Spatial pattern analysis of post-fire damages in the Menderes District of Turkey

Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of fo...
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Autor*in:	Çolak, Emre [verfasserIn] Sunar, Filiz [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	remote sensing GIS spectral indices disturbance index land surface temperature burn severity

Übergeordnetes Werk:	Enthalten in: Frontiers of earth science in China - Beijing : Higher Education Press, 2007, 14(2019), 2 vom: 04. Dez., Seite 446-461
Übergeordnetes Werk:	volume:14 ; year:2019 ; number:2 ; day:04 ; month:12 ; pages:446-461

Links:	Volltext

DOI / URN:	10.1007/s11707-019-0786-4

Katalog-ID:	SPR040405559

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520			\|a Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively).
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allfields	10.1007/s11707-019-0786-4 doi (DE-627)SPR040405559 (SPR)s11707-019-0786-4-e DE-627 ger DE-627 rakwb eng 550 ASE Çolak, Emre verfasserin aut Spatial pattern analysis of post-fire damages in the Menderes District of Turkey 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively). remote sensing (dpeaa)DE-He213 GIS (dpeaa)DE-He213 spectral indices (dpeaa)DE-He213 disturbance index (dpeaa)DE-He213 land surface temperature (dpeaa)DE-He213 burn severity (dpeaa)DE-He213 Sunar, Filiz verfasserin aut Enthalten in Frontiers of earth science in China Beijing : Higher Education Press, 2007 14(2019), 2 vom: 04. Dez., Seite 446-461 (DE-627)546007406 (DE-600)2389435-0 1673-7490 nnns volume:14 year:2019 number:2 day:04 month:12 pages:446-461 https://dx.doi.org/10.1007/s11707-019-0786-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 14 2019 2 04 12 446-461
spelling	10.1007/s11707-019-0786-4 doi (DE-627)SPR040405559 (SPR)s11707-019-0786-4-e DE-627 ger DE-627 rakwb eng 550 ASE Çolak, Emre verfasserin aut Spatial pattern analysis of post-fire damages in the Menderes District of Turkey 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively). remote sensing (dpeaa)DE-He213 GIS (dpeaa)DE-He213 spectral indices (dpeaa)DE-He213 disturbance index (dpeaa)DE-He213 land surface temperature (dpeaa)DE-He213 burn severity (dpeaa)DE-He213 Sunar, Filiz verfasserin aut Enthalten in Frontiers of earth science in China Beijing : Higher Education Press, 2007 14(2019), 2 vom: 04. Dez., Seite 446-461 (DE-627)546007406 (DE-600)2389435-0 1673-7490 nnns volume:14 year:2019 number:2 day:04 month:12 pages:446-461 https://dx.doi.org/10.1007/s11707-019-0786-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 14 2019 2 04 12 446-461
allfields_unstemmed	10.1007/s11707-019-0786-4 doi (DE-627)SPR040405559 (SPR)s11707-019-0786-4-e DE-627 ger DE-627 rakwb eng 550 ASE Çolak, Emre verfasserin aut Spatial pattern analysis of post-fire damages in the Menderes District of Turkey 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively). remote sensing (dpeaa)DE-He213 GIS (dpeaa)DE-He213 spectral indices (dpeaa)DE-He213 disturbance index (dpeaa)DE-He213 land surface temperature (dpeaa)DE-He213 burn severity (dpeaa)DE-He213 Sunar, Filiz verfasserin aut Enthalten in Frontiers of earth science in China Beijing : Higher Education Press, 2007 14(2019), 2 vom: 04. Dez., Seite 446-461 (DE-627)546007406 (DE-600)2389435-0 1673-7490 nnns volume:14 year:2019 number:2 day:04 month:12 pages:446-461 https://dx.doi.org/10.1007/s11707-019-0786-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 14 2019 2 04 12 446-461
allfieldsGer	10.1007/s11707-019-0786-4 doi (DE-627)SPR040405559 (SPR)s11707-019-0786-4-e DE-627 ger DE-627 rakwb eng 550 ASE Çolak, Emre verfasserin aut Spatial pattern analysis of post-fire damages in the Menderes District of Turkey 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively). remote sensing (dpeaa)DE-He213 GIS (dpeaa)DE-He213 spectral indices (dpeaa)DE-He213 disturbance index (dpeaa)DE-He213 land surface temperature (dpeaa)DE-He213 burn severity (dpeaa)DE-He213 Sunar, Filiz verfasserin aut Enthalten in Frontiers of earth science in China Beijing : Higher Education Press, 2007 14(2019), 2 vom: 04. Dez., Seite 446-461 (DE-627)546007406 (DE-600)2389435-0 1673-7490 nnns volume:14 year:2019 number:2 day:04 month:12 pages:446-461 https://dx.doi.org/10.1007/s11707-019-0786-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 14 2019 2 04 12 446-461
