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Deep Learning Techniques for Large-Scale Date Palm Tree Mapping from Multiscale Remotely Sensed Data

13 September 2023 10:00 am - 11:00 am
The reliable and efficient large-scale mapping of date palm trees from remotely sensed data is crucial for developing palm tree inventories, continuous monitoring, vulnerability assessments, and long-term management of the dating industry. Given the increasing availability of very-high spatial resolution (VHSR) images with limited spectral information, the high intra-class variance of date palm trees, the variations in the spatial resolutions of the data, and the differences in image contexts and backgrounds, accurate large-scale mapping of date palm trees from multiscale and multidate VHSR images can be challenging. This webinar aims to shed light on these challenges and provide state-of-the-art solutions using advanced deep learning techniques. Specifically, attendees will gain a comprehensive understanding of how state-of-the-art semantic and instance segmentation methods can substantially enhance the accuracy and reliability of mapping from multiscale remote sensing datasets.


Researcher and GIS Lab Engineer - University of Sharjah

Mohamed Barakat obtained his bachelor’s in Surveying Engineering from the Sudan University of Sciences and Technology in 2010 and later completed his master’s in Remote Sensing and GIS from University Putra Malaysia (UPM) in 2015. Mohamed serves as an RS and GIS Lab Engineer at the University of Sharjah’s Research Institute of Sciences and Engineering. Additionally, he is working towards his Ph.D. in Remote Sensing from the Faculty of Engineering at UPM, Malaysia. His research interests focus on harnessing the power of remote sensing technologies and state-of-the-art ML techniques in various Earth-related applications (i.e., vegetation and urban mapping, environmental monitoring, and other applications). Mohamed has published more than 25 peer-reviewed articles in the domains of remote sensing and GIS.

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September 13, 2023
10:00 am - 11:00 am +04
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