Determining the Regeneration Dynamics of Burned Forest Areas Using Satellite Images and Climate Parameters

Dilek Küçük Matcı; Uğur Avdan; Murat Kuruca; Deniz Hakan Durmuş; Sümeyye Aktaş Karadoğan

Makale detayları

Determining the Regeneration Dynamics of Burned Forest Areas Using Satellite Images and Climate Parameters

Yazarlar:

Dilek Küçük Matcı | Uğur Avdan | Murat Kuruca | Deniz Hakan Durmuş | Sümeyye Aktaş Karadoğan

Yayıncı:

Istanbul University

Ana Başlıklar:

Photogrammetry and Remote Sensing

Dergi:

International Journal of Environment and Geoinformatics Vol.11 Issue 4, pp.70-77

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001328482

pISSN:

2148-9173

Anahtar kelimeler:

Özet:

 Forest fires significantly impact ecosystems by reducing biological diversity and sustainability. Observing the regeneration process of burned areas and identifying factors influencing this process, monitoring the regeneration status, determining the spread of invasive species, and understanding the impact on wildlife and its evolution contribute to assessing the consequences of this disaster. However, on-site monitoring of burned areas is a time-consuming and challenging process. Therefore, in this study, the regeneration processes of burned forest areas and the factors influencing these processes were investigated using data from remote sensing systems. In this context, the regeneration processes of areas affected by the forest fire in Antalya Kumluca in 2016 were examined. Landsat-8 satellite images of the study area were obtained with the assistance of Google Earth Engine GEE. NBR Normalized Burn Ratio showing the severity of the burn and NDVI Normalized Difference Vegetation Index indicating the vitality status of the forest were calculated using these images. In addition, parameters such as wind speed, soil moisture, precipitation amount, Land Surface Temperature LST, and air temperature were obtained from data provided by remote sensing systems through GEE. Multiple regression analysis was conducted to identify the parameters affecting the regeneration process.

 Forest fires significantly impact ecosystems by reducing biological diversity and sustainability. Observing the regeneration process of burned areas and identifying factors influencing this process, monitoring the regeneration status, determining the spread of invasive species, and understanding the impact on wildlife and its evolution contribute to assessing the consequences of this disaster. However, on-site monitoring of burned areas is a time-consuming and challenging process. Therefore, in this study, the regeneration processes of burned forest areas and the factors influencing these processes were investigated using data from remote sensing systems. In this context, the regeneration processes of areas affected by the forest fire in Antalya Kumluca in 2016 were examined. Landsat-8 satellite images of the study area were obtained with the assistance of Google Earth Engine GEE. NBR Normalized Burn Ratio showing the severity of the burn and NDVI Normalized Difference Vegetation Index indicating the vitality status of the forest were calculated using these images. In addition, parameters such as wind speed, soil moisture, precipitation amount, Land Surface Temperature LST, and air temperature were obtained from data provided by remote sensing systems through GEE. Multiple regression analysis was conducted to identify the parameters affecting the regeneration process.

 Forest fires significantly impact ecosystems by reducing biological diversity and sustainability. Observing the regeneration process of burned areas and identifying factors influencing this process, monitoring the regeneration status, determining the spread of invasive species, and understanding the impact on wildlife and its evolution contribute to assessing the consequences of this disaster. However, on-site monitoring of burned areas is a time-consuming and challenging process. Therefore, in this study, the regeneration processes of burned forest areas and the factors influencing these processes were investigated using data from remote sensing systems. In this context, the regeneration processes of areas affected by the forest fire in Antalya Kumluca in 2016 were examined. Landsat-8 satellite images of the study area were obtained with the assistance of Google Earth Engine GEE. NBR Normalized Burn Ratio showing the severity of the burn and NDVI Normalized Difference Vegetation Index indicating the vitality status of the forest were calculated using these images. In addition, parameters such as wind speed, soil moisture, precipitation amount, Land Surface Temperature LST, and air temperature were obtained from data provided by remote sensing systems through GEE. Multiple regression analysis was conducted to identify the parameters affecting the regeneration process.

 Forest fires significantly impact ecosystems by reducing biological diversity and sustainability. Observing the regeneration process of burned areas and identifying factors influencing this process, monitoring the regeneration status, determining the spread of invasive species, and understanding the impact on wildlife and its evolution contribute to assessing the consequences of this disaster. However, on-site monitoring of burned areas is a time-consuming and challenging process. Therefore, in this study, the regeneration processes of burned forest areas and the factors influencing these processes were investigated using data from remote sensing systems. In this context, the regeneration processes of areas affected by the forest fire in Antalya Kumluca in 2016 were examined. Landsat-8 satellite images of the study area were obtained with the assistance of Google Earth Engine GEE. NBR Normalized Burn Ratio showing the severity of the burn and NDVI Normalized Difference Vegetation Index indicating the vitality status of the forest were calculated using these images. In addition, parameters such as wind speed, soil moisture, precipitation amount, Land Surface Temperature LST, and air temperature were obtained from data provided by remote sensing systems through GEE. Multiple regression analysis was conducted to identify the parameters affecting the regeneration process.

Makale detayları

Determining the Regeneration Dynamics of Burned Forest Areas Using Satellite Images and Climate Parameters

Yazarlar:

Dilek Küçük Matcı | Uğur Avdan | Murat Kuruca | Deniz Hakan Durmuş | Sümeyye Aktaş Karadoğan

Yayıncı:

Istanbul University

Ana Başlıklar:

Photogrammetry and Remote Sensing

Dergi:

International Journal of Environment and Geoinformatics Vol.11 Issue 4, pp.70-77

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001328482

pISSN:

2148-9173

Remote Sensing

Forest Fires

NDVI

NBR

Regeneration Process

Sayı

Makale detayları

Determining the Regeneration Dynamics of Burned Forest Areas Using Satellite Images and Climate Parameters

Yazarlar: Dilek Küçük Matcı | Uğur Avdan | Murat Kuruca | Deniz Hakan Durmuş | Sümeyye Aktaş Karadoğan

Yayıncı: Istanbul University

Ana Başlıklar: Photogrammetry and Remote Sensing

Dergi: International Journal of Environment and Geoinformatics Vol.11 Issue 4, pp.70-77

Belge Tipi: Makale

Yayın Tarihi: 12/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001328482

pISSN: 2148-9173

Remote Sensing

Forest Fires

NDVI

NBR

Regeneration Process

Sayı

Yazarlar:

Dilek Küçük Matcı | Uğur Avdan | Murat Kuruca | Deniz Hakan Durmuş | Sümeyye Aktaş Karadoğan

Yayıncı:

Istanbul University

Ana Başlıklar:

Photogrammetry and Remote Sensing

Dergi:

International Journal of Environment and Geoinformatics Vol.11 Issue 4, pp.70-77

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001328482

pISSN:

2148-9173