Abstract
This paper aims to assess the ways in which multi-resolution object-based classification methods can be used to group urban environments made up of a mixture of buildings, sub-elements such as car parks, roads, shades and pavements and foliage such as grass and trees. This involves using both unmanned aerial vehicles (UAVs) which provide high-resolution mosaic Orthoimages and generate a Digital Surface Model (DSM). For the study area chosen for this paper, 400 Orthoimages with a spatial resolution of 7 cm each were used to build the Orthoimages and DSM, which were georeferenced using well distributed network of ground control points (GCPs) of 12 reference points (RMSE = 8 cm). As these were combined with onboard RTK-GNSS-enabled 2-frequency receivers, they were able to provide absolute block orientation which had a similar accuracy range if the data had been collected by traditional indirect sensor orientation. Traditional indirect sensor orientation involves the GNSS receiver in the UAV receiving a differential signal from the base station through a communication link. This allows for the precise position of the UAV to be established, as the RTK uses correction, allowing position, velocity, altitude and heading to tracked, as well as the measurement of raw sensor data. By assessing the results of the confusion matrices, it can be seen that the overall accuracy of the object-oriented classification was 84.37%. This has an overall Kappa of 0.74 and the data that had poor classification accuracy included shade, parking lots and concrete pavements. These had a producer accuracy (precision) of 81%, 74% and 74% respectively, while lakes and solar panels each scored 100% in comparison, meaning that they had good classification accuracy.
Highlights
In recent years, photogrammetry has been recognised as an extremely good surveying method when trying to produce 3D images of the Earth’s surface
In spite of these advantages though, unmanned aerial vehicles (UAVs) often have weight and cost restrictions which mean that the sensors used in them are often lower quality than those that would be used during manned aerial photography
If the file is saved in the Exchangeable Image File Format (EXIF), Pix4D Mapper Pro will load it for Bundle Block Adjustment (BBA), as well as assessing its estimated position accuracy
Summary
Photogrammetry has been recognised as an extremely good surveying method when trying to produce 3D images of the Earth’s surface. The development of unmanned aerial vehicles (UAVs), has helped to make photogrammetry a more accessible means if data collection allows for the collection of images with high spatial and spectral resolutions in a way that can save both money and time. These technological advances allow for high-quality mapping of the earth’s surface using Orthoimages and mean that 3D models (meshes) of the earth’s surface can be created with high resolution and accuracy. This method is superior to VHR imagery as UAV Orthoimages are able to combine object segmentation and the fuzzy dimension digital classification method to recognise features in a diverse environment, while objects may be too spectrally similar for VHR to be used effectively
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
