LiDAR Research Papers - Academia.edu (original) (raw)

Despite the relatively high cost of airborne lidar-derived digital elevation models (DEMs), such products are usually presented without a satisfactory associated estimate of accuracy. For the most part, DEM accuracy estimates are typically provided by comparing lidar heights against a finite sample of check point coordinates from an independent source of higher accuracy, supposing a normal distribution of the derived height differences or errors. This paper proposes a new methodology to assess the vertical accuracy of lidar DEMs using confidence intervals constructed from a finite sample of errors computed at check points. A non-parametric approach has been tested where no particular error distribution is assumed, making the proposed methodology especially applicable to non-normal error distributions of the type usually found in DEMs derived from lidar. The performance of the proposed model was experimentally validated using Monte Carlo simulation on 18 vertical error datasets. Fifteen of these data-sets were computed from original lidar data provided by the International Society for Photogrammetry and Remote Sensing Working Group III/3, using their respective filtered reference data as ground truth. The three remaining data-sets were provided by the Natural Environment Research Council's Airborne Research and Survey Facility lidar system, together with check points acquired using high precision kinematic GPS. The results proved promising, the proposed models reproducing the statistical behaviour of vertical errors of lidar using a favourable number of check points, even in the cases of data-sets with non-normally distributed residuals. This research can therefore be considered as a potentially important step towards improving the quality control of lidar-derived DEMs.

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- LiDAR, Confidence intervals, DEM, Geomatic Engineering

Archaeological applications using airborne laser scanning (ALS) are increasing in number. Since the production of ALS-derived digital terrain models (DTM) involves a considerable amount of money, most applications use general purpose ALS data, which are usually cheaper and sometimes even provided for free for scientific applications. The main problem that comes with this kind of data is the frequent lack of meta-information. The archaeologist often does not get the information about original point density, time of flight, instrument used, type of flying platform, filter and DTM generation procedure etc. Therefore, ALS becomes a kind of “black box”, where the derived DTM is used without further knowledge about underlying technology, algorithms, and metadata. Consequently, there is a certain risk that the data used will not be suitable for the archaeological application.
Based on the experience of a two-year project “LiDAR-Supported Archaeological Prospection in Woodland”, the paper will give a review on archaeological ALS, explain its the basic process, demonstrate its potential for landscape archaeology especially in densely forested areas, and draw the attention to some critical parameters of ALS, which should be known to the user. Finally, further issues, which need to be solved in near future, are discussed.

- by Michael Doneus
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- LiDAR, Airborne Laser Scanning, Archaeological Prospection, LiDAR for Forestry

Three dimensional object extraction and recognition (OER) from LIDAR data has been an area of major interest in photogrammetry for quite a long time. However, most of the existing methods for automatic object extraction and recognition from LIDAR data are just based on the range information and employ parametric methods and object’s vagueness behaviour is basically neglected. Thus, these methods do not take into account the extraction and recognition complexities and may fail to reach a satisfied reliability level in complex situations. In this paper a novel approach based on the following strategies is formulated and implemented: (a) for a more comprehensive definition of the objects, information fusion concept is utilized, i.e., object’s descriptive components such as 3D structural and textural (ST) information are automatically extracted from first/last rang and intensity information of LIDAR data and simultaneously fed into the evaluation process, (b) for a more realistic expres...

- by Farhad Samadzadegan
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- Fuzzy Logic, Recognition, LiDAR, Region growing

This thesis develops a 3-D modelling framework that determines exact location and pattern of buildings, detailed information of their roofs, and generate computer-based 3-D building models. The proposed framework has utilisation in a range of applications, such as city planning, disaster management, urban modelling, and virtual reality. In addition, this thesis provides an automated system for large-scale assessment of the solar potential for industrial and govt energy businesses.

- by Ali Naqi Gilani
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- Computer Science, Remote Sensing, LiDAR, Monash University
- by Daniel Muntz
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- Geology, LiDAR, Inca Archaeology, Arqueología

The aim of this project was to assess the feasibility of a photo imaging approach in the assessment of vegetation condition attributes in comparison with the Queensland Department of Environment and Resource Management (QDERM) Vegetation Condition Assessment approach. The project applied both the QDERM BioCondition monitoring method and an alternative photo imaging analysis approach to the assessment of vegetation condition attributes on different regional ecosystems. The study focused on the comparability of results and the cost-effectiveness of the photo imaging approach in comparison to the standard BioCondition assessment method. Six regional ecosystems (RE) sites, of varying structural complexity, were selected for this study. They contained a diverse range of different vegetation attributes. Each site was assessed using both approaches. A low-cost Canon PowerShot SX10 IS camera was used to collect the photographs. It is equipped with a 20x Optical Zoom lens with a focal length...

