GPS World

Category: Lidar

  • Carlson releases Scan2K terrestrial scanner

    Carlson Software has released its Scan2K Laser Scanner, a versatile, fast, easy-to-use solution for the creation of accurate 3D survey data up to a range of 2K (2,000) meters. Carlson introduced the product at the Pennsylvania Society of Land Surveyors’ 2020 Conference.

    Carlson’s Bradley Husack, Special Projects Engineer, and Michael Hyman, Regional Director with the Scan2K at the Pennsylvania Society of Land Surveyors’ conference. (Photo: Carlson)
    Carlson’s Bradley Husack, Special Projects Engineer, and Michael Hyman, Regional Director with the Scan2K at the Pennsylvania Society of Land Surveyors’ conference. (Photo: Carlson)

    Built with surveyors in mind, the Scan2K is at home in the field with its weather-proof housing, user-friendly sunlight-visible touch screen interface with simple, menu-driven operations for quickly collecting and georeferencing point cloud data. With an integrated high-resolution camera, inclinometers, a compass, and an L1 GNSS receiver, the Scan2K can be deployed in many environments and orientations, including mobile operations.

    Carlson’s partner on the Scan2K project is Teledyne Optech, a world leader in 3D survey systems. Carlson will be the exclusive global distributor of the OEM Scan2K solution.

    “The Scan2K addresses the diverse range of applications for a laser scanner in the surveying and mining industries,” said Bradley Husack, a Special Projects Engineer at Carlson. “Carlson is bringing to market an all-in-one solution that now leads the market in versatility, speed, and value.”

    The Carlson Scan2K has a simple, sunlight-visible touchscreen interface. (Photo: Carlson)
    The Carlson Scan2K has a simple, sunlight-visible touchscreen interface. (Photo: Carlson)

    Beyond its impressive 2,000 meter range, the Scan2K also has short- and medium-range modes, as well as the capability to record over 500,000 points per second, all within the chosen scanning target window.

    Additionally, each laser pulse from the Scan2K records up to four returns, providing the capability to record the first return for a blocking object (such as a leaf) as well as the last return for an object behind it (such as a wall), and the versatility to exclude one or the other.

    The Carlson Scan2K comes bundled with ATLAScan software, a powerful yet simple solution for registering the point cloud, as well as Carlson Point Cloud Advanced for feature extraction into Carlson’s suite of CAD office products.

    The Scan2K comes ready to be equipped with an additional external camera, an external GNSS receiver, or for mobile operation.

    Whether on a tripod, a vehicle, or another moving platform, the performance offered by the Scan2K easily makes it a versatile terrestrial laser scanner for the market.

  • Delving into a jungle mystery

    Image: PrecisionHawk
    Image: PrecisionHawk

    Earlier this year, a drone pilot and two data scientists from PrecisionHawk traveled to the Philippines for a unique mission — to fly drones equipped with lidar sensors over a dense rainforest to map ancient trade paths. The aim was to find buried treasure left by the Japanese during World War II.

    PrecisionHawk was approached by the producers of a new History Channel show to help them navigate the Filipino rainforests. Through the combination of air and ground sensors, including a DJI M600 UAV equipped with a Riegl miniVUX lidar sensor and a Sony a6000 camera, PrecisionHawk staff produced a colorized 3D map of the forest.

    The History Channel aired the series premiere of “Lost Gold of World War II” on March 19, 2019; all eight episodes are now available for streaming. The second episode features visuals generated by PrecisionHawk, as well as interviews with the drone pilot and data scientists.

    Photo: PrecisionHawk
    Photo: PrecisionHawk

  • Drones and imagery: Utilities turn to artificial intelligence

    How AI and machine learning algorithms redefine the way utility companies manage their infrastructure

    By Jaro Uljanovs, Lead AI Developer and Data Scientist, Sharper Shape

    Artificial intelligence (AI) boasts a wide range of potential applications, across nearly every industry imaginable — healthcare, automotive, retail, even fast food. But it’s the utility industry where AI and machine learning (ML) are beginning to demonstrate some of their most impactful effects on many aspects of the business. Power companies are increasingly leaning on AI to improve their electricity delivery and prevent potential wildfires, and AI is actually enhancing, rather than eliminating, human jobs.

    From data collection and analysis to their presentation of actionable insights, AI and ML algorithms are quickly redefining how utility companies manage their electric infrastructure.

    Consolidating and classifying data

    Utility companies oversee massive infrastructure networks, comprising poles, conductors, substations and transmission and distribution lines that span thousands of miles. The vegetation surrounding this key infrastructure must also be monitored, as it presents a danger of fire or outage.

    Taking a comprehensive snapshot of these assets means utilizing a variety of different sensors for network inspections. These sensors include lidar, color (RGB), hyperspectral and thermal imagery.

