Forests are considered as one of the main sources of biodiversity. Forest fires caused by various reasons pose a high risk in terms of biodiversity. Therefore, mapping of fire zones is of great importance in determining the damage caused by the fire, managing the fire process, and planning the interventions in the fire zone. Although remote sensing is a fast and cost-effective methodology for mapping fire zones, the implementation of the remote sensing methodologies is problematic in some respects. The web-based Google Earth Engine makes possible to access the satellite imagery and process the imagery easily. The research area of this study is Muğla, Turkey in where many forest fires broke out in 2021 summer. This study provides an implementation of normalized burn ratio which is widely used to highlight burned areas on Google Earth Engine platform. Both vector data and satellite images were used in the study. The vector data is in the shape file format and was uploaded to the Google Earth Engine platform as a table. The Sentinel-2 imagery was used to calculate normalized burn ratio. The satellite imagery was clipped using the table data. The difference pre-fire and post-fire images was calculated, and the classes were assigned to the pixels according to the normalized burn ratio ranges. The study indicates that finding the burned areas and constructing the burn severity levels can be realized in 1.32 minutes on Google Earth Engine platform.
Published in | American Journal of Remote Sensing (Volume 9, Issue 2) |
DOI | 10.11648/j.ajrs.20210902.12 |
Page(s) | 72-77 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Burn Ratio, Forest Fire, Burn Severity, Remote Sensing
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APA Style
Gulsum Cigdem Cavdaroglu. (2021). Google Earth Engine Based Approach for Finding Fire Locations and Burned Areas in Muğla, Turkey. American Journal of Remote Sensing, 9(2), 72-77. https://doi.org/10.11648/j.ajrs.20210902.12
ACS Style
Gulsum Cigdem Cavdaroglu. Google Earth Engine Based Approach for Finding Fire Locations and Burned Areas in Muğla, Turkey. Am. J. Remote Sens. 2021, 9(2), 72-77. doi: 10.11648/j.ajrs.20210902.12
AMA Style
Gulsum Cigdem Cavdaroglu. Google Earth Engine Based Approach for Finding Fire Locations and Burned Areas in Muğla, Turkey. Am J Remote Sens. 2021;9(2):72-77. doi: 10.11648/j.ajrs.20210902.12
@article{10.11648/j.ajrs.20210902.12, author = {Gulsum Cigdem Cavdaroglu}, title = {Google Earth Engine Based Approach for Finding Fire Locations and Burned Areas in Muğla, Turkey}, journal = {American Journal of Remote Sensing}, volume = {9}, number = {2}, pages = {72-77}, doi = {10.11648/j.ajrs.20210902.12}, url = {https://doi.org/10.11648/j.ajrs.20210902.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20210902.12}, abstract = {Forests are considered as one of the main sources of biodiversity. Forest fires caused by various reasons pose a high risk in terms of biodiversity. Therefore, mapping of fire zones is of great importance in determining the damage caused by the fire, managing the fire process, and planning the interventions in the fire zone. Although remote sensing is a fast and cost-effective methodology for mapping fire zones, the implementation of the remote sensing methodologies is problematic in some respects. The web-based Google Earth Engine makes possible to access the satellite imagery and process the imagery easily. The research area of this study is Muğla, Turkey in where many forest fires broke out in 2021 summer. This study provides an implementation of normalized burn ratio which is widely used to highlight burned areas on Google Earth Engine platform. Both vector data and satellite images were used in the study. The vector data is in the shape file format and was uploaded to the Google Earth Engine platform as a table. The Sentinel-2 imagery was used to calculate normalized burn ratio. The satellite imagery was clipped using the table data. The difference pre-fire and post-fire images was calculated, and the classes were assigned to the pixels according to the normalized burn ratio ranges. The study indicates that finding the burned areas and constructing the burn severity levels can be realized in 1.32 minutes on Google Earth Engine platform.}, year = {2021} }
TY - JOUR T1 - Google Earth Engine Based Approach for Finding Fire Locations and Burned Areas in Muğla, Turkey AU - Gulsum Cigdem Cavdaroglu Y1 - 2021/10/05 PY - 2021 N1 - https://doi.org/10.11648/j.ajrs.20210902.12 DO - 10.11648/j.ajrs.20210902.12 T2 - American Journal of Remote Sensing JF - American Journal of Remote Sensing JO - American Journal of Remote Sensing SP - 72 EP - 77 PB - Science Publishing Group SN - 2328-580X UR - https://doi.org/10.11648/j.ajrs.20210902.12 AB - Forests are considered as one of the main sources of biodiversity. Forest fires caused by various reasons pose a high risk in terms of biodiversity. Therefore, mapping of fire zones is of great importance in determining the damage caused by the fire, managing the fire process, and planning the interventions in the fire zone. Although remote sensing is a fast and cost-effective methodology for mapping fire zones, the implementation of the remote sensing methodologies is problematic in some respects. The web-based Google Earth Engine makes possible to access the satellite imagery and process the imagery easily. The research area of this study is Muğla, Turkey in where many forest fires broke out in 2021 summer. This study provides an implementation of normalized burn ratio which is widely used to highlight burned areas on Google Earth Engine platform. Both vector data and satellite images were used in the study. The vector data is in the shape file format and was uploaded to the Google Earth Engine platform as a table. The Sentinel-2 imagery was used to calculate normalized burn ratio. The satellite imagery was clipped using the table data. The difference pre-fire and post-fire images was calculated, and the classes were assigned to the pixels according to the normalized burn ratio ranges. The study indicates that finding the burned areas and constructing the burn severity levels can be realized in 1.32 minutes on Google Earth Engine platform. VL - 9 IS - 2 ER -