Massive Reef Discovered Behind Great Barrier

North-westerly view of the hidden reef. Depths are coloured red (shallow) to blue (deep), over a depth range of about 50 metres. Credit: James Cook University

North-westerly view of the hidden reef. Depths are coloured red (shallow) to blue (deep), over a depth range of about 50 metres. Credit: James Cook University

Scientists had an idea that there was a much larger reef behind the Great Barrier, but it was the Royal Australian Navy who confirmed the shape, size, and vast scale of the deep reef with bathymetric lidar.

“We’ve now mapped over 6,000 square kilometres. That’s three times the previously estimated size, spanning from the Torres Strait to just north of Port Douglas,” says one of the researchers, Mardi McNeil from Queensland University of Technology.

“They clearly form a significant inter-reef habitat which covers an area greater than the adjacent coral reefs.”

The discovery of this vast, living reef has now got researchers wondering how the effects of climate change and ocean acidification have been felt by these algae populations. Unlike the life on the Great Barrier Reef, which we have decades of history to learn from, we’re just beginning to get to know this ecosystem.

“For instance, what do the 10- to 20-metre-thick sediments of the bioherms tell us about past climate and environmental change on the Great Barrier Reef over this 10,000 year time-scale?” says one of the team, Robin Beaman from James Cook University in Queensland, adding that they’re now going to have to figure out what kinds of life are sustained by these massive bioherms.

 

 

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Automation as a Continuum

quanThis is a very interesting article and video interview with the CEO of Quanergy, Dr. Louay Eldada who believes automated vehicles will require video, radar and lidar operating at different wavelengths to provide a complete picture of the environment with redundancy.

Dr. Eldada believes that the automation process itself will be a continuum, the length of which will be driven by the cost curve for the technology. The greater the demand for the sensors the lower the costs of manufacturing for greater quantities which will stimulate more demand and so on.

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Is the 3D Laser Scanning Industry Maturing?

faroIn the early days of an emerging industry the innovations come at a rapid pace. As an industry begins to mature that pace naturally slows down. Perhaps the manufacturers are working on a new round of disruptive products that will soon be announced, but for now it seems that recently we are seeing mainly incremental improvements.

I am thinking of something like what FARO did a few years ago when they shocked the market with their Focus3D.

A lot of the excitement today seems to be with technologies that use 3D data such as augmented/virtual reality and the autonomous vehicle industry. These drive the need for 3D data which is good for the laser scanning ecosystem.

Perhaps it’s just me. What do you think?

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Self Driving Trucks

ottoNow this is going to get your attention – an autonomous tractor trailer, but actually the ability to mount the sensor systems above most of the traffic is a distinct advantage.

Looks like taxi giant Uber has acquired Otto, a start-up founded by ex-Google engineer Anthony Levandowski and targeted solely at self-driving trucks. The merger and acquisition activity in the autonomous vehicle space is just getting started.

The Otto website does not provide a lot of detail on the technology, but it is reported that Otto has developed their own in-house lidar technology.

As you can see in the video real world testing is taking place. The main Ohio toll road which joins Chicago with the East Coast is scheduled to test automatically controlled vehicles soon and Uber will test up to 100 autonomous cabs on the downtown streets of Pittsburgh using Volvo XC90 models, retrofitted with the requisite technology, before year end.

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Multisensor and Multispectral Lidar

chris-hopkinsonThe potential of multispectral imaging has held great promise for many years. Chris Hopkinson provided a link to a recent research project where his team looked at the use of multisensor and multispectral lidar to see if this might improve the ability to characterize and classify forest environments. The paper is open access.

From the abstract – For practical design and manufacture reasons, the 1064 nm near-infrared (NIR) wavelength has been the most commonly adopted, and most literature in this field represents sampling characteristics in this wavelength. However, due to eye-safety and application-specific needs, other common wavelengths are 1550 nm and 532 nm. All provide canopy structure reconstructions that can be integrated or compared through space and time but the consistency or complementarity of 3D airborne LiDAR data sampled at multiple wavelengths is poorly understood.