    This allows the system to capture everything — from vegetation proximity, to infrastructure assets, to individual components (such as insulators on poles) and their operational integrity, to hot spots indicating potential fire risks.

    That’s a lot of data to capture, catalog and process. And there are a lot of individual elements within that data — even in just one image — to pinpoint and classify, let alone do so accurately. Classifying billions of data points across all of those images is an impossibly time-consuming task to do manually.

    Photo: shaunl/E+/Getty Images
    Photo: shaunl/E+/Getty Images

    AI and ML tools can accomplish that same work — scanning thousands of images collected across thousands of miles of utility infrastructure — in seconds. Lidar point cloud segmentation can detect conductors (quite a difficult component-type to segment) with an accuracy of over 90%, while hyperspectral image segmentation can identify vegetation species with an accuracy of up to 99%.

    More than that, when paired with drone sensors, these algorithms can also improve the upfront collection of images and data. AI and ML tools help to adjust sensor positioning in real time, in the event a signal is lost or the drone veers slightly away from its inspection flight path.

    By helping to readjust the sensors’ bearings while in flight, AI not only ensures more accurate data collection, but also that the flight doesn’t need to be done again or prematurely ended because of faulty data collection, saving time and money. AI pinpoints any faults in the sensors or the drone’s flight path while in the air, recalibrating as needed and identifying individual elements within the data as it comes through the sensor’s video feed.

    Breaking down silos to create a holistic data approach

    Key to all of this is eliminating the silos that tend to naturally build up between different data segments. In the utility inspection space, asset management, vegetation management, different sensors and so on all produce their own disparate, walled-off sets of data.

    When data is kept siloed like this, it becomes unnecessarily difficult if not impossible for teams to derive companywide insights or conclusions from the information being collected. And what good is all that data if it can’t be used to check against itself and enhance other sets of data?

    The northwest fire line of the wildfire that devastated Santa Rosa, California, taken by satellite Oct. 10. (Satellite image ©2017 DigitalGlobe)
    The northwest fire line of the wildfire that devastated Santa Rosa, California, taken by satellite Oct. 10. (Satellite image ©2017 DigitalGlobe)

    Good data management can’t exist in a piecemeal approach. It needs to be holistic, and AI provides the impetus to make that happen. AI provides a central resource for pooling all these data sources together, making it easier to cross-analyze for potential problems — like wildfire-prone vegetation or damaged components. When these issues are collected in one system, it becomes much easier to identify faults and resolve them — and do so far faster than it would be to manually sift through countless images of poles or vegetation maps.

    And for all the stereotypical concerns about AI eliminating work for human beings, at utility companies AI actually enhances the role that people have to play in the network inspection process. Because the AI is what analyzes the data, it’s not something that is dependent on the potentially biased expertise of a professional human inspector, nor is it prone to fatigue and the anomalous results that can come from that. But at the same time, AI can’t do everything itself. It’s a tool for presenting clearer, more accurate and more actionable information for the people to then act on with their own judgment.

    There’s a lot of easy-to-make assumptions, both good and bad, about AI. But at the end of the day, what AI really means for the utility industry is a more efficient and effective tool for providing the right information about a power company’s infrastructure — its transmission and distributions lines, its poles, and its nearby vegetation — into the hands of its key decision makers.

  • Pointfuse laser scanning software transforms digital construction workflows

    A design mesh. (Photo: Pointfuse)
    A design mesh. (Photo: Pointfuse)

    Pointfuse has released the latest version of its advanced point cloud processing software that converts the millions of individual measurements captured by laser scanning and photogrammetry.

    Featuring new streamlined classification to ensure maximum efficiency and multicore processing for unlimited conversion power, the new version of Pointfuse is set to transform workflows within digital construction, facilities management and virtual design applications.

    “Pointfuse is designed to make the use of point cloud data more accessible by removing many of the traditional barriers to use,” said Mark Senior, regional sales director at Pointfuse. “Obstacles such as processing time and computer power, incompatibility within existing workflows and outputs files that are large and complex; these have all been obliterated with the latest Pointfuse release.”

    Pointfuse now includes a new streamlined workflow which makes object classification easy, using templates and shortcuts to ensure maximum efficiency. This ability to classify objects within Pointfuse has had a huge impact on how as-built data is utilized within digital design workflows; being able to quickly compare specific as-built objects with the design enables more accurate clash detection, reducing the number of false clashes being flagged.

    IFC (Industry Foundation Classes — an open format data model that is intended to describe architectural, building and construction industry data) templates can also be created and edited for specific applications. With applications including architectural, MEP and HVAC, selected objects can be classified and mapped to ensure compatibility with onward workflows.

