Natural Disasters Detection using GIS and Remote Sensing Analytics:
a Google Earth Engine Workshop
About
Natural Disasters Detection using GIS and Remote Sensing Analytics:
a Google Earth Engine Workshop
An immersive training designed to provide participants with practical, hands-on experience in cloud-based geographic information systems (GIS) and remote sensing using Google Earth Engine to process and analyse satellite imagery to observe and detect natural disasters.
Workshop Level: Entry Level to Intermediate Level
Workshop Language: English
Workshop Requirement: Gmail Account & Google Earth Engine Account
Highlights
- Remote sensing and GIS fundamentals
- Introduction to JavaScript
- Cloud-based geospatial data processing
- Several case studies such as flood mapping, fire damage detection, land cover classification, and environmental change analysis.



Eng. Naseeb Asaad Albakri
Research Assistant at MBRSC Lab
Naseeb Asaad Albakri is a dedicated Research Assistant at the MBRSC Lab, University of Dubai, with four years of experience in remote sensing and GIS. His expertise lies in land classification, environmental monitoring, and SAR image analysis, with a strong focus on studying surface temperature and classification. Before joining MBRSC, he worked as a Research Assistant at the University of Sharjah for 2.5 years, contributing to GIS analysis, research and publishing, and regression analysis. He holds a Master’s in GIS and Remote Sensing and a Bachelor’s in Civil and Environmental Engineering, both from the University of Sharjah. Proficient in ArcGIS Pro and Google Earth Engine, Naseeb is passionate about leveraging geospatial technology to enhance environmental monitoring and disaster response.

Eng. Leena Elneel
Research Assistant at MBRSC Lab
Eng. Leena Elneel is a dedicated researcher at MBRSC Lab at University of Dubai, specialized in developing AI-based solutions for remote sensing applications and data visualization. With nine years of experience in the field, she has worked on integrating AI with remote sensing applications, geospatial analytics, and data-driven solutions. Leena has worked on various remote sensing applications and visualization platforms, and has published researches contributing to advancements in the field. She holds a Bachelor’s degree in Computer Engineering from Khalifa University and a Master’s Degree in Computer Network Security from Heriot-Watt University. Passionate about the intersection of AI and geospatial technologies, she focuses on leveraging innovative computational methods to improve geospatial analysis and decision-making.