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About

Michael Arens is a leading researcher in geospatial data analysis, specializing in change detection, 3D sensing, and remote sensing technologies. His work primarily focuses on developing automated methods for detecting environmental and urban changes using advanced sensor data, including airborne laser scanning (ALS) and mobile laser scanning. Arens’s major contributions include pioneering object-based analysis for change detection in urban areas, as demonstrated in his most-cited paper, "Change detection in urban areas by object-based analysis and on-the-fly comparison of multi-view ALS data" (87 citations). He also advanced low-cost depth sensor technology, with his accuracy analysis of commodity sensors like the Kinect V2 (35 citations) influencing computer vision and robotics applications. His research on automatic change detection using mobile laser scanning and performance evaluation of UAV-based location recognition further underscores his impact in 3D environment monitoring. With a total of over 139 citations across his top works, Arens has significantly shaped the fields of geospatial analysis and autonomous systems, providing foundational methods for real-time, multi-temporal data comparison that are critical for urban planning, security, and robotics.