    Pointfuse also includes a new conversion engine which uses multicore processing to manage and enable unlimited point cloud conversion to provide real scalability. In addition, Pointfuse’s mesh models are intelligently optimized, reducing the working data size by a factor of up to 100, making them easy to share with online 3D collaboration platforms, such as BIM 360, 3D Repo, Revitzo and Trimble Connect.

    “Using Pointfuse we can create intelligent 3D mesh models in a fraction of the time,” commented Ben Callan, BIM coordinator in global construction services company ISG’s UK Fit Out business. “This accelerated modelling and reduced risk of error contributes to a direct reduction in costs when compared against traditional methods of modelling and point cloud data analysis. The easy to use, easy to consume outputs are also paving the way for new applications of the data including existing versus design clash avoidance and checks of temporary works against required construction activities.”

  • Viametris launches new version of urban and road scanner

    Photo: Viametris
    Photo: Viametris

    Viametris has launched the second-generation version of the vMS3D, its urban and road lidar scanner.

    The second-generation version of the 3D mobile vehicle scanner has been redesigned to be more compact. The system has been simplified considerably in both electronic and ergonomic terms to make it more robust and stable in adverse conditions and challenging environments.

    Despite being lighter, the second generation offers the same technological capacities as its predecessor, but is simpler to use and can be mounted on a vehicle in minutes.

    The system component (including the sensors) and the element to affix the device to the vehicle (the frame) previously formed one unit, but are now separated.

    • The redesigned system is much lighter (9 kg) and more compact.
    • The mechanism to fix the scanner to the vehicle, which formed part of the system in the first-generation version, has been transformed. A rigid metal frame, fixed onto two roof bars, now holds the system, which fits into a dedicated compartment in seconds. As the frame is rigid, it limits vibrations between the system and the vehicle and prevents any strain on the mechanics during acquisition.
    • The second auxiliary antenna, which measures the heading by satellite, is discreet and non-removable, and fixed directly to the vehicle chassis.

    The new design makes it easier to mount and use the system, a task that can be accomplished by a single person in under three minutes. Alignment takes place the first time the system is mounted and does not need to be repeated, saving valuable time each start.

    Technological features

    The vMS3D comprises a new set of components that are more robust and stable in difficult conditions.

    • The integrated connectors are next-generation and embedded-grade.
    • The control box for power supply and communication with the tablet has been moved inside the vehicle to offer increased comfort to the user.

    Specifications

    Receiver: Septentrio AsteRx-m2a GPS+GLONASS+BeiDou+Galileo, 448 channels – L1/L2, B1/B2, E1/E5B, RAW

    IMU: SBG-Systems Ellipse2-D

    Scanner: 700,000 points per second

    Centimeter precision

    Panoramic 30MP FLIR Ladybug 5+ camera

    Double antenna

    SLAM compatible

  • Fugro uses airborne RAMMS to acquire land and sea data

    Fugro has completed a landmark data acquisition campaign over the Turks and Caicos Islands, marking the first commercial success of its new Rapid Airborne Multibeam Mapping System (RAMMS).

    Working under contract to the United Kingdom Hydrographic Office (UKHO), the company acquired more than 7,400 square kilometers of integrated, high-resolution bathymetric, topographic and image data. The resulting deliverables will support updated nautical charts and coastal zone management activities in the region.

    Launched in August 2018, RAMMS is a highly efficient, next-generation airborne bathymetric mapping system that uses multibeam laser technology to deliver depth penetration and point densities, the company said. The compact sensor is deployed from small aircraft and can be integrated with other remote sensing technologies for simultaneous collection of multiple complementary datasets.

    For the Turks and Caicos project, this approach made it possible to acquire near-shore (bathymetry) and coastal (topography and imagery) data in a single deployment, producing a cost-effective solution and advancing Fugro’s sustainability goals by significantly reducing fuel consumption.

    “After years of development, it’s extremely gratifying to operate RAMMS commercially and to demonstrate to clients the value that this cutting-edge technology can bring,” said Mark MacDonald, Fugro Americas Marine Division hydrographic service line director.

    He pointed to the massive Turks and Caicos project as an example. “The system’s multibeam lidar capability allowed us to achieve point densities that otherwise would have required vessel-based surveys. With RAMMS, we were able to avoid that additional time and expense, and significantly reduce health and safety exposure.”

    Fugro is working on three additional RAMMS projects in the Americas region, one for UKHO in Belize, and two for the Canadian Hydrographic Society, in Quebec and Atlantic Canada. These projects are similar in scope to that of the Turks and Caicos project, combining bathymetry, topography and imagery for maximum value to clients, serving both navigation and coastal applications.

    Based on steady interest in RAMMS, Fugro and technology partner Areté Associates are building an additional system to meet anticipated contracting volumes in 2019.

    Fugro is also finalizing a cloud-processing capability, which will further improve client delivery by streamlining data review and approvals, and ultimately making data available for download-on-demand.

