Enhancing building footprints with squaring operations

Whatever the data source, or the capture process, the creation of a building footprint in a geographical dataset is error prone. Building footprints are designed with square angles, but once in a geographical dataset, the angles may not be exactly square. The almost-square angles blur the legibility of the footprints when displayed on maps, but might also be propagated in further applications based on the footprints, e.g., 3D city model construction. This paper proposes two new methods to square such buildings: a simple one, and a more complex one based on nonlinear least squares. The latter squares right and flat angles by iteratively moving vertices, while preserving the initial shape and position of the buildings. The methods are tested on real datasets and assessed against existing methods, proving the usefulness of the contribution. Direct applications of the squaring transformation, such as OpenStreetMap enhancement, or map generalization are presented

Statistical approach of factors controlling drainage network patterns in arid areas. Application to the Eastern Anti Atlas (Morocco)

International audience12 13 Abstract: 14 Several studies have revealed that the complexity in the distribution of drainage network patterns is not 15 random and controlled by major parameters, variable in space but also throughout geological time. Drainage 16 networks in the Eastern Anti-Atlas of Morocco consist of complex spatial arrangements with various types of 17 patterns, such as trellis, angular, dendritic and parallel. The objective was to distinguish, quantify and rank 18 the relationship that may exist between the different drainage networks patterns, geology and 19 geomorphology. A total of 230 basins were extracted from the ASTER-GDEM Elevation Data (USGS), which 20 were assigned 16 parameters reflecting their topography, morphometry, slope and geology. The statistical 21 treatment of the dataset (16 variables x 230 observations) was carried out through principal component 22 analysis (PCA), linear discriminant analysis (LDA) and agglomerative hierarchical clustering (AHC), in order to 23 investigate the complexity of drainage network patterns and their distribution. The PCA showed that the 24 topographical, slope and geological parameters, i.e. primarily the parameter associated with structural 25 control, best explains the variation in the type of the drainage pattern. The LDA made it possible to distinguish 26 between the four types of drainage patterns with a success rate of 90%, using 3 discriminant functions that 27 were better correlated with geological and slope parameters. LDA and AHC statistical treatments show 28 confusion between the parallel, trellis and angular patterns, on the one hand, due to similar factors 29 responsible for their formation, and on the other because of transitions phenomenon from one drainage 30 pattern to another over time or space. Such possible drainage network shifting may be explained by the 31 geological events that have occurred in the Eastern Anti Atlas from Lower Mesozoic to the Quaternary. 32 3

Multi-Scale Modelling of Cold Regions Hydrology

Numerical computer simulations are increasingly important tools required to address both research and operational water resource issues related to the hydrological cycle. Cold region hydrological models have requirements to calculate phase change in water via consideration of the energy balance which has high spatial variability. This motivates the inclusion of explicit spatial heterogeneity and field-testable process representations in such models. However, standard techniques for spatial representation such as raster discretization can lead to prohibitively large computational costs and increased uncertainty due to increased degrees of freedom. As well, semi-distributed approaches may not sufficiently represent all the spatial variability. Further, there is uncertainty regarding which process conceptualizations are used and the degree of required complexity, motivating modelling approaches that allow testing multiple working hypotheses. This thesis considers two themes. In the first, the development of improved modelling techniques to efficiently include spatial heterogeneity, investigate warranted model complexity, and appropriate process representation in cold region models is addressed. In the second, the issues of non-linear process cascades, emergence, and compensatory behaviours in cold regions hydrological process representations is addressed. To address these themes, a new modelling framework, the Canadian Hydrological Model (CHM), is presented. Key design goals for CHM include the ability to: capture spatial heterogeneity in an efficient manner, include multiple process representations, be able to change, remove, and decouple hydrological process algorithms, work both at point and spatially distributed scales, reduce computational overhead to facilitate uncertainty analysis, scale over multiple spatial extents, and utilize a variety of boundary and initial conditions. To enable multi-scale modelling in CHM, a novel multi-objective unstructured mesh generation software *mesher* is presented. Mesher represents the landscape using a multi-scale, variable resolution surface mesh. It was found that this explicitly captured the spatial heterogeneity important for emergent behaviours and cold regions processes, and reduced the total number of computational elements by 50\% to 90\% from that of a uniform mesh. Four energy balance snowpack models of varying complexity and degree of coupling of the energy and mass budget were used to simulate SWE in a forest clearing in the Canadian Rocky Mountains. It was found that 1) a compensatory response was present in the fully coupled models’ energy and mass balance that reduced their sensitivity to errors in meteorology and albedo and 2) the weakly coupled models produced less accurate simulations and were more sensitive to errors in forcing meteorology and albedo. The results suggest that the inclusion of a fully coupled mass and energy budget improves prediction of snow accumulation and ablation, but there was little advantage by introducing a multi-layered snowpack scheme. This helps define warranted complexity model decisions for this region. Lastly, a 3-D advection-diffusion blowing snow transport and sublimation model using a finite volume method discretization via a variable resolution unstructured mesh was developed. This found that the blowing snow calculation was able to represent the spatial redistribution of SWE over a sub-arctic mountain basin when compared to detailed snow surveys and the use of the unstructured mesh provided a 62\% reduction in computational elements. Without the inclusion of blowing snow, unrealistic homogeneous snow covers were simulated which would lead to incorrect melt rates and runoff contributions. This thesis shows that there is a need to: use fully coupled energy and mass balance models in mountains terrain, capture snow-drift resolving scales in next-generation hydrological models, employ variable resolution unstructured meshes as a way to reduce computational time, and consider cascading process interactions