Here, we report on multispectral LiDAR missions carried out in 2013 and 2015 over a managed forest research site. The 1st used 3 independent sensors, and the 2nd used a single sensor carrying 3 lasers. The experiment revealed differences in proportions of returns at ground level, vertical foliage distributions, and gap probability across wavelengths. Canopy attenuation was greatest at 532 nm, presumably due to leaf tissue absorption. Relative to 1064 nm, foliage was undersampled at midheight percentiles at 1550 nm and 532 nm.

Multisensor data demonstrated differences in foliage characterization due to combined influences of wavelength and acquisition configuration. Single-sensor multispectral data were more stable but demonstrated clear wavelength-dependent variation that could be exploited in intensity-based land cover classification without the aid of 3D derivatives. This work sets the stage for improvements in land surface classification and vertical foliage partitioning through the integration of active spectral and structural laser return information.

 

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Ford’s Strategic Investments

autoFord has announced its intention to produce a fully autonomous, or “SAE level 4-capable” (operable without a wheel of pedals), vehicle for commercial operations by 2021 as part of a ride-hailing or ride-sharing service.

“The next decade will be defined by automation of the automobile, and we see autonomous vehicles as having as significant an impact on society as Ford’s moving assembly line did 100 years ago,” said Mark Fields, Ford president and CEO.

The four key investments and collaborations that Ford is making involve expanding its research into advanced algorithms, 3D mapping, LiDAR, and radar and camera sensors. The companies are:

•Velodyne, a Silicon Valley-based leader in light detection and ranging (LiDAR) sensors with whom Ford has a 10-year-long relationship that is currently aiming to commercialise LiDAR.

•SAIPS, a computer vision and machine learning company acquired by Ford to further enhance image and video processing through the use of algorithmic solutions and artificial intelligence.

•Nirenberg Neuroscience, a machine vision company founded by neuroscientist Dr Sheila Nirenberg, who cracked the neural code the eye uses to transmit visual information to the brain, that Ford has exclusively licensed agreement to bring humanlike learning to its virtual drivers.

•Civil Maps, a Berkeley-based company that Ford has invested in to further develop high-resolution 3D mapping capabilities to generate high-resolution maps for its autonomous vehicles.

Ford is also tripling its autonomous vehicle test fleet in 2016 to around 30 self-driving Fusion Hybrid sedans – largest such test fleet for any automaker – for tests on the roads around California, Arizona and Michigan, and plans to triple it yet again next year.

The construction of a dedicated campus in Palo Alto, is meanwhile set to add two buildings and 14,000m2 of work and lab space under the plans to double the local team by the end of 2017.

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Lidar Drone Market Research Report

drone__20160203120903_ZHThe increasing automation through LiDAR drones and reduction of human efforts drive the growth of the market. LiDAR drones have applications in corridor mapping, archaeology, precision farming, environment, construction, and entertainment.

PDF sample download: http://www.marketsandmarkets.com/pdfdownload.asp?id=128835365

Both top-down and bottom-up approaches have been considered to estimate the size of the LiDAR drone market. This research study involves an extensive usage of secondary sources, directories, and databases (such as Factiva and OneSource) to identify and collect information useful for the technical, market-oriented, and commercial study of the market.

The points below explain the research methodology applied for this report:
The market for rotary wing LiDAR is expected to grow at the highest CAGR between 2016 and 2022. Rotary wing drones are smaller in size and cheaper than fixed wind LiDAR drones.

Their design enables them to access confined spaces such as pipelines and bridges, owing to which they are used for inspection & monitoring applications. They can fly vertically and horizontally and can also hover in a fixed position, which makes them best suited for aerial photography and high-resolution video capturing.