    Additionally, Fugro aims to operate the unmanned aerial vehicle-proven system autonomously in 2019, providing further operational efficiency gains and increasing access to remote project areas.

  • USGS selects Dewberry to complete lidar mapping for Florida

    This digital elevation model (DEM) indicates the type of data currently being acquired across Florida. (Photo: Dewberry)
    This digital elevation model (DEM) indicates the type of data currently being acquired across Florida. (Photo: Dewberry)

    High-resolution airborne lidar data to be acquired over 34,000 square miles for disaster response and recovery.

    Under an active Geospatial Products and Services contract, the U.S. Geological Survey (USGS) has selected Dewberry, a privately held professional services firm, to complete a statewide lidar mapping project for Florida. The project is funded by the Florida Division of Emergency Management and USGS as part of Hurricane Irma Disaster Recovery, Response and Preparedness measures being conducted by the state and federal agencies.

    The approximately $20 million project includes airborne lidar data acquisition, ground survey and preparation of bare earth point cloud and digital elevation model products for various applications to support response, recovery, and preparation for future storm events.

    The resulting quality level 1 data will be primarily used for hydrologic and hydraulic modeling and many engineering applications by the water management districts to mitigate the impacts of flooding caused by these storms.

    USGS and the Federal Emergency Management Agency (FEMA) will also utilize these data for various flood studies. The project encompasses an area of more than 34,000 square miles.

    Photo: Dewberry
    Photo: Dewberry

    Dewberry has acquired and processed nearly 22,000 square miles of lidar data for various local, state, and federal agencies in Florida within the past three years.

    “As we continue to map the state of Florida, we’re looking forward to using the best technology and personnel to complete such a vast undertaking,” said Dewberry Vice President and Director of Remote Sensing Amar Nayegandhi, CP, CMS, GISP. “Once these data are acquired and analyzed, they will be able to support USGS, FEMA, the Natural Resources Conservation Service, the Florida water management districts, and several other state and local agencies in their mission to better prepare for natural disasters and minimize loss of life and property; and use these scientific data to enhance and protect our quality of life.”

    Dewberry will serve as prime contractor for this project and will perform the majority of the data production. The firm is teaming with seven other partner firms including Woolpert Inc., Quantum Spatial Inc. and Digital Aerial Solutions, Inc, which will acquire and process data to support the project.

    Dewberry’s other subcontractors will be tasked with acquiring airborne lidar data.

    “We have 11 aircraft with top-of-the-line airborne lidar sensors being deployed for data acquisition starting in early December,” said Dewberry Senior Project Manager Elise MacPherson, PMP. “I’m excited to manage this project and support the needs of USGS, their partner federal agencies and the many stakeholders in Florida.”

  • Lidar data fused for understanding of tropical forests

    A University of Queensland, Australia, environmental project fused data from terrestrial and UAV lidar collections to estimate forest biomass.

    Forest ecosystems contain more biomass than any other ecosystem. Estimating biomass — a critical endeavor to detect the health of ecosystems — can be difficult. Traditional methods can be destructive, such as harvesting trees to measure the weight of the different components.

    “We know that forest ecosystems contain more carbon biomass than any other above-ground ecosystem on the planet,” said Kim Calders, Ghent University, on the TERN website. TERN is Australia’s land ecosystem observatory, under the University of Queensland.

    It’s estimated that Australian forests store about 10 billion tonnes of carbon, but calculating an exact figure without cutting down trees is difficult. “Traditional methods of estimating aboveground biomass are based on volumes calculated from cut trees and expensive field measurements of tree diameter and height,” Calders said.

    Enter 3D-FOREST

    The three-year 3D-FOREST project is funded by the Belgian Federal Science Policy Office led by Calders and Hans Verbeeck from Ghent University, partnering with Harm Bartholomeus and Martin Herold from Wageningen University.

    Tracking progress towards meeting major global environmental agreements and targets, such as the United Nations’ Sustainable Development Goals and The Paris Agreement, require detailed accounts of carbon stocks and how they’re changing over time.

    To meet this need, the 3D-FOREST project is developing new on-ground remote sensing techniques to measure biomass and forest structure and validate global-scale satellite measurements.

    “The concept of the project is to capture data to create ‘virtual forests’ with high level detail,” Calders said. “The combination of ‘bottom-up’ terrestrial laser scanning (TLS) and ‘top-down’ UAV lidar data improves biomass estimates and knowledge on how we can upscale plot-based measurements to the landscape level.”

    Harvesting virtual forests

    Representatives of the 3D-FOREST team undertook terrestrial laser scanning and UAV lidar data collection at three TERN sites: the TERN Litchfield Savanna SuperSite in the Northern Territory; the TERN Robson Creek SuperSite and the affiliate TERN Daintree Rainforest SuperSite in Queensland.