- by Lucy Richardson
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- Geography, LiDAR, Natural Resource Management, Vegetation Condition

An airborne differential absorption lidar (DIAL) system has been developed at the NASA Langley Research Center for remote measurements of atmospheric water vapor (H 2 0) and aerosols. A solid-state alexandrite laser with a 1-pm linewidth and > 99.85% spectral purity was used as the on-line transmitter. Solid-state avalanche photodiode detector technology has replaced photomultiplier tubes in the receiver system, providing an average increase by a factor of 1.5-2.5 in the signal-to-noise ratio of the H 2 O measurement. By incorporating advanced diagnostic and data-acquisition instrumentation into other subsystems, we achieved additional improvements in system operational reliability and measurement accuracy. Laboratory spectroscopic measurements of H 2 O absorption-line parameters were performed to reduce the uncertainties in our knowledge of the absorption cross sections. Line-center H 2 O absorption cross sections were determined, with errors of 3-6%, for more than 120 lines in the 720-nm region. Flight tests of the system were conducted during 1989-1991 on the NASA Wallops Flight Facility Electra aircraft, and extensive intercomparison measurements were performed with dew-point hygrometers and H 2 0 radiosondes. The H 2 0 distributions measured with the DIAL system differed by • 10% from the profiles determined with the in situ probes in a variety of atmospheric conditions.

- by Patrick Ponsardin
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- LiDAR

The Lidar (LIght Detection And Ranging) sensor produced by Siemens uses five infrared beams to detect targets up to a distance of approximately 250m. The paper describes the tests witch has been develop using our new software in order to visualize the detected targets. We used our program in the detection of different types of targets, placed at different distances and in different combinations. An important goal was to see how various meteorological conditions affect or do not affect the target detection. Other types of experiments were focused on low visibility conditions, different lighting conditions (natural, artificial, day, night).

- by Georgiana Simion
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- Computer Science, Sensor, LiDAR, Programming

We use two recent Japanese earthquakes to demonstrate the rich potential, as well as some of the challenges, of differencing repeat airborne Light Detection and Ranging (lidar) topographic data to measure coseismic fault zone deformation. We focus on densely-vegetated sections of the 14 June 2008 Iwate–Miyagi (Mw 6.9) and 11 April 2011 Fukushima–Hamadori (Mw 7.1) earthquake ruptures, each covered by 2 m-resolution pre-event and 1 m-resolution post-event bare Earth digital terrain models (DTMs) obtained from commercial lidar providers. Three-dimensional displacements and rotations were extracted from these datasets using an adaptation of the Iterative Closest Point (ICP) algorithm. These displacements remain coherent close to surface fault breaks, as well as within dense forest, despite intervals of ∼2 years (Iwate–Miyagi) and ∼4 years (Fukushima–Hamadori) encompassed by the lidar scenes. Differential lidar analysis is thus complementary to Interferometric Synthetic Aperture Radar (InSAR) and sub-pixel correlation techniques which often break down under conditions of long time intervals, dense vegetation or steep displacement gradients. Although the ICP displacements are much noisier than overlapping InSAR line-of-sight displacements, they still provide powerful constraints on near-surface fault slip. In the Fukushima–Hamadori case, near-fault displacements and rotations are consistent with decreased primary fault slip at very shallow depths of a few tens of meters, helping to account for the large, along-strike heterogeneity in surface offsets observed in the field. This displacement field also captures long-wavelength deformation resulting from the 11 March 2011 Tohoku great earthquake.

- by E. Nissen and +1
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- LiDAR, Seismology, Remote Sensing (Earth Sciences), Earthquake

The article is aimed at presenting a semi-empirical model coded and computed in the programming language Python, which utilizes data gathered with a standard biaxial elastic lidar platform in order to calculate the altitude profiles of the structure coefficients of the atmospheric refraction index C N 2 ( z ) and other associated turbulence parameters. Additionally, the model can be used to calculate the PBL (Planetary Boundary Layer) height, and other parameters typically employed in the field of astronomy. Solving the Fernard–Klett inversion by correlating sun-photometer data obtained through our AERONET site with lidar data, it can yield the atmospheric extinction and backscatter profiles α ( z ) and β ( z ) , and thus obtain the atmospheric optical depth. Finally, several theoretical notions of interest that utilize the solved parameters are presented, such as approximated relations between C N 2 ( z ) and the atmospheric temperature profile T ( z ) , and between the scintillati...

