UN-SPIDER Recommended Practice for Burn Severity Mapping: a guide using QGIS, SCP, and Landsat 8

The "United Nations Platform for Disaster Management and Emergency Response" (UN-SPIDER) is a United Nations program that aims to "ensure that all countries and international and regional organizations have access to and develop the capacity to use all types of space-based information to support the full disaster management cycle".
In particular, UN-SPIDER aims to ensure access and use of space technologies for humanitarian aid and emergency response, during all phases of the disaster management cycle.

The UN-SPIDER website provides several recommended practices for fostering the use of satellite data in the various phases of disaster management.
In this post I am glad to suggest this methodology for mapping burn severity in the disaster cycle phase of recovery and reconstruction.

UN-SPIDER website

The purpose of the recommended practice is to assess the post-fire burn severity with a methodology that uses remote sensing images, and the calculation of the Normalized Burn Ratio (NBR) in pre-fire and post-fire images.
In particular, a step by step guide is provided to assess burn severity using QGIS and the Semi-Automatic Classification Plugin. You can read the whole guide here.
Landsat 8 images are used in the guide, covering a large forest area in Empedrado (Chile) that was affected by a very large wildfire in January 2017.

The guide is divided in two parts:
  1. an overview of QGIS
  2. the mapping of burn severity mapping using QGIS and the Semi-Automatic Classification Plugin, and in particular:
    • Conversion to reflectance
    • Calculation of the Normalized Burn Ratio (NBR)
    • Calculation of the delta NBR (dNBR)
    • Calculation of the burn severity map 
The result of the process is a map that allows for the assessment of  burn severity from low to high levels.
The methodology is described in detail and several figures guide you through the process, easing the reproducibility of the method to any study area affected by wildfires.

I am glad that open-source software is recommended for disaster management, and I am very grateful to UN-SPIDER for providing such useful guides.
Of course, I invite you to read also the other guides here and to visit the.UN-SPIDER website for other useful resources.

For any comment or question, join the Facebook group and the Google+ Community about the Semi-Automatic Classification Plugin.

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