    Back in the lab, virtual 3D forests created from the lidar data are then ‘virtually harvested’. Quantitative structure models (QSM) digitally weigh individual trees by calculating their volume and converting this to carbon mass.

    “These 3D structural metrics and biomass estimates allow us to scale-up the spatial patterns of tree structure and evenness from the 1-hectare plot scale to entire forests,” Calders said. “This information is crucial for more efficient forest management, but also for better understanding of the spatial variation of forest structure in ecosystem models.”

    Scaling up to global carbon budgets

    As Europe’s, America’s and India’s space agencies get ready to launch satellites to measure and map the planet’s forests in high-resolution 3D, the value of on-ground and UAV lidar data collected by Calders’ team at TERN sites is even more apparent.

    The data from 3D-FOREST will be used to calibrate, validate and improve the accuracy of global bio-geophysical satellite data delivered by space missions including the European Space Agency’s BIOMASS, NASA’s GEDI, and the joint Indian Space Research Organisation and NASA NISAR.

    “The ability for these space missions to scale-up estimates of forest biomass to the global carbon budget and monitor ecosystem disturbances is dependent on the high-quality ground reference measurements collected at ecosystem research infrastructure sites, including TERN’s,” Calders said. “The emerging methods and technologies for data collection, and the speed of their development, are truly exciting.”

    The field campaign was made possible thanks to collaborations with the CSIRO, James Cook University and the Australian Government Department of Environment and Energy.

    For more information on the TERN Ecosystem Processes platform, its network of 12 open-access SuperSites and eddy covariance flux towers, and the data they collect, click here or explore the open data via TERN’s Data Discovery Portal.

  • Mobile mapping market size worth over $40B by 2024

    The mobile mapping market size is expected to be worth more than $40 billion by 2024, according to a new research report by Global Market Insights.

    The mobile mapping market is propelled by the increasing adoption of mobile devices such as smartphones and tablets across the globe. Smartphone users are extensively using mapping applications on their devices for navigation and driving assistance, the report said.

    Furthermore, they are also leveraging on the GIS and GPS applications to access geo-referenced data for searching nearby restaurants, cinema halls and other landmarks. This is encouraging the technology companies to commence mapping across the globe to acquire accurate GIS data and provide an enhanced customer experience.

    High initial investment is a major factor limiting the growth of the mobile mapping market. Currently, the market comprises a few major players with a long-standing expertise in location-based technologies. High initial investments in developing mobile mapping systems and assembling major components have restricted the entry of new players in the market.

    According to the report, the software market is anticipated to grow at a CAGR of 15 percent over the projected timespan. The growing demand for geo-referenced data acquisition and data analysis software among the organizations is driving the mobile mapping market growth. The software assists organizations in simplifying the data extraction process by combining the vital details. It retrieves geographic and spatial data captured by the positioning devices to develop maps and other graphic displays. This data is also used by enterprises to build effective decision support systems, which will drive the market demand.

    The report includes key industry insights in 250 pages with 341 market data tables and 38 figures and charts from the report, “Mobile Mapping Market Size, By Component (Hardware [Imaging Device, Laser Ranging Device & Scanning Device, Positioning Device], Software [Mapping Data Extraction, Data Processing], Service [Consulting, Integration & Maintenance, Managed Service]), By Application (Road & Railway Survey, GIS Data Collection, Vehicle Control & Guidance, Asset Management), By End-User (Agriculture, BFSI, Government & Public Sector, Real Estate, Retail, Mining, Telecommunication, Transport & Logistics), Industry Analysis Report, Regional Outlook (U.S., Canada, the United Kingdom, Germany, France, Italy, Spain, Australia & NZ, China, India, Japan, South Korea, Brazil, Mexico, Argentina, GCC, Israel, South Africa), Growth Potential, Competitive Market Share & Forecast, 2018 – 2024.”

    The mobile mapping technology is used for conducting road and rail surveys, collecting GIS data, and developing vehicle control and guidance systems and asset management systems. The road and rail survey market is expected to register a growth rate of over 17 percent during the forecast period. It is used to analyze the road and rail infrastructure and plan the engineering operations with minimum disruptions. The surveying authorities across the globe are using mobile mapping technology to create maps for the transportation department for road assessment purposes.

    The agriculture sector is estimated to grow at a CAGR of 22 percent during the forecast timeline. The integration of the GPS and GNSS devices into the farming process to acquire geospatial data is the primary factor driving the mobile mapping market share. Furthermore, the ability of the mobile mapping technology to monitor the crop yield and land variability also augments the demand for the technology among the farmers.

    The European region accounted for over 25 percent global mobile mapping market in 2017. The increasing investments by the government agencies have accelerated the adoption of mobile mapping technology in the region. For instance, in 2017, the U.K. government established the Geospatial Data Commission to frame a strategy for using the public sector location data to support the country’s growth.