- by Alin Rosu
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- Environmental Science, Physics, Remote Sensing, LiDAR

Recent advances in 3D sensing and volumetric data compression are encouraging research efforts to meet the demands for vision guidance of autonomous vehicle. Nowadays, autonomous vehicle technology is successful in a high percentage of common road scenarios. However, new research efforts are required to meet the demands for higher performance. The diversity of traffic scenarios in the urban environment presents great challenges, foremost for videobased environment recognition. Autonomous driving technology and other automated assistance systems process huge amounts of data, thus efficient data compression, storage and retrieval is necessary. Key technologies for autonomous vehicles, i.e. 3D video/Point Cloud compression solutions for camera and LiDAR sensor systems are presented in this paper.

The classification of LiDAR point cloud is a key but difficult step for 3D reconstruction of architecture. The main classification methods are clustering-based and objectoriented. The support vector machine is an effective tactic which has been applied to classification, regression or other tasks. In this paper, we extract the vector angle, vector residual and position variance of point data as the key features of dimension value and put these key features into multi-class support vector machine, through calculating the probability of every point that belongs to each type, voting the maximum possible result. According to the voting result, we obtain the final classification result. The experiment results show that the classification method is promising.

- by Qingming Zhan
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- Architecture, LiDAR, Support Vector Machines, Probability

1] Persistent meteor trains, studied for more than a century, remain somewhat mysterious [Newton, 1869;. The Leonids meteor showers of recent years afforded opportunities to apply new research technologies, including lidars and sophisticated cameras. Here we explore a particularly curious but common feature: double trains. Since the traditional hollow cylinder explanation has been shown to be untenable, we suggest a new explanation, arguing that one train is due to gaseous vapor train emissions behind the meteor while the other is due to heterogeneous chemistry associated with recoagulated dust. In this model the separation is caused by gravitational sedimentation of dust particles, an idea supported by rocket-based observations of recoagulated dust behind a meteor, by rocket-based observations of enhanced sodium emissions in a dust layer, by rocket observations of a dusty trail, and by recent theoretical estimates of chemical reactions on dust.

- by C. Gardner
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- Technology, LiDAR, Multidisciplinary, Models

Page 1. Advanced pixel design for infrared 3D LADAR imaging Fabrice Guellec, Michaël Tchagaspanian Eric de Borniol, Pierre Castelein, André Perez, Johan Rothman CEA Leti – MINATEC, 17 rue des Martyrs, 38054 Grenoble Cedex 9, France... more

- by André Perez
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- Engineering, LiDAR, Stereoscopy, Optical Imaging
- by Gabriel Lombardi
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- LiDAR, Atmospheric Turbulence
- by Nannina Spanò
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- Engineering, Archaeological documentation, LiDAR, Feature Extraction

Knowing physical structure of the unknown environment is a requirement in some natural disaster situations such as earthquake, fire accidents or flood. Many existing algorithms in literature have been developed for the purpose of extracting map of unknown environment. These algorithms called as SLAM (Simultaneous Localization and Mapping). But still there are problems in SLAM to be solved. One of these problems referred in literature as chicken-egg problem. Another struggling problem is requirement of more parameters to execute and generate accurate map and pose estimation. That makes systems' structures more complicated and hierarchical. In this study, parameters of Gmapping SLAM algorithm are reduced to avoid complicated structures and execute in a low cost handheld system. In the second step, a rough map is generated by designed handheld system. This rough map called as pre-map. Purpose of the generated pre-map is to use it in other studies, to assist solving localization problem.  Index Terms-pre-mapping, LIDAR, GMAPPING, scan matching, grid base mapping, rao-blackwellized Jamal Esenkanova received the B.Sc. and M.Sc.

