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The use of Global Positioning System (GPS) precise point positioning (PPP) on a fixed‐wing unmanned aerial vehicle (UAV) is demonstrated for photogrammetric mapping at accuracies of centimetres in planimetry and about a decimetre in height, from flights of 25 to 30 minutes in duration. The GPS PPP estimated camera station positions are used to constrain estimates of image positions in the photogrammetric bundle block adjustment, as with relative GPS positioning. GPS PPP alleviates all spatial operating constraints associated with the installation and the use of ground control points, a local ground GPS reference station or the need to operate within the bounds of a permanent GPS reference station network. This simplifies operational logistics and enables large‐scale photogrammetric mapping from UAVs in even the most remote and challenging geographic locations.

The limited quality of location data poses a major problem to those who want to use such data for research or safety management. The proportion of crashes unassigned to specific road locations is considerable. This fact is sometimes overlooked because crash database queries return crashes assignable to locations but do not issue warnings about crashes that are not assignable. Without reliable location information, crash data are of limited use for more refined safety research and even for basic road safety management. Probabilistic linking techniques are frequently chosen to link medical, census, and other population records, mainly for medical research but also for security concerns and market studies. This paper presents a first application of the probabilistic method of assigning crashes to roads through linking road crash records with road inventory records. Because of missing or incorrect data, multiple locations are candidates, and probabilistic linking offers a solution by selecting the highest-likelihood locations. This paper uses the Bayesian approach to link data in a version specialized for linking one-to-many records.

ABSTRACT:The Iterative Closest Point (ICP) algorithm is prevalent for the automatic fine registration of overlapping pairs of terrestrial laser scanning (TLS) data. This method along with its vast number of variants, obtains the least squares parameters that are necessary to align the TLS data by minimizing some distance metric between the scans. The ICP algorithm uses a "model-data" concept in which the scans obtain differential treatment in the registration process depending on whether they were assigned to be the "model" or "data". For each of the "data" points, corresponding points from the "model" are sought. Another concept of "symmetric correspondence" was proposed in the Point-to-Plane (P2P) algorithm, where both scans are treated equally in the registration process. The P2P method establishes correspondences on both scans and minimizes the point-to-plane distances between the scans by simultaneously considering the stochastic properties of both scans. This paper studies both the ICP and P2P algorithms in terms of their consistency in registration parameters for pairs of TLS data. The question being investigated in this paper is, should scan A be registered to scan B, will the parameters be the same if scan B were registered to scan A? Experiments were conducted with eight pairs of real TLS data which were registered by the two algorithms in the forward (scan A to scan B) and backward (scan B to scan A) modes and the results were compared. The P2P algorithm was found to be more consistent than the ICP algorithm. The differences in registration accuracy between the forward and backward modes were negligible when using the P2P algorithm (mean difference of 0.03mm). However, the ICP had a mean difference of 4.26mm. Each scan was also transformed by the forward and backward parameters of the two algorithms and the misclosure computed. The mean misclosure for the P2P algorithm was 0.80mm while that for the ICP algorithm was 5.39mm. The conclusion from this study is that the symmetric correspondence of the P2P algorithm provides more consistent registration results between a given pair of scans. The basis for this improvement is that symmetric correspondence better deals with the disparity between scans in terms of point density and point precision. BACKGROUNDThe registration of terrestrial laser scanning (TLS) data is an essential task in 3D modeling. The data of each scan are inherently referenced to a local coordinate system that is defined by the scanner's setup. Registration is thus needed to obtain a homogeneous dataset from the multiple disparate scans, prior to any 3D modeling and/or analysis.The development of automatic registration approaches is of interest to many research communities. Among the many automatic approaches that have been proposed, the Iterative Closest Point (ICP) method of Besl and McKay (1992) is one of the most popular methods used. The method is particularly prevalent for the fine registration of pairs of TLS data. Besl and McKay (1992) obtain the least squares parameters that are...