    The Asia Pacific region will grow at a rapid pace over the forecast timespan. The rapid urbanization of the region and the growing number of infrastructural projects have fostered the growth of the mobile mapping market in the region. Moreover, the widespread adoption of smartphones has also driven the market size.

    Prominent players operating in the mobile mapping market are Phoenix LiDAR, Sharp Corporation, Teledyne Optech, TomTom International, Topcon Positioning Systems, MapJack, Mapquest, Navteq, NCTech, Microsoft, Mitsubishi, NovAtel, Phaseone industrial, Hexagon, EveryScape, Foursquare Labs and XIMEA.

    The major companies in the market are collaborating with other expert companies in the market to develop new product offerings and conduct strategic acquisitions to gain a competitive advantage over its competitors.

    For instance, in 2017, Garmin acquired Navionics, a provider of electronic navigational charts to the marine industry. This acquisition is aimed at combining the data from Navionics charts and Garmin’s blue charts to develop improved navigational services to its customers. Similarly, in 2017, Hexagon entered into an OEM partnership with Smart Guided Systems to develop new precision technologies for commercial applications.

    The global mobile mapping market research report includes an in-depth coverage of the industry with estimates and forecast revenue in USD respectively from 2013 to 2024, for the following segments.

    Mobile Mapping Market, By Component

    Hardware
    Imaging device
    Laser ranging and scanner device
    Positioning device
    Software
    Mapping data extraction
    Data processing
    Service
    Consulting
    Integration & maintenance
    Managed

    Mobile Mapping Market, By Application

    Road & railway survey
    GIS data collection
    Vehicle control & guidance
    Asset management

    Mobile Mapping Market, By End-User

    Agriculture
    BFSI
    Government & public sector
    Real estate & infrastructure
    Retail
    Mining
    Telecommunication

    Regions and Countries

    North America
    U.S.
    Canada
    Europe
    UK
    Germany
    France
    Spain
    Italy
    Asia Pacific
    ANZ
    China
    India
    Japan
    South Korea
    Latin America
    Brazil
    Mexico
    Argentina
    MEA
    GCC
    South Africa
    Israel

  • Volcanic GIS: Mapping and imaging the Kilauea eruption

    A number of geospatial companies played a key role in the government’s response to the Kilauea Volcano eruption. The volcano on the Big Island of Hawaii began erupting May 3, and while quiet for more than a week, it could resume erupting at any time.

    Mapping the flow. As a resident of Hawaii, Brennan O’Neill, Hawaiian branch manager of Frontier Precision, was in a unique position to offer support. Frontier Precision provided free access to technology and expertise to assist in mapping the lava flow.

    “I had to help out,” O’Neill said. “It was tearing at my soul. For a geologist, it’s even more powerful than that. The lava flow is like a living mass that has a mind of its own, creeping, glowing — an upside-down conveyor belt surging forward and burning everything in its path.”

    Through Frontier Precision, O’Neill offered high-tech mapping equipment, his own expertise, and the help of Nathan Stephenson, an applied geospatial engineer working in the company’s Denver office.

    “We used a combination of Trimble R10s and Trimble R8s to gather accurate data points on the ground,” Stephenson said.

    This thermal map shows the fissure system and lava flows as of 6 a.m. on Saturday, Aug. 11. The thermal map was constructed by stitching many overlapping oblique thermal images collected by a handheld thermal camera during a helicopter overflight of the flow field. The base is a copyrighted color satellite image (used with permission) provided by Digital Globe. (Map: USGS)
    This thermal map shows the fissure system and lava flows as of 6 a.m. on Saturday, Aug. 11. The thermal map was constructed by stitching many overlapping oblique thermal images collected by a handheld thermal camera during a helicopter overflight of the flow field. The base is a copyrighted color satellite image (used with permission) provided by Digital Globe. (Map: USGS)

    The mapping team flew UAS drones over the flow to gather visual imagery data, matched it to the ground reference points, stitched the photos together and draped it over county maps. The process was repeated as often as needed — daily, and sometimes even hourly — to show the speed and direction of the flow.

    Stephenson isn’t new to mapping lava flows. As a graduate student at the University of Hawaii – Hilo, he worked on collecting data on the Pahoa eruption in 2014, and he’s seen advances in technology in just a few years.

    “One thing we have now that we didn’t have in 2014 was a thermal radiometric camera that helps us map more accurately at night and enables us to capture large heat signatures.”

    The collected data helps Hawaii Civil Defense and other agencies keep the public informed and safe, and in the long term it also contributes to the store of scientific knowledge about eruptions and lava flow behavior.