- by Sirma Yavuz
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- Robotics, Embedded Systems, LiDAR, Electrical energy

Light Detection and Ranging (LiDAR) is a technology that has been used for years with the variety of applications including the production of digital terrain models (DTMs), and high-accuracy mapping. LiDAR offers a very detailed collection of 3-D point clouds of the earth surface which can be used in generating orthophotos. Traditional orthophoto production based on the DTM has to

- by DR ISMAIL MA'AROF
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- Computer Science, Signal Processing, Digital Photography, Production

Differential absorption lidar (DIAL) at the National Institute for Environmental Studies (NIES) in Tsukuba (36 N, 140 E), Japan has been making routine observations for almost 20 years. Since 1988, more than 600 vertical profiles of stratospheric ozone and temperature have been obtained. We compared the lidar data with satellite data from the Stratospheric Aerosol and Gas Experiment (SAGE II) and assimilation data from the National Center for Environmental Prediction (NCEP). The lidar and SAGE II ozone profiles agreed within 5% in altitude range from 18 km to 40 km and within 10% up to 45 km. The lidar and NCEP temperatures agreed within 7 K in the 35-to 50-km range. Ozone levels were highest in spring at altitudes below 20 km. Above 30 km, the ozone maximum occurred during summer. The annual cycle of temperature is observed with a spring maximum for all altitudes in the 35-to 50-km range. Ozone variations caused by the quasi-biennial oscillation (QBO) and the 11-year solar cycle are discussed. The ozone trends after subtraction of the QBO and solar effects for the altitude range from 30 to 40 km are-6.0 AE 0.5%/decade for the period from 1988 to 1997 and statistically insignificant after 1998.

- by Nobuo Sugimoto
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- Remote Sensing, Prediction, LiDAR, Stratosphere

Celem tekstu jest podkreślenie biograficznego charakteru kultury materialnej. To znaczy, rzeczy i krajobrazy również mają swoje biografie, historie życia, które łączą się z historiami konkretnych jednostek. Za studium przypadku posłuży... more

- by Dawid Kobiałka
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- Archaeology, Anthropology, Historical Archaeology, Material Culture Studies

The coherent launch-site atmospheric wind sounder (CLAWS) is a lidar atmospheric wind sensor designed to measure the winds above space launch facilities to an altitude of 20 km. In our development studies, lidar sensor requirements are defined, a system to meet those requirements is defined and built, and the concept is evaluated, with recommendations for the most feasible and cost-effective lidar system for use as an input to a guidance and control system for missile or spacecraft launches. The ability of CLAWS to meet NASA goals for increased safety and launch/mission flexibility is evaluated in a field test program at Kennedy Space Center (KSC) in which we investigate maximum detection range, refractive turbulence, and aerosol backscattering efficiency. The Nd:YAG coherent lidar operating at 1.06 pum with 1-J energy per pulse is able to make real-time measurements of the three-dimensional wind field at KSC to an altitude of 26 km, in good agreement with our performance simulations. It also shows the height and thickness of the volcanic layer caused by the volcanic eruption of Mount Pinatubo in the Philippines.

- by Charley Hale
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- Mechanical Engineering, Environmental Science, LiDAR, Medicine

In order to measure the D structure of a number of objects a comparably new technique in computer vision exists, namely time of flight (TOF) cameras. The overall principle is rather easy and has been applied using sound or light for a long time in all kind of sonar and lidar systems. However in this approach one uses modulated light waves and receives the signals by a parallel pixel array structure. Out of the travelling time at each pixel one can estimate the depth structure of a distant object. The technique requires measuring the intensity differences and ratios of several pictures with extremely high accuracy; therefore one faces in practice rather high noise levels. Object features as reflectance and roughness influence the measurement results. This leads to partly high noise levels with variances dependent on the illumination and material parameters. It can be shown that a reciprocal relation between the variance of the phase and the squared amplitude of the signals exists. On...

- by Bernhard Moser
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- Engineering, Geography, Computer Science, Computer Vision

Management of highly dynamic coastal landscapes requires repeated mapping and analysis of observed changes. Modern mapping techniques such as lidar increased the frequency and level of detail in coastal surveys and new methods were developed to extract valuable information from these data using Geographic Information Systems. The brief presents techniques for analyzing and visualizing coastal topographic and shoreline change and sand dune dynamics using open source GRASS GIS.

- by Helena Mitasova and +1
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- Coastal Geomorphology, LiDAR, Beach erosion

Flood related scientific and community-based data are rarely systematically collected and analysed in the Philippines. Over the last decades the Pagsangaan River Basin, Leyte, has experienced several flood events. However, documentation describing flood characteristics such as extent, duration or height of these floods are close to non-existing. To address this issue, computerized flood modelling was used to reproduce past events where there was data available for at least partial calibration and validation. The model was also used to provide scenario-based predictions based on A1B climate change assumptions for the area. The most important input for flood modelling is a Digital Elevation Model (DEM) of the river basin. No accurate topographic maps or Light Detection And Ranging (LIDAR)-generated data are available for the Pagsangaan River. Therefore, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM), Version 1, was chosen...

