlights: The forest ecosystem was more fragmented, with patches becoming more irregular, complex, and edgy.
Forest fire risk mapping with Landsat 8 OLI images: Evaluation of the potential use of vegetation indices
(Elsevier B.V., 2024) Sivrikaya, F.; Günlü, A.; Küçük, Ö.; Ürker, O.
Fire is one of the most important natural catastrophes threatening the forest ecosystem. The severity and frequency of forest fires are increasing daily due to the increase in population in vulnerable areas and the effects of global climate change. Creating fire risk maps and using them to take the required protective actions to prevent fires will decrease the adverse effects of forest fires. This study focused on producing and comparing fire risk maps based on four vegetation indices, the Normalized Burn Ratio (NBR) index, Normalized Burn Ratio Thermal (NBRT) index, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI) and data gathered with the use of remote sensing devices. The Muğla Regional Directorate of Forestry, which is in the Mediterranean climate zone and has experienced mega-fires, was selected as the case study area. Fire risk maps were prepared for the four vegetation indices from Landsat 8 OLI satellite images. Receiver operating characteristic curves and 195 fire ignition points that occurred in 2021 from July 5 to the end of the year were used to assess the accuracy of fire risk maps. Most fire ignition locations (>90%) were in high- and extremely high-risk fire areas on the maps prepared according to the NBR, NDWI, and NDVI. The fact that almost all of the fires occurred in high-risk areas revealed that the study area was sensitive to fire and that the vegetation indices used to draw up the risk maps were highly accurate in predicting where fires might occur. The accuracy results showed that the area under the curve was 0.842 for the NBR, 0.835 for the NDWI, 0.812 for the NBRT, and 0.810 for the NDVI. The NBR approach was more precise than the other models in providing information for fire risk maps. Risk maps created with the NBR could help decision-makers to take precautions and minimize fire damage.
Forest fire risk mapping with Landsat 8 OLI images: Evaluation of the potential use of vegetation indices
(2024.01.01) Sivrikaya, F.; Günlü, A.; Küçük, Ö.; Ürker, O.
Fire is one of the most important natural catastrophes threatening the forest ecosystem. The severity and frequency of forest fires are increasing daily due to the increase in population in vulnerable areas and the effects of global climate change. Creating fire risk maps and using them to take the required protective actions to prevent fires will decrease the adverse effects of forest fires. This study focused on producing and comparing fire risk maps based on four vegetation indices, the Normalized Burn Ratio (NBR) index, Normalized Burn Ratio Thermal (NBRT) index, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI) and data gathered with the use of remote sensing devices. The Mugla Regional Directorate of Forestry, which is in the Mediterranean climate zone and has experienced mega-fires, was selected as the case study area. Fire risk maps were prepared for the four vegetation indices from Landsat 8 OLI satellite images. Receiver operating characteristic curves and 195 fire ignition points that occurred in 2021 from July 5 to the end of the year were used to assess the accuracy of fire risk maps. Most fire ignition locations (>90%) were in high- and extremely high-risk fire areas on the maps prepared according to the NBR, NDWI, and NDVI. The fact that almost all of the fires occurred in high-risk areas revealed that the study area was sensitive to fire and that the vegetation indices used to draw up the risk maps were highly accurate in predicting where fires might occur. The accuracy results showed that the area under the curve was 0.842 for the NBR, 0.835 for the NDWI, 0.812 for the NBRT, and 0.810 for the NDVI. The NBR approach was more precise than the other models in providing information for fire risk maps. Risk maps created with the NBR could help decision-makers to take precautions and minimize fire damage.