    Lidar image of the Hawaii dataset showing the Kilauea Calderand the Halena'uma'u Crater and within it. (Image: Quantum Spatial)
    Lidar image of the Hawaii dataset showing the Kilauea Calderand the Halena’uma’u Crater and within it. (Image: Quantum Spatial)

    Airborne lidar insights. Another technology that aids in volcano response is lidar. High-resolution lidar surveys help first responders, scientists and government agencies monitor Kilauea conditions and predict future lava flows.

    Independent geospatial data firm Quantum Spatial Inc. (QSI) has conducted high-resolution lidar surveys of areas surrounding the Kilauea volcano eruption in Hawaii.

    The emergency response effort was part of the U.S. Geological Survey’s (USGS) Rapid Response Imagery Products (RRIP) in support of the Kilauea’s 2018 East Rift Zone – Remote Sensing Acquisition Requirement.

    The USGS Hawaiian Volcano Observatory (HVO), along with emergency responders, government agencies and academics, will use the data to better understand the conditions and characteristics of the volcano, and help planners model potential lava flows, which may better predict and respond to future flows and enhance safety of residents.

    The QSI team, which included GEO1 and Windward Aviation, deployed within days to acquire high-resolution lidar at point densities averaging from 40 to 80 ppsm, with up to 150 ppsm in select areas and 100-mp digital imagery using a Riegl dual VUX-1 LR sensor pod equipped with ABGPS/IMU mounted on a Hughes 500D helicopter.

    The project required 11 missions over the course of six days, operating at times as low as 500 feet above the ground and above active flows and nearby erupting calderas. With a need for a quick turn around, QSI deployed an analyst with the flight crew to post process each mission within hours of collection.

    The data was uploaded to the Geospatial Repository and Data Management System (GRiD) interface, developed by the U.S. Army Corps of Engineers (USACE), where additional data products have been developed and provided to the response team that includes FEMA, Hawaii’s Emergency Operations Center (EOC) and the Hawaii County Civil Defense.

    After data collection, QSI measured topographic shifts during the processing by comparing new data with a 2011 lidar collection from the same area. Survey specialists and USGS experts confirmed within hours of processing QSI’s lidar data that areas within the site had shifted up to 1.5 meters east, 2 meters to the north and 1 meter in elevation.

    USGS scientists will continue to examine the new topographic data to better understand the nature of these shifts, and integrate it into lava flow models for more accurate predictive modeling.

    The eruption in action. Using small unmanned aerial systems (sUAS) together with air-quality sensors, advanced imaging tools and Esri’s spatial analytics and mapping, a team from the Center for Robot-Assisted Search and Rescue (CRASAR) provided real-time aerial views of the eruption.

    The five volunteers armed with drones, advanced sensor systems and GIS technologies joined the response effort May 14-19 at Kilauea Volcano Lower East Rift Zone to assist in tracking and predicting the ongoing volcanic eruption. The team supplemented the University of Hawaii Hilo’s (UHH) sUAS capabilities, allowing UHH sUAS operators to focus on geographical and volcanology.

    The CRASAR team identified a new fissure not visible from the ground, projected the lava flow rate during the night when manned helicopters were not allowed to fly, and provided ongoing data collection from new thermal sensors technology.

    After the project, CRASAR published lessons learned on its blog:

    • Night flights of UAVs are very effective.
    • Rotorcraft UAVs can effectively sample gas.
    • Rotorcraft UAVs with thermal sensors are very effective.
    • Rotorcraft UAVs provide a quick look at lava flow rates.
    • Plumes will interfere with photogrammetric mapping.
    • Hanger 360 (software) rapidly produced panoramas.

    During the six-day Leilani deployment, the CRASAR team flew 44 sUAS flights, including 16 at night, using DJI 200, 210, Inspire, and Mavic Pro drones. Esri’s Drone2Map for ArcGIS together with Hangar’s Enterprise Platform for 360-degree imaging enabled rapid 360-imaging for situational awareness.

    DJI’s new XT2 thermal sensor provided unprecedented drone-based air-quality monitoring. Video and data were shared with local first responders using FirstNet, the first high-speed, nationwide wireless broadband network dedicated to public safety.

    The CRASAR response marks the first known use of sUAS for emergency response to a volcanic eruption and first known use of sUAS for sampling air quality.

    The GIS mapping and imaging technologies responders used on the scene at Kilauea Volcano Lower East Rift Zone are available here.

  • Quantum Spatial lidar surveys provide volcano eruption insights

    Looking southwest towards Leilani Estates with Fissure 8 erupting in the background. (Image: Ron Chapple/GEO 1)
    Looking southwest towards Leilani Estates with Fissure 8 erupting in the background. (Image: Ron Chapple/GEO 1)

    High-resolution lidar surveys help first responders, scientists and government agencies monitor Kilauea conditions and predict future lava flows.

    Independent geospatial data firm Quantum Spatial Inc. (QSI) has conducted high-resolution lidar surveys of areas surrounding the Kilauea volcano eruption in Hawaii.