- by Olaf Neussner
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- Geography, LiDAR, Digital Elevation Models, Remote sensing and GIS

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and method-ological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for a) assessing the pros and cons of the different approaches and b) assessing the potential detection rate of remote sensing. Interpretation of images and a Li-DAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both ...

- by Ole Risbøl and +3
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- Archaeology, Remote Sensing, LiDAR, Cultural Heritage Management

Elaboración de mapas base para el deporte de Orientación, a partir de datos LIDAR.

- by Arturo Fernández
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- Cartography, LiDAR, Airborne Laser Scanning, Sports

Airborne lidar systems are equipped with a scanning mechanism that produces a swath of 3D coordinated points to form a cloud in each flight strip. The scanning is perpendicular to the direction of flight. The density of the point cloud is one of the major quality measures for the data collected with such systems. Point density, shade (occlusion of the laser beam) and penetration rate are major factors to be considered in the flight design. For practical operations, flight missions may be designed with overlaps ranging from 5 to 50%. Aside from the percentage overlap, the field of view is another important parameter for flight design. An evaluation scheme to assess the percentage overlap between flight strips and the selection of the field of view is proposed in this study. The influences of overlap and field of view are also demonstrated with real data gathered by an airborne lidar system.

- by Peter Shih
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- Geography, LiDAR, Geomatic Engineering, Digital Elevation Model
- by Ugo Chiocchini and +1
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- Geology, Geomorphology, Morphological evolution, LiDAR

The ultimate goal of pattern recognition systems in remote sensing is to achieve the best possible classification performance for recognition of different objects such as buildings, roads and trees. From a scientific perspective, the extraction of roads in complex environments is one of the challenging issues in photogrammetry and computer vision, since many tasks related to automatic scene interpretation are involved. Roads have homogeneous reflectivity in LIDAR intensity and the same height as bare surface in elevation. Proposed method in this paper is based on combining multiple classifiers (MCS) is one of the most important topics in pattern recognition to achieve higher accuracy. Majority Voting and Selective Naive Bays are two methods that used for fusion of classifiers.

- by Farhad Samadzadegan
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- Computer Vision, Remote Sensing, Photogrammetry, Data Mining

Lidar-based positioning in a 2D map is analyzed as a method to provide a robust, high accuracy, and infrastructurefree positioning system required by the automation development in underground mining. Expressions are derived that highlight separate information contributions to the obtained position accuracy. This is used to develop two new methods that efficiently select which subset of available lidar rays to use to reduce the computational complexity and allow for online processing with minimal loss of accuracy. The results are verified in simulations of a mid-articulated underground loader in a mine. The methods are shown to be able to reduce the number of rays needed without considerably affecting the performance, and to be competitive with currently used methods. Furthermore, simulations highlight the effects of errors in the map and other map properties, and how imperfect maps degrades the performance of different selection strategies.

- by Kristin Nielsen
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- Computer Science, Control Engineering, LiDAR, IEEE

In this paper, we explore some of the applications of computer vision to sports analytics. Sport analytics deals with understanding and discovering patterns from a corpus of sports data. Analysing such data provides important performance metrics for the players, for instance in soccer matches, that could be useful for estimating their fitness and strengths. Team level statistics can also be estimated from such analysis. This paper mainly focuses on some the challenges and opportunities presented by sport video analysis in computer vision. Specifically, we use our multi-camera setup as a framework to discuss some of the real-life challenges for machine learning algorithms.

- by Fabio Cuzzolin
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- Computer Science, Computer Vision, LiDAR, Object Tracking (Computer Vision)

A recent development in the use of lidar remote sensing techniques is ground-based laser scanning. Laser scanning of rock faces yields the spatial relation between all scanned rock surface points, at a very high resolution, basically a dense "point cloud" in three-dimensional space. The subject of this research is to obtain discontinuity information from the point cloud data set, using an approach that can be automated. The first step in this methodology is to interpolate the point cloud data using 3D Delaunay triangulation in order to create a 3D surface. As a 3D triangulated surface, the scanned rock face is represented by a large number of triangles. The orientation of each triangle can subsequently be computed using basic geometrical rules. Analysis of the kernel density stereo plots of the orientation of all triangles, reveal that specific discontinuity sets can be recognised. Obviously, if this approach can be further developed and fully automated, this would give the site engineer or geologist, in realtime, evidence on the internal structure of any discontinuous rock mass. Particularly in areas where access to rock outcrops is poor, application of this technique will be very promising.