Building Footprint Extraction from LiDAR Data and Imagery Information

This study presents an automatic method for regularisation of building outlines. Initially, building segments are extracted using a new fusion method. Data- and model-driven approaches are then combined to generate approximate building polygons. The core part of the method includes a novel data-driven algorithm based on likelihood equation derived from the geometrical properties of a building. Finally, the Gauss-Helmert and Gauss-Markov models adjustment are implemented and modified for regularisation of building outlines considering orthogonality constraints

The characteristics of plutonic rocks in various climatic zones as shown on multiband satellite imagery

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In-situ backplane inspection of fiber optic ferrules

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (p. 193-200).The next generation of supercomputers, routers, and switches are envisioned to have hundreds and thousands of optical interconnects among components. An optical interconnect attains a bandwidth-distance product as high as 90 GHz.km, about 200 times higher than can be attained by a copper interconnect. But defects (such as dust or scratches) as small as 1 micron on the connector endfaces can seriously degrade performance. Therefore, for every mate and de-mate, optical connectors must be inspected to ensure high performance data transmission capabilities. The tedious and time consuming task of manually inspecting each connector is one of the barriers to adoption of optics in the backplanes of large card-based machines. This thesis provides a framework and method for in-situ automatic inspection of backplane optical connectors. We develop an inspection system that fits into the envelope of a single daughter card, moves a custom microscope objective in three degrees of freedom to image the connector endfaces, and detects and classifies defects with major diameter of one micron or larger.The inspection machine mounts to the backplane in the same manner as a daughter card, and positions the microscope with better than 0.2 micron resolution and 15 micron repeatability in three degrees of freedom. Despite tight packaging constraints, the ultra-long working distance custom microscope objective attains 1 micron Rayleigh resolution via deconvolution. Several images taken at different exposures and focus settings are fused to extend the imaging sensor's limited dynamic range and depth of field. A set of machine-vision algorithms are developed to process the resulting image and detect and classify the fiber core, cladding and their defects.by Andrew K. Wilson.Ph.D

Mapping and Real-Time Navigation With Application to Small UAS Urgent Landing

Small Unmanned Aircraft Systems (sUAS) operating in low-altitude airspace require flight near buildings and over people. Robust urgent landing capabilities including landing site selection are needed. However, conventional fixed-wing emergency landing sites such as open fields and empty roadways are rare in cities. This motivates our work to uniquely consider unoccupied flat rooftops as possible nearby landing sites. We propose novel methods to identify flat rooftop buildings, isolate their flat surfaces, and find touchdown points that maximize distance to obstacles. We model flat rooftop surfaces as polygons that capture their boundaries and possible obstructions on them. This thesis offers five specific contributions to support urgent rooftop landing. First, the Polylidar algorithm is developed which enables efficient non-convex polygon extraction with interior holes from 2D point sets. A key insight of this work is a novel boundary following method that contrasts computationally expensive geometric unions of triangles. Results from real-world and synthetic benchmarks show comparable accuracy and more than four times speedup compared to other state-of-the-art methods. Second, we extend polygon extraction from 2D to 3D data where polygons represent flat surfaces and interior holes representing obstacles. Our Polylidar3D algorithm transforms point clouds into a triangular mesh where dominant plane normals are identified and used to parallelize and regularize planar segmentation and polygon extraction. The result is a versatile and extremely fast algorithm for non-convex polygon extraction of 3D data. Third, we propose a framework for classifying roof shape (e.g., flat) within a city. We process satellite images, airborne LiDAR point clouds, and building outlines to generate both a satellite and depth image of each building. Convolutional neural networks are trained for each modality to extract high level features and sent to a random forest classifier for roof shape prediction. This research contributes the largest multi-city annotated dataset with over 4,500 rooftops used to train and test models. Our results show flat-like rooftops are identified with > 90% precision and recall. Fourth, we integrate Polylidar3D and our roof shape prediction model to extract flat rooftop surfaces from archived data sources. We uniquely identify optimal touchdown points for all landing sites. We model risk as an innovative combination of landing site and path risk metrics and conduct a multi-objective Pareto front analysis for sUAS urgent landing in cities. Our proposed emergency planning framework guarantees a risk-optimal landing site and flight plan is selected. Fifth, we verify a chosen rooftop landing site on real-time vertical approach with on-board LiDAR and camera sensors. Our method contributes an innovative fusion of semantic segmentation using neural networks with computational geometry that is robust to individual sensor and method failure. We construct a high-fidelity simulated city in the Unreal game engine with a statistically-accurate representation of rooftop obstacles. We show our method leads to greater than 4% improvement in accuracy for landing site identification compared to using LiDAR only. This work has broad impact for the safety of sUAS in cities as well as Urban Air Mobility (UAM). Our methods identify thousands of additional rooftop landing sites in cities which can provide safe landing zones in the event of emergencies. However, the maps we create are limited by the availability, accuracy, and resolution of archived data. Methods for quantifying data uncertainty or performing real-time map updates from a fleet of sUAS are left for future work.PHDRoboticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/170026/1/jdcasta_1.pd

The Multispectral Imaging Science Working Group. Volume 3: Appendices

The status and technology requirements for using multispectral sensor imagery in geographic, hydrologic, and geologic applications are examined. Critical issues in image and information science are identified

On the popularization of digital close-range photogrammetry: a handbook for new users.

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική