Digital twin generation and comparison from aerial Lidar and images in urban area

Abstract

Research Problem/Questions – For the integration of spatial data, the obtained point cloud measurements need to be registered to the geodetic coordinate system. In this study, 3D modeling of urban areas was made with Lidar and photogrammetric method. Short Literature Review – Lidar measurements are in the form of a point cloud that represents the measuring surface with its actual dimensions. Integration of measurements into the common geodetic coordinate system is done either using the ground control points (GCP) or with flight data at the time of measurement [1]. Using a ground control points improves accuracy, but has a high workload cost. Geodetic coordinating with direct flight data provides adequately accurate geodetic coordinating for many applications [2]. Methodology – To be able to use the lidar point cloud for mapping, it must be registered to a geodetic coordinate system. The registration to the geodetic coordinate system is done by three methods: GCP, flight data and data processing. Coordinating is easily done with GNSS data during flight. It uses direct georeferencing, global navigation satellite systems (GNSS) and inertial measurement unit (IMU). The GNSS records the position (XYZ coordinates) and the IMU records the rotation, tilt, yaw angles around the axis at the time of recording. These parameters are combined and each measured Lidar point is converted directly into the georeference system. The lidar point cloud is precisely georeferenced with minimal processing. Direct georeferencing is currently the most widely used method for LiDAR point cloud data. Geodetic coordinates of the photogrammetric point cloud are easily done using the camera projection center coordinates recorded by GPS during flight. This process is a fast and efficient method for geodetic coordinating of the photogrammetric point cloud. Results and Conclusions – Different types of land cover can affect point accuracy. However, there was no significant difference between Lidar and photogrammetric point cloud in this study.

Keywords

• Lidar
• photogrametry
• point cloud
• jeodetic koordinate
• urban area modelling

Hava Lidar ve fotoğraflardan kentsel alanların digital ikizinin oluşturulması ve karşılaştırılması

Abstract

Arazi topoğrafyası ve ilişkili detayların nokta bulutu şeklinde sayısallaştırılarak bilgisayar ortamına aktarılması çok sayıda uygulamada vazgeçilmez hale gelmiştir. Araziye ilişkin her türlü planlama, akıllı şehir uygulamaları ve diğer hizmetler için bu sayısal verilerden yararlanılır. Hava Lidar ve fotogrametri geniş alanların kısa sürede sayısallaştırılması için yaygın ölçme teknikleridir. Hava lidar sisteminde belirli bir açı artışı ile yönlendirilen lazer ışınları ile tarama yapılarak nokta bulutu ölçülür. Fotogrametrik nokta bulutu yöntemi teknik bilgi gerektirmez ve düşük maliyetlidir. Konumsal verilerin entegrasyonu için elde edilen nokta bulutu ölçülerinin jeodezik koordinat sistemine dönüştürülmesi gerekir. Bu çalışmada Lidar ve fotogrametrik yöntem ile kentsel alanların 3B modellemesi yapılmıştır. Nokta bulutu verileri uçuş esnasındaki konum bilgileri ile jeodezik koordinat sistemine dönüştürülmüştür.

Keywords

• Lidar
• photogrametry
• point cloud
• jeodetic koordinate
• urban area modelling

References

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