- by Robert H R G K Hack
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- Rock Mechanics, Geotechnical Engineering, Laser, LiDAR

Individual tree detection methods are more and more present, and improve, in forestry and silviculture domains with the increasing availability of satellite metric imagery[2-7]. Automatic detection on these very high spatial resolution images aims to determine the tree positions and crown sizes. In this paper, we used a mathematical model based on marked point processes, which showed advantages w.r.t. several individual tree detection algorithms for plantations [2], to analyze an eucalyptus plantation in Brazil, with 2 optical images acquired by the WorldView-2 satellite. A tentative detection simultaneously with 2 images of different dates (multi-date) was tested for the first time, which estimates individual tree crown variation during these dates. While, for the most present detection methods, only the static state of tree crowns at the moment of one image's acquisition was estimated. The relevance of detection was discussed considering the detection performance in tree localizations and crown sizes. Then, tree crown growth was deduced from detection results and compared with the expected dynamics of corresponding populations.

- by Ihssen Hedhli and +4
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- Remote Sensing, LiDAR, Satellite remote sensing, Optical Imaging

In this work we present an in-situ method to compute the calibration of two sensors, a LIDAR (Light Detection and Ranging) and a spherical camera. Both sensors are used in urban environment reconstruction tasks. In this scenario the speed at which the various sensors acquire and merge the information is very important, however reconstruction accuracy, which depends on sensors calibration, is also of high relevance. Here, a new calibration pattern, visible to both sensors is proposed. By this mean, the correspondence between each laser point and its position in the camera image is obtained so that the texture and color of each LIDAR point can be known. Experimental results for the calibration and uncertainty analysis are presented for data collected by the platform integrated with a LIDAR and the spherical camera.

- by Angel Ivan Garcia Moreno
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- Remote Sensing, LiDAR, Image Analysis

LIDAR sensors are bound to become one the core sensors in achieving full autonomy for self driving cars. LIDARs are able to produce rich, dense and precise spatial data, which can tremendously help in localizing and tracking a moving vehicle. In this paper, we review the latest finding in 3D LIDAR localization for autonomous driving cars, and analyze the results obtained by each method, in an effort to guide the research community towards the path that seems to be the most promising.

- by Mahdi ElHousni
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- Computer Science, Artificial Intelligence, LiDAR, Point Cloud

Post-earthquake reconstruction of housing in heritage settlements confronts challenges such as inadequate damage assessment and replacement, displaced population and loss of heritage significance. Recording the built fabric and ways of life within heritage settlements are key for conserving their historic value, which is increasingly possible with the evolution of digital technologies. This paper presents an ongoing research project developing a novel methodology for heritage conservation and post-disaster re-construction using state-of-the-art 3D-laser-scanning (LiDAR) technologies to enable comprehensive damage assessment and design of solutions for repair, retrofitting, reuse and disaster risk mitigation, facilitating community empowerment, while virtually preserving the living heritage of vernacular settlements in Kutch, Gujarat. Through the development of a scalable method of re-construction, the aim is to break the unsustainable cycle of buildings' replacement, dereliction...

- by Rohit Jigyasu
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- Engineering, Architecture, Cultural Heritage, Heritage Conservation

A synthesis of Doppler lidar measurements with conventional meteorological data, including automatic weather stations and radiosondes, leads to the conclusion that the cold front in the Wipp Valley was an atmospheric density current characterized by an elevated head, a front-relative feeder flow and a typical propagation speed of 7 m s −1 . The foehn flow on top of the density current caused strong wind shear and triggered shear-flow instability that led to the formation of a turbulent wake behind the head. As the density current propagated towards the Brenner Pass, it slowed down. The shape of the frontal surface varied in time. Its inclination of about 10 • -20 • is steeper than previously reported for the Inn Valley but is consistent with other observations of atmospheric density currents. Citation: Gohm A, Mayr GJ, Darby LS, Banta RM. 2010. Evolution and structure of a cold front in an Alpine valley as revealed by a Doppler lidar. Q. J. R. Meteorol. Soc. 136: 962-977.