The LiDAR drone ecosystem comprises LiDAR sensor manufacturers such as SICK AG (Germany), Velodyne LiDAR (U.S.), FARO Technology (U.S.), and Phoenix Aerial Systems (U.S.) among others; LiDAR systems providers such as YellowScan (France), Riegl Laser Measurement Systems (Austria), drone providers such as 3D Robotics Inc. (U.S), and DJI (China) among others.

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Utility Engineering and Surveying Institute Call for Abstracts

uesiWe encourage you to submit a presentation abstract to a Utility Engineering and Surveying Institute (UESI) conference by the Sep 14 deadline.  The call for abstracts is at http://www.pipelinesconference.org/call-for-submissions-2017/, and the conference will be held Aug 6-9, 2017, in Phoenix, AZ.  It’s called the Pipelines Conference because it is existing and established, but don’t let that dissuade you.  Your presentation need not be about pipelines; it can be anything about surveying or geomatics in the broadest sense (i.e., “geospatial”).

Note that although the Pipelines Conference normally requires peer-reviewed papers (submitted later); papers are not required for the Surveying/Geomatics track because it is new and we’re trying to increase participation.  Nonetheless papers are encouraged, and submittals that include papers will be given preference.  In addition, only papers will be published in the proceedings; presentation slides will not.

Some background:  The ASCE Geomatics Division is now part of UESI, a new ASCE Institute (seewww.asce.org/utility-engineering-and-surveying/utility-engineering-and-surveying-institute/ for more information).  With enough participation, this could ultimately evolve into a major surveying/geomatics/geospatial conference in its own right.

Thanks in advance for considering participation at this conference!   The first Pipelines Conference with a Surveying/Geomatics track was held last month in Kansas City, and it went quite well.  We want to do even better in 2017!

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Velodyne Investment Update

Roadmap to AutomationWOW – this is much bigger news than I reported on yesterday. The complete story is that Ford and Baidu are joining forces with Velodyne by investing $150 million to further autonomous vehicle research and development. Velodyne has certainly come a long way from the days of building a lidar to win the DARPA contest.

This is all about reducing the cost of solid state lidar.“LiDAR continues to prove itself as the critical sensor for safe autonomous vehicle operation,” said David Hall, founder and CEO, Velodyne LiDAR. “This investment will accelerate the cost reduction and scaling of Velodyne’s industry-leading LiDAR sensors, making them widely accessible and enabling mass deployment of fully autonomous vehicles. We are determined to help improve the goal of safety for automotive vehicles as soon as possible, as well as empower the efficiency autonomous systems offer.”

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Baidu Invests in Velodyne

autoThis is potentially very BIG news for both Baidu, a mega Chinese consumer Internet company and Velodyne Lidar. Autonomous vehicles have a much greater potential in a highly controlled state government.

It’s learned that Baidu has reached investment intent with Velodyne LiDAR, but no accurate investment amount or share ratio has been reported. In the future, the two companies will conduct deep cooperation in self-driving and other areas. Velodyne is a Silicon Valley company which established in 1983, famous for its 64-Line Laser Radar Product, which is used by Google’s self-driving car.

Baidu established self-driving business unit in December, 2015, and proposed a “three years for commercial vehicles and five years for mass production”plan. Self-driving project is on trial operation in Wuhu and Wu Village in succession, and now the product in under testing in Shanghai. Wang Jing, General Manager of Baidu’s self-driving business unit, said that Baidu is directly aiming at fully automatic driving and will buy the most expensive sensor to protect customers’safety and gradually achieve commercial mass production.

He reveals that the supplying price for Velodyne 64-line Laser Rader product has decreased from RMB 700,000 to RMB 500,000, resulted by Baidu’s mass purchasing. Baidu will have an opportunity to obtain a cheaper product after it holds Velodyne LiDAR’s shares. For Velodyne LiDAR, cooperating with a Chinese company makes it easier to open the domestic market. China has become one of the most active countries in R&D of self-driving technologies, and Baiduhas leading technologies among all domestic companies. The two sides may also consider cooperation in technologies, resources, apart from strategic layouts.

 

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