allfieldsSound	10.1007/s11707-019-0786-4 doi (DE-627)SPR040405559 (SPR)s11707-019-0786-4-e DE-627 ger DE-627 rakwb eng 550 ASE Çolak, Emre verfasserin aut Spatial pattern analysis of post-fire damages in the Menderes District of Turkey 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively). remote sensing (dpeaa)DE-He213 GIS (dpeaa)DE-He213 spectral indices (dpeaa)DE-He213 disturbance index (dpeaa)DE-He213 land surface temperature (dpeaa)DE-He213 burn severity (dpeaa)DE-He213 Sunar, Filiz verfasserin aut Enthalten in Frontiers of earth science in China Beijing : Higher Education Press, 2007 14(2019), 2 vom: 04. Dez., Seite 446-461 (DE-627)546007406 (DE-600)2389435-0 1673-7490 nnns volume:14 year:2019 number:2 day:04 month:12 pages:446-461 https://dx.doi.org/10.1007/s11707-019-0786-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 14 2019 2 04 12 446-461
language	English
source	Enthalten in Frontiers of earth science in China 14(2019), 2 vom: 04. Dez., Seite 446-461 volume:14 year:2019 number:2 day:04 month:12 pages:446-461
sourceStr	Enthalten in Frontiers of earth science in China 14(2019), 2 vom: 04. Dez., Seite 446-461 volume:14 year:2019 number:2 day:04 month:12 pages:446-461
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topic_facet	remote sensing GIS spectral indices disturbance index land surface temperature burn severity
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container_title	Frontiers of earth science in China
authorswithroles_txt_mv	Çolak, Emre @@aut@@ Sunar, Filiz @@aut@@
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Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. 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author	Çolak, Emre
spellingShingle	Çolak, Emre ddc 550 misc remote sensing misc GIS misc spectral indices misc disturbance index misc land surface temperature misc burn severity Spatial pattern analysis of post-fire damages in the Menderes District of Turkey
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topic	ddc 550 misc remote sensing misc GIS misc spectral indices misc disturbance index misc land surface temperature misc burn severity
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title	Spatial pattern analysis of post-fire damages in the Menderes District of Turkey
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title_full	Spatial pattern analysis of post-fire damages in the Menderes District of Turkey
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title_sort	spatial pattern analysis of post-fire damages in the menderes district of turkey
title_auth	Spatial pattern analysis of post-fire damages in the Menderes District of Turkey
abstract	Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively).
abstractGer	Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively).
abstract_unstemmed	Abstract Forest fires, whether caused naturally or by human activity can have disastrous effects on the environment. Turkey, located in the Mediterranean climate zone, experiences hundreds of forest fires every year. Over the past two decades, these fires have destroyed approximately 308000 ha of forest area, threatening the sustainability of its ecosystem. This study analyzes the forest fire that occurred in the Menderes region of Izmir on July 1, 2017, by using pre- and post-fire Sentinel 2 (10 m and 20 m) and Landsat 8 (30 m) satellite images, MODIS and VIIRS fire radiative power (FRP) data (1000 m and 375 m, respectively), and reference data obtained from a field study. Hence, image processing techniques integrated with the Geographic Information System (GIS) database were applied to a satellite image data set to monitor, analyze, and map the effects of the forest fire. The results show that the land surface temperature (LST) of the burned forest area increased from 1 to 11°C. A high correlation (R = 0.81) between LST and burn severity was also determined. The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. A high correlation was found between FRP-slope, and FRP-burn severity (0.96 and 0.88, respectively).
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title_short	Spatial pattern analysis of post-fire damages in the Menderes District of Turkey
url	https://dx.doi.org/10.1007/s11707-019-0786-4
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The burned areas were calculated using two different classification methods, and their accuracy was compared with the reference data. According to the accuracy assessment, the Sentinel (10 m) image classification gave the best result (96.43% for Maximum Likelihood, and 99.56% for Support Vector Machine). The relationship between topographical/forest parameters, burn severity and disturbance index was evaluated for spatial pattern distribution. According to the results, the areas having canopy closure between 71%–100% and slope above 35% had the highest burn incidence. As a final step, a spatial correlation analysis was performed to evaluate the effectiveness of MODIS and VIIRS FRP data in the post-fire analysis. 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Spatial pattern analysis of post-fire damages in the Menderes District of Turkey

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