- by Georg Mayr
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- Cartography, Oceanography, LiDAR, Atmospheric sciences

... The Modagspace project: Lidar data and landscape archaeology in southern France (Languedoc). Nicolas Poirier ( Auteur correspondant. ) 1, 2, 3 , Rachel Opitz 1, 3 , Laure Nuninger ( Auteur correspondant. ) 1, 3, 4 , Krištof Oštir 2,... more

- by Nicolas Poirier
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- Geography, Archaeology, Remote Sensing, Spatial Analysis

The study is the most comprehensive solar inventory done of UT campus to date showing that “Roofspace” on UT campus has great potential to produce renewable energy through the integration of solar photovoltaic and thermal panels. Unlike other renewable forms of energy, solar technologies can be integrated into the built environment making them one of the few options for onsite renewable energy for the University. However, there are substantial social and economic barriers that will inhibit the University from developing the full potential of its solar energy resources. Economically, the price of solar energy is too high in comparison to current electrical generation on campus. Socially, the aesthetic and cultural value of the UT campus’s red clay-tiled roof space surpasses the value to be potentially gained by covering them with solar collectors. The paper examined the potential taken into account these barriers and incorporated them into a model, which utilized Geographic Information Science (GISc) techniques of Light Detection and Ranging (LiDAR) along with Solar Analyst tools developed by ESRI. This analysis demonstrates that the UT Campus has significant potential for generating solar energy, even without placement of PV arrays on its treasured red-tile roofs, but economically the price of solar energy is still too high to compete with the current highly efficient natural gas power generation. Although extensive installation of solar panels cannot be justified solely on an economic savings basis today, the price of solar PV is dropping and solar power may be economically advantageous for the University in the near future.

- by Moulay Anwar Sounny-Slitine
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- Sustainable Development, LiDAR, Solar Energy

The distribution of vegetation within urban zones is well understood to be important for delivery of a range of ecosystem services. While urban planners and human geographers are conversant with methodologies for describing and exploring the volumetric nature of built spaces there is less research that has developed imaginative ways of visualising the complex spatial and volumetric structure of urban vegetation from the treetops to the ground. Using waveform LiDAR data to measure the three-dimensional nature of the urban greenspace, we explore different ways of virtually, and tangibly engaging with volumetric models describing the 3D distribution of urban vegetation. Using waveform LiDAR data processed into voxels (volumetric pixels) and experimenting with a variety of creative approaches to visualise the volumetric nature of the data, we describe the development of new methods for mapping the urban green volume, using a combination of Geographic Information Systems (GIS), Minecraft, 3D printing and Computer Numerical Control (CNC) milling processes. We demonstrate how such methodologies can be used to reveal and explore the complex nature of the urban green volume. We also describe the outcome of using these models to engage diverse audiences with the volumetric data. We explain how the products could be used readily by a range of urban researchers and stakeholders: from town and city councils, to architects and ecologists.

- by Jo McCallum
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- LiDAR, 3D visualisation, Tangible User Interfaces, 3D printing

Slave cabins within two settlements at Bush Camp Field and Behavior on Sapelo Island, Georgia deviate from typical low country Georgia architectural and landscape patterns. Rather than poured tabby duplexes arranged in a linear fashion, excavations in the 1990s by Ray Crook identified two wattle and tabby daub structures—both with slightly different architecture, and both built in an African creolized style. A 2016 University of Tennessee project attempted to locate additional slave cabins in both settlements to test if these structures are pattern or anomaly. LiDAR, historical maps, pedestrian surveys, and shovel tests allowed for the identification of an additional cabin, also made of wattle and tabby daub. Following Crook’s analysis and using Geechee oral history, we argue that the nonlinear cabin placement and creolized African, Caribbean, and European architectural elements are both examples of one end of the spectrum of independence within 19th century low country slavery.

- by Lindsey Cochran
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- Archaeology, Geophysics, Historical Archaeology, LiDAR

Recognizing 3D objects in the presence of noise, varying mesh resolution, occlusion and clutter is a very challenging task. This paper presents a novel method named Rotational Projection Statistics (RoPS). It has three major modules: local reference frame (LRF) definition, RoPS feature description and 3D object recognition. We propose a novel technique to define the LRF by calculating the scatter matrix of all points lying on the local surface. RoPS feature descriptors are obtained by rotationally projecting the neighboring points of a feature point onto 2D planes and calculating a set of statistics (including low-order central moments and entropy) of the distribution of these projected points. Using the proposed LRF and RoPS descriptor, we present a hierarchical 3D object recognition algorithm. The performance of the proposed LRF, RoPS descriptor and object recognition algorithm was rigorously tested on a number of popular and publicly available datasets. Our proposed techniques exhibited superior performance compared to existing techniques. We also showed that our method is robust with respect to noise and varying mesh resolution. Our RoPS based algorithm achieved recognition rates of 100, 98.9, 95.4 and 96.0 % respectively when tested on the Bologna, UWA, Queen's and Ca' Foscari Venezia Datasets.

