Mr. Rahman possesses more than 20 years of professional experience at CEGIS and is a seasoned Land Management Expert and Remote Sensing Specialist with extensive involvement in land use mapping, geospatial data management, and satellite-image–based analytical workflows. His expertise covers the full spectrum of land-related data generation, processing, interpretation, verification, and application in various infrastructure and environmental projects, utilizing advanced GIS and remote sensing tools. He is highly skilled in utilizing advanced GIS and remote sensing technologies to produce precise, reliable, and decision-ready geospatial outputs.
He has in-depth knowledge and hands-on experience in high-resolution satellite image interpretation, GNSS/RTK-based land surveys, mauza and parcel-level mapping, and geodatabase development to support land use planning, land acquisition (LAP/RAP), river management, and infrastructure development initiatives. His core strengths include designing and overseeing field survey operations, developing technical workplans, and ensuring quality control across all GIS/RS deliverables.
Mr. Rahman has specialized capabilities in Land Use/Land Cover (LULC) mapping using both high- and medium-resolution satellite datasets. He is highly proficient in accurately extracting key land classes—such as agricultural areas, forests, wetlands, settlements, waterbodies, riverine zones, and infrastructure—through a combination of manual interpretation and advanced image classification techniques.
Demonstrating strong leadership and organizational skills, he has effectively planned, managed, and supervised large-scale multidisciplinary teams, guided complex project workflows, ensured timely delivery of outputs, and contributed to national-scale land management initiatives. His combined strengths in technical expertise and project management have enabled him to support major programs in land governance, disaster risk reduction, river management, environmental planning, remote sensing analytics, and geospatial Land Information Systems (LIS).
