COMPARISON OF LOW COST PHOTOGRAMMETRIC SURVEY WITH TLS AND LEICA PEGASUS BACKPACK 3D MODELS

This paper considers Leica backpack and photogrammetric surveys of a mediaeval bastion in Padua, Italy. Furhtermore, terrestrial laser scanning (TLS) survey is considered in order to provide a state of the art reconstruction of the bastion. Despite control points are typically used to avoid deformations in photogrammetric surveys and ensure correct scaling of the reconstruction, in this paper a different approach is considered: this work is part of a project aiming at the development of a system exploiting ultra-wide band (UWB) devices to provide correct scaling of the reconstruction. In particular, low cost Pozyx UWB devices are used to estimate camera positions during image acquisitions. Then, in order to obtain a metric reconstruction, scale factor in the photogrammetric survey is estimated by comparing camera positions obtained from UWB measurements with those obtained from photogrammetric reconstruction. Compared with the TLS survey, the considered photogrammetric model of the bastion results in a RMSE of 21.9cm, average error 13.4cm, and standard deviation 13.5cm. Excluding the final part of the bastion left wing, where the presence of several poles make reconstruction more difficult, (RMSE) fitting error is 17.3cm, average error 11.5cm, and standard deviation 9.5cm. Instead, comparison of Leica backpack and TLS surveys leads to an average error of 4.7cm and standard deviation 0.6cm (4.2 cm and 0.3 cm, respectively, by excluding the final part of the left wing)

Forest structure from terrestrial laser scanning – in support of remote sensing calibration/validation and operational inventory

Forests are an important part of the natural ecosystem, providing resources such as timber and fuel, performing services such as energy exchange and carbon storage, and presenting risks, such as fire damage and invasive species impacts. Improved characterization of forest structural attributes is desirable, as it could improve our understanding and management of these natural resources. However, the traditional, systematic collection of forest information – dubbed “forest inventory” – is time-consuming, expensive, and coarse when compared to novel 3-D measurement technologies. Remote sensing estimates, on the other hand, provide synoptic coverage, but often fail to capture the fine- scale structural variation of the forest environment. Terrestrial laser scanning (TLS) has demonstrated a potential to address these limitations, but its operational use has remained limited due to unsatisfactory performance characteristics vs. budgetary constraints of many end-users. To address this gap, my dissertation advanced affordable mobile laser scanning capabilities for operational forest structure assessment. We developed geometric reconstruction of forest structure from rapid-scan, low-resolution point cloud data, providing for automatic extraction of standard forest inventory metrics. To augment these results over larger areas, we designed a view-invariant feature descriptor to enable marker-free registration of TLS data pairs, without knowledge of the initial sensor pose. Finally, a graph-theory framework was integrated to perform multi-view registration between a network of disconnected scans, which provided improved assessment of forest inventory variables. This work addresses a major limitation related to the inability of TLS to assess forest structure at an operational scale, and may facilitate improved understanding of the phenomenology of airborne sensing systems, by providing fine-scale reference data with which to interpret the active or passive electromagnetic radiation interactions with forest structure. Outputs are being utilized to provide antecedent science data for NASA’s HyspIRI mission and to support the National Ecological Observatory Network’s (NEON) long-term environmental monitoring initiatives

Scan registration using planar features

Point cloud acquisition by using laser scanners provides an efficient way for 3D as-built modelling of indoor/outdoor urban environments. In the case of large structures, multiple scans may be required to cover the entire scene and registration is needed to merge them together. In general, the identification of corresponding geometric features among a series of scans can be used to compute the 3D rigid-body transformation useful for the registration of each scan into the reference system of the final point cloud. Different automatic or semi-automatic methods have been developed to this purpose. Several solutions based on artificial targets are available, which however may not be suitable in any situations. Methods based on surface matching (like ICP and LS3D) can be applied if the scans to align have a proper geometry and surface texture. In the case of urban and architectural scenes that present the prevalence of a few basic geometric shapes ("Legoland" scenes) the availability of many planar features is exploited here for registration. The presented technique does not require artificial targets to be added to the scanned scene. In addition, unlike other surface-based techniques (like ICP) the planar feature-based registration technique is not limited to work in a pairwise manner but it can handle the simultaneous alignment of multiple scans. Finally, some applications are presented and discussed to show how this technique can achieve accuracy comparable to a consolidated registration method

Classification and information structure of the Terrestrial Laser Scanner: methodology for analyzing the registered data of Vila Vella, historic center of Tossa de Mar

This paper presents a methodology for an architectural survey, based on the Terrestrial Laser Scanning technology TLS, not as a simple measurement and representation work, but with the purpose understanding the projects being studied, starting from the analysis, as a process of distinction and separation of the parts of a whole, in order to know their principles or elements. As a case study we start from the Vila Vella recording, conducted by the City’s Virtual Modeling Laboratory in 2008, being taken up from the start, in relation to the registration, georeferencing, filtering and handling. Aimed at a later stage of decomposition and composition of data, in terms of floor plan and facades, using semiautomatic classification techniques, for the detection of vegetation as well as the relationship of the planes of the surfaces, leading to reorganize the information from 3D data to 2D and 2.5D, considering information management, as well as the characteristics of the case study presented, in the development of methods for the construction and exploitation of new databases, to be exploited by the Geographic Information Systems and Remote Sensing.Peer Reviewe

Co-registration of single tree maps and data captured by a moving sensor using stem diameter weighted linking

A new method for the co-registration of single tree data in forest stands and forest plots applicable to static as well as dynamic data capture is presented. This method consists of a stem diameter weighted linking algorithm that improves the linking accuracy when operating on diverse diameter stands with stem position errors in the single tree detectors. A co-registration quality metric threshold, QT, is also introduced which makes it possible to discriminate between correct and incorrect stem map co-registrations with high probability (>99%). These two features are combined to a simultaneous location and mapping-based co-registration method that operates with high linking accuracy and that can handle sensors with drifting errors and signal bias. A test with simulated data shows that the method has an 89.35% detection rate. The statistics of different settings in a simulation study are presented, where the effect of stem density and position errors were investigated. A test case with real sensor data from a forest stand shows that the average nearest neighbor distances decreased from 1.90 m to 0.51 m, which indicates the feasibility of this method

Classification and information structure of the Terrestrial Laser Scanner: methodology for analyzing the registered data of Vila Vella, historic center of Tossa de Mar

This paper presents a methodology for an architectural survey, based on the Terrestrial Laser Scanning technology TLS, not as a simple measurement and representation work, but with the purpose understanding the projects being studied, starting from the analysis, as a process of distinction and separation of the parts of a whole, in order to know their principles or elements. As a case study we start from the Vila Vella recording, conducted by the City’s Virtual Modeling Laboratory in 2008, being taken up from the start, in relation to the registration, georeferencing, filtering and handling. Aimed at a later stage of decomposition and composition of data, in terms of floor plan and facades, using semiautomatic classification techniques, for the detection of vegetation as well as the relationship of the planes of the surfaces, leading to reorganize the information from 3D data to 2D and 2.5D, considering information management, as well as the characteristics of the case study presented, in the development of methods for the construction and exploitation of new databases, to be exploited by the Geographic Information Systems and Remote Sensing.Peer Reviewe