GIS/ Remote sensing expert

Rate, USD
Not specified
Work schedule
Full Time,
Language skills
Arabic, English
Available for Hire
Yes
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About me

I am a GIS and Remote Sensing expert with over 12 years of experience in geospatial analysis, remote sensing applications, natural resources, environment, and urban planning. I have proven expertise in leveraging satellite imagery, LiDAR UAV/drone data, and AI-powered geospatial analytics to support smart city development, environmental monitoring, and infrastructure management. I am adept at using ArcGIS Pro, QGIS, ERDAS Imagine, ENVI, Python, and machine learning for geospatial solutions (GeoAI).

Throughout my career, I have developed AI-based land-use classification models using random forest classifiers for Sentinel-2 and Landsat imagery to monitor urban expansion. I have automated object detection models using Pytorch and GeoAI for disaster risk analysis and streamlined geospatial workflows with Python to enhance data processing efficiency. I have collaborated with government agencies on flood risk mapping and environmental impact assessments.

I have created 3D terrain models (DEM/DTM) for hydrological, climatic, and soil modeling as well as flood risk analysis. Additionally, I have developed interactive web maps using ArcGIS Online and PowerBI to support real-time municipal decision-making. My experience also includes leading projects with budgets exceeding $500k and managing teams of over 15 members.

Earlier in my career, I worked as a Geospatial Analyst where I developed and implemented robust data collection processes, acquired satellite data, created databases and metadata, and ensured data quality control. I processed high-resolution satellite and drone imagery for vegetation health assessment and urban green space analysis. I supported climate risk finance initiatives by integrating satellite data with GIS platforms and restructuring databases.

I have provided training and technical support to end-users, enabling them to access, analyze, and apply geospatial data effectively. I continuously update my skills through certifications and advanced training in AI for flood risk modeling, UAV/drone mapping, time series crop monitoring, spectroscopy, eco-hydrology, climate change, and natural resource management.

I am fluent in English and have a strong preference for Arabic. My educational background includes a Ph.D. in remote sensing and geographic information systems from the Sudan Academy of Science, and M.Sc. and B.Sc. degrees with honors in Agriculture from the University of Khartoum. I have been recognized with prestigious awards for academic excellence in soil and environmental science.




Education

2008/2011 Ph.D. in Remote Sensing and Geographic Information System @ Sudan Academy of Science
1996/1999 M.Sc. in Agriculture @ University of Khartoum

Department of Soil and Environmental Science, Faculty of Agriculture

1991/1996 B.Sc. (Honors) in Agriculture @ University of Khartoum

Department of Soil and Environmental Science, Faculty of Agriculture


Experience

2013 - 2025 GIS & Remote Sensing Expert @ Remote Sensing Authority - National Research Center

Developed AI-based land-use classification models using random forest classifier for Sentinel-2 & Landsat imagery for urban expansion monitoring. Automated object detection model using Pytorch, GeoAI for disaster risk analysis. Automated geospatial workflows using Python to enhance data processing efficiency. Collaborated with government agencies on flood risk mapping & environmental impact assessments. Created 3D terrain models (DEM/DTM) for hydrological, climatic, soil modeling, flood risk. Created interactive web maps (ArcGIS Online, PowerBI) for real-time municipal decision-making.

2005 - 2013 Geospatial Analyst @ Remote Sensing Authority - National Research Center

Developed and implemented robust data collection, acquiring satellite data, database creation, metadata creation, data quality control. Processed high-resolution satellite and drone imagery for vegetation health assessment and urban green space analysis. Supported climate risk finance initiatives by integrating satellite data with GIS platforms, database restructuring and building. Developed the entire data pipeline, from raw satellite data ingestion to feature engineering and machine learning modeling. Provided training and technical support to end-users.


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