3D Printed Map of London

london 3dSan Francisco-based programmer Andrew Godwin has found a way to use the British government’s LIDAR data to create a scale model of a small slice of Central London, the city where he grew up.

Godwin got the idea for his map called “London Rising” when he learned through Twitter that the UK Environment Agency had begun releasing LIDAR data of London’s landscape. Searching for innovative ways to use the 3D printer he had recently purchased, Godwin discerned he could transform the raw data into a 3D map with actual vertical relief.

He ran into the project’s first major obstacle when he began converting the raw LIDAR data into a printable STL file that the 3D printer could read. Godwin relied on some basic geometry to convert the cloud of data points into a 3D model, but refining its jagged edges into a smoother model required some feature extraction skills that Godwin doesn’t possess. “I just took all the data, averaged out points to make a lower-detail heightmap, snapped the heights to 3m intervals and applied neighbour-based smoothing to the whole thing,” Godwin writes in his detailed blog post about the project.

There were many lessons learned in turning his idea into a reality, but Godwin plans to apply his conversion of LIDAR data to 3D relief maps to other cities around the globe. Perhaps his new home base San Francisco will be the subject of his next attempt, as he’s already begun collecting LIDAR data of San Francisco’s peninsula from the USGS. The map of London that hangs above his desk serves as a reminder that a lot is possible with a little bit of data, a 3D printer, and a surplus of perseverance and patience.

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Rock Art Documented in 3D

Credit: Photo and enhancement: C. Defrasne

Credit: Photo and enhancement: C. Defrasne

Archaeologists at the University of York have undertaken pioneering scans of the highest prehistoric rock art paintings of animals in Europe.

Studying the rock paintings of Abri Faravel, a rock shelter in the Southern French Alps 2,133m above sea level, archaeologists used car batteries to power laser and white-light scanners in a logistically complex operation.

Producing virtual models of the archaeological landscape, researchers have now published the scans in Internet Archaeology — an online, open-access journal.

Abri Faravel was discovered fortuitously in 2010. The rock shelter has seen phases of human activity from the Mesolithic to the medieval period, with its prehistoric rock paintings known to be the highest painted representations of animals (quadrupeds) in Europe.

Dr Kevin Walsh, Senior Lecturer in York’s Department of Archaeology and project lead, said: “After years of research in this valley, the day we discovered these paintings was undeniably the highlight of the research programme.

“Whilst we thought that we might discover engravings, such as in the Vallée des Merveilles to the south-east, we never expected to find prehistoric paintings in this exposed area that affords so few natural shelters.

“As this site is so unusual, we made the decision to carry out a laser-scan of the rock shelter and the surrounding landscape, plus a white-light scan of the actual paintings. The scanning was logistically complex as our only source of electricity was car batteries, which, along with all of the scanning equipment, had to be carried up to the site.

“This is the only example of virtual models, including a scan of the art, done at high altitude in the Alps and probably the highest virtual model of an archaeological landscape in Europe.”

 

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Virtual Reality Crime Scenes

vrResearchers from Staffordshire University’s Centre of Archaeology and Forensic and Crime Science have been awarded a $203,000 European Union grant to research virtual reality crime scene technology. The project will apply a range of digital recording methods to complex criminal investigation, experts say.

(File photo – An attendee tries on the Oculus VR Inc. Rift Development Kit 2 headset at the 2014 Electronic Entertainment Expo (E3) in Los Angeles, California June 11, 2014. (REUTERS/Kevork Djansezian)

Although still at the concept stage, the technology could potentially revolutionize how evidence is presented in court.

“The project will use a variety of different techniques to record crime scenes in high definition. We will be trialling the use of drones, laser scanners, photogrammetry and a wide range of other methods used in archaeological research and games technology,” Caroline Sturdy Colls, project lead and associate professor of Forensic Archaeology and Genocide Investigation at Staffordshire University, told FoxNews.com, via email. “The data [we] will collect will be 3D, so this means that we can then create virtual environments from it, into which jurors and experts can be ‘transported’ into a virtual crime scene.”

A number of major tech companies have thrown their weight behind virtual reality. Earlier this year, for example, Oculus, which is owned by Facebook, began shipping its much-anticipated Rift technology. Last week, at its Google I/O developer conference in Mountain View, Calif. Google announced Daydream, a virtual reality platform for Android devices that will debut in the fall. Samsung launched its Gear VR headset last year.

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Laser Scanning – Based Bridge Assessment

bridgeThe Institute for Transportation at Iowa State University has released a report that considers the performance of terrestrial laser scanners as a means to automatically detect cracks when carrying out bridge structural condition assessments.

This research project proposed to measure the performance of TLS for the automatic detection of cracks for bridge structural condition assessment. Laser scanning is an advanced imaging technology that is used to rapidly measure the three-dimensional (3D) coordinates of densely scanned points within a scene. The data gathered by a laser scanner are provided in the form of point clouds, with color and intensity data often associated with each point within the cloud.

Point cloud data can be analyzed using computer vision algorithms to detect cracks for the condition assessment of reinforced concrete structures. In this research project, adaptive wavelet neural network (WNN) algorithms for detecting cracks from laser scan point clouds were developed based on the state-of-the-art condition assessment codes and standards. Using the proposed method for crack detection would enable automatic and remote assessment of a bridge’s condition. This would, in turn, result in reducing the costs associated with infrastructure management and improving the overall quality of our infrastructure by enhancing maintenance operations.

