Northern Syria Burned Land Analysis Dataset - May June 2019

**UNOSAT code: FR20191016LBN** This map illustrates satellite-detected burned areas in Al-Haffa and Al-Qardaha Districts, Lattakia Governorate, Syria, based on SPOT-6 imagery acquired on 21 October 2019. Approximately 433 ha of potentially burned areas were detected by UNOSAT as of 21 October 2019 (red). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

**UNOSAT code: FR20191016LBN** This map illustrates satellite-detected fire hotspots based on the analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) accessed via NASA FIRMS, between October 15-16, 2019. 30 hotspots were detected in Lebanon and 121 hotspots were detected in three analysed Governorates (i.e. Homs, Lattakia and Tartous) in Syria. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Dates of Images: Post-Event: May 20, 2026 Pre-Event: April 20, 2026 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Sentinel2- dataset at 10m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Check fire containment and image dates for further context on image timing. Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. Higher dNBR values represent a proxy for greater burn severity. Negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: Copernicus Sentinel-2 Resolution: 10 meters Credits: NASA/MSFC, USGS Service URL: See individual Layers. WMS Endpoint: See Descriptions of individual layers.

**UNOSAT code: FR20191016LBN** This map illustrates satellite-detected burned areas in Akkar, Tartous and Homs Governorates, in Lebanon and Syria, based on SPOT-6 imagery acquired on 21 October 2019. Approximately 549 ha of potentially burned areas were detected by UNOSAT as of 21 October 2019 (red). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

This map illustrates satellite-detected damage in the city of Idlib, Syrian Arab Republic. Using satellite imagery acquired 01 August 2016, 06 April 2015, 02 May 2014, and 15 September 2013 UNITAR - UNOSAT identified a total of 1,267 affected structures within the city. Approximately 278 of these were destroyed, 353 severely damaged, and 636 moderately damaged. While much of the city was damaged by 06 April 2015, 768 structures were newly damaged and 39 structures experienced an increase in damage between that date and 01 August 2016. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

This map illustrates satellite-detected damage density in the city of Idlib, Syrian Arab Republic. Using satellite imagery acquired 06 April 2015, 02 May 2014, 15 September 2013, and 22 March 2010 UNITAR - UNOSAT identified a total of 545 affected structures within the city. Approximately 176 of these were destroyed, 180 severely damaged, and 189 moderately damaged. While much of the city was damaged by 02 May 2014, 249 structures were newly damaged and 5 structures experienced an increase in damage between that date and 06 April 2015. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.