PhD Seminar - Utilizing the Unexplored Potential of Remote Sensing Derived Fire Characteristics in Fire Danger Modelling

Sami’s PhD Project explores the potential of Remote Sensing derived fire characteristics in fire danger modelling including development of a new fire danger index for Australia.

schedule Date & time
Date/time
23 Sep 2022 4:00pm
person Speaker

Speakers

Sami Shah
contact_support Contact

Content navigation

Register

Description

Sami’s PhD Project explores the potential of Remote Sensing derived fire characteristics in fire danger modelling including development of a new fire danger index for Australia. Remote sensing derived fire characteristics used for fire danger modeling has been limited to the fire ignitions or fires of relatively smaller sizes. However, the remote sensing derived fire characteristics such as fire sizes and fire radiative power provide opportunities to develop remote sensing-based fire danger models that encompass a whole range of the fire danger conditions.

Sami’s PhD project explored the relationship of remote sensing derived burned area with the McArthur’s fire danger indices to relate a more quantifiable fire characteristics to the McArthur’s fire danger classes. More importantly, his PhD project developed an integrated fire danger index for Australia using remote sensing based fire sizes and fire radiative power using Random Forest (machine learning algorithm).
 

About the Speaker

With a civil engineering background, Sami Shah changed his professional line to Remote Sensing and GIS data expert after his master’s degree in Remote Sensing and GIS from National University of Sciences and Technology, Pakistan in 2015. Since then, Sami has been associated with an organization specialized in performing commercial surveying, remote sensing and GIS based tasks. His remote sensing and GIS expertise are specific to drought monitoring and fire danger modelling.

Location

Frank Fenner Seminar Room, 141 Linnaeus Way, Acton ACT 2601, & online via Zoom.

-35.2779772, 149.1153748