 

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NASA’s EAARL Upgraded

EAARL-LIDAR_plane-thThe original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL) was extensively modified to increase the spatial sampling density and to improve performance in water ranging from 3 to 44 meters (m).

The new (EAARL-B) sensor features a higher spatial density that was achieved by optically splitting each laser pulse into three pulses spatially separated by 1.6 m along the flight track and 2.0 m across the flight track, on the water surface when flown at a nominal altitude of 300 m (984 feet). The sample spacing can be optionally increased to 1.0 m across the flight track. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10 and by designing a new “deep-water” receiver, which is optimized to exclusively receive refracted and scattered light from deeper water (15–44 m).

Two different clear-water flight missions were conducted over the U.S. Navy’s South Florida Testing Facility (SFTF) to determine the EAARL-B calibration coefficients. The SFTF is an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. We used 23 selected polygons at 23 distinct depths to compare a reference dataset from this site to determine EAARL-B calibration constants over the depth range of 6.5 to 34 m.

Read the full story on this impressive research platform.

 

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3D Roof Reconstruction from Lidar

remotesensing-08-00415-ag_jpegThis is an interesting research paper written by a group of Chinese researchers who are also trying to improve the automation of 3D roof reconstruction from airborne lidar data.

They report, “A new approach for three-dimensional (3-D) reconstruction of building roofs from airborne light detection and ranging (LiDAR) data is proposed, and it includes four steps. Building roof points are first extracted from LiDAR data by using the reversed iterative mathematic morphological (RIMM) algorithm and the density-based method. The corresponding relations between points and rooftop patches are then established through a smoothness strategy involving “seed point selection, patch growth, and patch smoothing.” Layer-connection points are then generated to represent a layer in the horizontal direction and to connect different layers in the vertical direction. Finally, by connecting neighboring layer-connection points, building models are constructed with the second level of detailed data.

The key contributions of this approach are the use of layer-connection points and the smoothness strategy for building model reconstruction. Experimental results are analyzed from several aspects, namely, the correctness and completeness, deviation analysis of the reconstructed building roofs, and the influence of elevation to 3-D roof reconstruction.

In the two experimental regions used in this paper, the completeness and correctness of the reconstructed rooftop patches were about 90% and 95%, respectively. For the deviation accuracy, the average deviation distance and standard deviation in the best case were 0.05 m and 0.18 m, respectively; and those in the worst case were 0.12 m and 0.25 m. The experimental results demonstrated promising correctness, completeness, and deviation accuracy with satisfactory 3-D building roof models.”

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Estimating Crop Biomass from Lidar

cornThis research team from Chain and Canada looked at the effects of a number of lidar data collection parameters on the estimation of crop biomass estimation. Their findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results.

Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters.

Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Their results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations.

In general, the results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

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Forensic Competency Testing

hxgnThis is something different. One of the items being offered at the upcoming HxGN LIVE user conference being held in Anaheim, CA June 13 – 16 will be a low-cost, proctored competency testing for those who use the Leica ScanStation. The intent of the course will be to certify people based on ISO/IEC 17025:2005 Section 5.2.1 for forensic laser scanning.

There will also be a number of additional forensic courses including crime scene management and court defensible evidence and procedures.

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Chimney Rock

chimneyA group of researchers at the University of Colorado, Boulder want to make it possible for everyone to virtually walk through the ancient dwellings at Chimney Rock National Monument as the ancient pueblo people did.

Their work is part of Project Map, an effort to model ancient and historic monuments across the state. Chimney Rock is one of their first projects because of its archaeological ties to Chaco Canyon National Historic Park, and for decades researchers from CU Boulder have worked at the site, which was mainly inhabited between 925 and 1125.

“This is one of the most important national monuments of the Chacoan culture in the state of Colorado,” Gutierrez said.

The team plans to make the model accessible to the public as an all encompassing virtual reality experience so people will be able to walk the ancient paths themselves, Gutierrez said. Transferring the data to a video gaming platform will likely start in the fall.

The model also creates a permanent record of the site, so that future researchers and site managers will be able to tell exactly how it changes over time.

Posted in 3D Modeling, cultural heritage, Historic Preservation, Research | 2 Comments

Lasers or Cameras for Pavement Analysis?

profilerThis reminds me of my masters thesis on skid resistance of asphalt pavements.

A University of Texas at Arlington engineer is working with the Texas A&M Transportation Institute to assess whether scanning lasers can accurately measure microtexture of pavement aggregates, which are used in asphalt and concrete mixtures.

Roger Walker, a professor of computer science and engineering, is leading the two-year, $671,011 project, which is funded through the Texas Department of Transportation. The agency currently uses camera-based systems to assess aggregate characteristics.

“These lasers will enable TxDOT to more accurately measure the microtexture of the aggregates,” Walker said. “The laser system also will measure aggregate shape and angularity, offering important insights into which materials and mixes work best on Texas roads. This could ultimately affect sustainability, cost and safety.”

Walker’s project will determine the viability of replacing the current camera system with lasers. The data generated in the study will be crucial for the development of new adhesive systems that make binding asphalt and concrete better and longer lasting.

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