{'fraction_non_alphanumeric': 0.01240694789081886, 'fraction_numerical': 0.00041356492969396195, 'mean_word_length': 5.591280653950954, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
ALTERNATIVE APPROACHES FOR UTILIZING LIDAR DATA AS A SOURCE OF CONTROL INFORMATION FOR PHOTOGRAMMETRIC MODELS

Laser scanning (LIDAR) is a recent technology that is receiving an increasing interest from professionals dealing with mapping applications. The interest in LIDAR is attributed to the rich geometric surface information provided by the data in the form of dense non-selective points. On the other hand, photogrammetric processing of stereo-images provides an accurate surface model represented by few points as well as a wealth of semantic information about the photographed objects. Considering the nature of photogrammetric and LIDAR data, it is clear that the two systems provide complementary information. However, the complementary information can only be fully utilized after successful alignment/absolute orientation of the photogrammetric and LIDAR models relative to a common reference frame. This paper deals with two alternative approaches for utilizing linear features derived from LIDAR data as control information for aligning the photogrammetric model relative to the LIDAR reference frame. The first approach incorporates LIDAR lines as control information directly in a photogrammetric triangulation. The second approach starts by generating a photogrammetric model through a photogrammetric triangulation using an arbitrary datum (no control information). LIDAR features are then used as control information for the absolute orientation of the photogrammetric model. A mathematical model is derived to utilize the LIDAR features for the absolute orientation of the photogrammetric model. These features can be extracted from range data using various methods. For example, planar patches can be extracted from 3dimensional LIDAR data through segmentation techniques. Then, neighbouring planar patches can be intersected to generate linear features corresponding to object space discontinuities. LIDAR data pre-processing for the purpose of feature extraction is not a trivial task. An alternative and simpler approach is to use recorded intensities by laser scanners to directly identify and extract linear features from the LIDAR data. The paper presents a quantitative analysis of the performance of the different approaches for extracting linear features from the LIDAR data. The analysis is based on the quality of fit of the final alignment between the LIDAR and photogrammetric models.