Evaluation of Fire Severity Indices Based on Pre- and Post-Fire Multispectral Imagery Sensed from UAV
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Carvajal Ramírez, Fernando![Autoridad Universidad de Almería Autoridad Universidad de Almería](/themes/Mirage2/images/autoridades/autoridad.png)
![Autoridad Universidad de Almería Autoridad Universidad de Almería](/themes/Mirage2/images/autoridades/autoridad.png)
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2019-04-26Resumen
Fire severity is a key factor for management of post-fire vegetation regeneration strategies because it quantifies the impact of fire, describing the amount of damage. Several indices have been developed for estimation of fire severity based on terrestrial observation by satellite imagery. In order to avoid the implicit limitations of this kind of data, this work employed an Unmanned Aerial Vehicle (UAV) carrying a high-resolution multispectral sensor including green, red, near-infrared, and red edge bands. Flights were carried out pre- and post-controlled fire in a Mediterranean forest. The products obtained from the UAV-photogrammetric projects based on the Structure from Motion (SfM) algorithm were a Digital Surface Model (DSM) and multispectral images orthorectified in both periods and co-registered in the same absolute coordinate system to find the temporal differences (d) between pre- and post-fire values of the Excess Green Index (EGI), Normalized Difference Vegetation Index (ND...
Palabra/s clave
Fire Severity
UAV
Multispectral Imagery