- by Ferdous Ahmed Sohel
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- Archaeology, Computer Vision, Image Processing, Machine Learning

The urban heat island (UHI) phenomenon is a significant worldwide problem caused by rapid population growth and associated urbanization. The UHI effect exacerbates heat waves during the summer, increases energy and water consumption, and causes the high risk of heat-related morbidity and mortality. UHI mitigation efforts have increasingly relied on wisely designing the urban residential environment such as using high albedo rooftops, green rooftops, and planting trees and shrubs to provide canopy coverage and shading. Thus, strategically designed residential rooftops and their surrounding landscaping have the potential to translate into significant energy, long-term cost savings, and health benefits. Rooftop albedo, material, color, area, slope, height, aspect and nearby landscaping are factors that potentially contribute. To extract, derive, and analyze these rooftop parameters and outdoor landscaping information, high resolution optical satellite imagery, LIDAR (light detection and ranging) point clouds and thermal imagery are necessary. Using data from the City of Tempe AZ (a 2010 population of 160,000 people), we extracted residential rooftop footprints and rooftop configuration parameters from airborne LIDAR point clouds and QuickBird satellite imagery (2.4 m spatial resolution imagery). Those parameters were analyzed against surface temperature data from the MODIS/ASTER airborne simulator (MASTER). MASTER images provided fine resolution (7 m) surface temperature data for residential areas during daytime and night time. Utilizing these data, ordinary least squares (OLS) regression was used to evaluate the relationships between residential building rooftops and their surface temperature in urban environment. The results showed that daytime rooftop temperature was closely related to rooftop spectral attributes, aspect, slope, and surrounding trees. Night time temperature was only influenced by rooftop spectral attributes and slope.

- by Qunshan Zhao and +1
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- Sustainable Urban Environments, LiDAR, Urban Heat Island Effect, Landscaping

Evaluation oJ tree height determination Fom airborne laser scanner data over the richly structured natural Jorests oJ the Bavarian Forest National Park. The purpose of this study was to investigate the accuracy of manual tree height measurements with airborne laser scanners. The study material included small-footprint time-offtight laser scanner data acquired in the spring and summer of 2002 using a TopoSys Falcon II air borne laser system over the montane mixed forests dominated by Norway spruce (Picea abies) and European beech (Fagus sylvatica) of the Bavarian Forest National Park near Passau, Germany. A data set based on 3055 trees in 23 different stands was available for the determination of the accuracy of tree height measurements using laser scanning data. 1001 of these trees could be correctly identified visually with the laser scanning data. Tree heights are underestimated by an average ofO.53 m. The standard deviation was 1.24m. The average value of the absolute tree height differences was 1.01 m, with a standard deviation of 0.9 m. The underestimation of height was greater among conifers (0.74m) than among deciduous trees (0.37 m). However, the standard deviation was higher for deciduous trees (1.43 m) than for conifers (1.25 m). The deviation in height was corrected with the aid of regression models attaining a coefficient of determination ofO.99 m. In regard to height measurements, these results indicate a similar level of accuracy as those acquired through conventional forestry practices. Indeed, there are some indications that they may even be more accurate.

Floodplains may be transformed when environmental changes or human activity causes alluvial systems to cross channel pattern thresholds. Thresholds between pattern states based on occurrence fields are only available for some pattern distinctions, and these may not encompass the alluvial contexts and range of dynamic factors involved. Pattern changes now known from the UK Holocene are reviewed as a basis for appreciating the potential for future transformations in a changing environment. These involved episodic boulder and gravel spreads in upland environments, and braiding $ meandering, anastomosing ! meandering and active $ inactive transformations in more lowland contexts. Concern for possible impacts of climatic change need to be grounded in an appreciation of the nature and scale of these past changes. Some potential future changes may be relatively predictable in location (braiding $ meandering); others are more difficult given both present knowledge and the varying, modified and inheritance-rich 'contexts of vulnerability' that floodplains now represent. Implications for management are discussed.

- by Mark Macklin
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- Management, Environmental Engineering, Civil Engineering, Remote Sensing

For many decades attempts to accomplish Automatic Target Recognition have been made using both visual and FLIR camera systems. A recurring problem in these approaches is the segmentation problem, which is the separation between the target... more

- by Ernst Bovenkamp
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- Image Processing, Pattern Recognition, LiDAR, Image segmentation

- by jamal esenkanova
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- LiDAR