Mr. Usman Ahmed Khan | Remote Sensing | Best Researcher Award
Manager at Suparco, Pakistanđź“–
Hafiz Usman Ahmed Khan is a geospatial expert specializing in remote sensing, GIS, and artificial intelligence (AI)-based land use and land cover (LULC) analysis. Currently working at SUPARCO, he leverages geospatial technologies to support national development projects and drive innovative solutions in urban planning and environmental monitoring. With extensive experience in remote sensing applications, he focuses on integrating artificial neural networks (ANN) for precise LULC prediction and sustainable urban development.
Profile
Education Background🎓
- MS – Space Technology Application, Beihang University, Beijing, China
- BS – Space Sciences, Punjab University, Lahore, Pakistan
Professional Experience🌱
At SUPARCO, Hafiz Usman has played a key role in multiple geospatial projects, specializing in land use change detection, environmental monitoring, and urban heat island analysis. His expertise in remote sensing data processing, GIS-based mapping, and AI-driven urban planning enables him to provide data-driven solutions for national and regional development projects. His work has significantly contributed to urban sustainability, climate impact assessment, and natural resource management.
Research interests include:
- Land Use and Land Cover (LULC) Prediction using AI and machine learning models
- Urban Heat Island (UHI) Effect and its environmental implications
- Glacier Monitoring through remote sensing techniques
- Forest Cover Change Analysis and deforestation trends
- Integration of AI in Geospatial Sciences
Author Metrics
Hafiz Usman has published multiple research papers in international journals, covering urban expansion, environmental monitoring, and remote sensing applications. His notable works include:
- Evaluating the Impact of Expansion on Urban Thermal Surroundings: A Case Study of Lahore Metropolitan City, Pakistan
- Monitoring and Mapping Batura Glacier using Remote Sensing
- Application of Remote Sensing and GIS in Forest Cover Change in District Haripur, Pakistan
- Future Simulation of Land Use Changes in Rapidly Urbanizing South China Based on Land Change Modeler and Remote Sensing Data
- Recognized for outstanding contributions to geospatial research and remote sensing applications
- Contributor to national-level development projects at SUPARCO
- Acknowledged for innovative approaches in AI-based LULC analysis
1. Forecasting Urban Sprawl Dynamics in Islamabad: A Neural Network Approach
Journal: Remote Sensing
Publication Date: January 2025
Article Type: Journal Article
DOI: 10.3390/rs17030492
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Abstract:
This study employs a neural network-based approach to predict urban sprawl dynamics in Islamabad, Pakistan. Utilizing remote sensing data, the research integrates deep learning models to analyze spatial expansion trends and assess the impact of urbanization on land use and environmental sustainability. The study compares traditional urban growth models with AI-driven neural networks, demonstrating improved accuracy in forecasting future urban expansion patterns. The findings provide valuable insights for urban planners, policymakers, and environmentalists to implement sustainable development strategies.
Conclusion
Hafiz Usman Ahmed Khan has demonstrated exemplary expertise in remote sensing, GIS, and AI-based geospatial research. His contributions to national development projects, urban sustainability, and climate change analysis make him a deserving candidate for the Best Researcher Award. With his continued focus on AI-driven geospatial analytics, his research has the potential to reshape the future of remote sensing applications worldwide.