    The emergency response effort was part of the U.S. Geological Survey’s (USGS) Rapid Response Imagery Products (RRIP) in support of the Kilauea’s 2018 East Rift Zone – Remote Sensing Acquisition Requirement.

    The USGS Hawaiian Volcano Observatory (HVO), along with emergency responders, government agencies and academics, will use the data to better understand the conditions and characteristics of the Kilauea volcano, which has been continually erupting since May 3.

    Data also will assist planners in modeling potential lava flows, which may better predict and respond to future flows and enhance safety of residents.

    The USGS National Geospatial Program (NGP) selected QSI to perform the first of two planned surveys over the active volcanic area. The QSI team, which included GEO1 and Windward Aviation, deployed within days to acquire high-resolution lidar at point densities averaging from 40 to 80 ppsm, with up to 150 ppsm in select areas and 100-mp digital imagery using a Riegl dual VUX-1 LR sensor pod equipped with ABGPS/IMU mounted on a Hughes 500D helicopter.

    Five distinct locations, covering an area of 57 square miles, were targeted:

    • Kīlauea Summit Caldera
    • Pu’u O’o Crater and flow
    • Chain of Craters Road / Kaoe
    • Puna Geothermal Venture (PGV)
    • Western Leilani Estates lava field.

    The project required 11 missions over the course of six days, operating at times as low as 500 feet above the ground and above active flows and nearby erupting calderas. With a need for a quick turn around, QSI deployed an analyst with the flight crew to post process each mission within hours of collection.

    The data was uploaded to the Geospatial Repository and Data Management System (GRiD) interface, developed by the U.S. Army Corps of Engineers (USACE), where additional data products have been developed and provided to the response team that includes FEMA, Hawaii’s Emergency Operations Center (EOC) and the Hawaii County Civil Defense.

    After data collection, QSI measured topographic shifts during the processing by comparing new data with a 2011 lidar collection from the same area. Survey specialists and USGS experts confirmed within hours of processing QSI’s lidar data that areas within the site had shifted up to 1.5 meters east, 2 meters to the north and 1 meter in elevation.

    USGS scientists will continue to examine the new topographic data to better understand the nature of these shifts, and integrate it into lava flow models for more accurate predictive modeling.

    “Airborne lidar and imagery remote sensing surveys are invaluable tools for understanding the effects of active volcanic eruptions, which change the topography as fissures emerge and lava flows extend to the ocean,” said Michael Shillenn, vice president at QSI. “We were honored to work with the USGS and others on this critical project. We believe that data and analysis provided by the QSI team will provide insights into future scenarios, enabling emergency responders to protect the surrounding community.”

  • Dewberry to update lidar for Puerto Rico and US Virgin Islands after hurricane

    The U.S. Geological Survey (USGS) has selected Dewberry, a privately held professional services firm, to collect and process Quality Level 1 topographic lidar data of Puerto Rico, including the islands of Culebra, Vieques and Isla de Mona; and the U.S. Virgin Islands of St. Croix, St. John and St. Thomas.

    The new data will be used to identify the impact of Category 5 Hurricane Maria, which struck the territories in September 2017.

    Digital elevation model of El Yunque National Forest produced from 2016 topographic lidar data. (Image: Dewberry)

    The project will be completed under Dewberry’s Geospatial Product and Services Contract with USGS to support the agency’s 3D Elevation Program.

    Dewberry has been performing mapping, mitigation planning and sea-level rise studies in Puerto Rico for more than 10 years, primarily serving the Federal Emergency Management Agency (FEMA).

    In a similar effort, the firm recently collected and processed more than 3,400 square miles of topographic and bathymetric lidar data for USGS, the National Oceanic and Atmospheric Administration and the Commonwealth of Puerto Rico.

    For that project, the data were collected prior to Hurricane Maria’s landfall, and the new data will be assessed in comparison to that dataset to evaluate the storm’s impact. Lidar data have not been collected for the U.S. Virgin Islands in more than 10 years.

    Digital Elevation Model of the Guajataca Lake Dam produced from 2016 topographic lidar data. (Image: Dewberry)

    The new lidar data will be collected, processed and delivered by the spring of 2019. Dewberry will perform all ground surveys and its geospatial team will complete the processing and creation of digital elevation models and other ancillary products. The firm’s subconsultant, Leading Edge Geomatics, will perform the data acquisition using two Riegl VQ1560i sensors.

    “The pre-storm data we had collected and processed under our prior task order was instrumental in assisting FEMA, its partners and the local Puerto Rican government in planning and conducting its post-Maria disaster recovery work,” said Amar Nayegandhi, CP, CMS, GISP, vice president of geospatial and technology services for Dewberry. “The new data are being collected at a higher density to also support the infrastructure community and will show how the storm has altered the terrain.”