MAPPS honored members with the 2018 Geospatial Products and Services Excellence Awards as part of their 12th annual awards banquet at the group’s winter meeting in Denver in January.
The Geospatial Excellence Awards are presented to regular and associate member firms whose entries exemplify the professionalism, value, integrity and achievement of the firm’s staff as demonstrated over the previous year, according to MAPPS. “A distinguished and impartial panel of three judges evaluated the submitted projects from eight categories: airborne and satellite data acquisition; photogrammetry/elevation data generation; remote sensing; GIS/IT; surveying/field data collection; small projects; technology innovation; and licensed data products,” the association noted. A winner was selected for each category with submissions.
This year included a new “Member’s Choice” award. In addition to the various categories, an overall Project of the Year Award was presented to Towill Inc., for its entry in the category “surveying/field data collection.”
Geospatial Project of the Year and The Geospatial Excellence Award for Surveying/Field Data Collection –
The San Francisco Public Utilities Commission (SFPUC) took a proactive move to plan five water pipeline improvement projects. One project focused on the San Andreas Pipeline No. 2 (SAPL2), part of the Hetch Hetchy regional drinking water system, built in 1929 and owned and operated by the city and county of San Francisco.
The SFPUC investigated whether a sliplining method could be used to save considerable time, money, road closures, and environmental impacts by inserting a new 48-inch outside-diameter pipeline into the existing 54-inch pipeline rather than excavating and replacing the entire 1,800-foot segment. With only outdated drawings and incomplete information on the dimensions and location of the pipeline, SFPUC needed to determine the exact dimensions of the pipeline’s interior and to locate any horizontal and vertical bends.
Towill Inc., was brought on by the design firm, Kennedy/Jenks Consultants, to collect and analyze this information using integrated surveying and static terrestrial laser scanning (STLS) technologies.
Towill created a very dense point cloud to serve as an as-built of the conditions inside of the pipe. From that, Towill was able to capture the pipeline’s horizontal and vertical alignments, ovality and roundness, and unknown horizontal and vertical deflections. Towill then modeled various pipe diameters and lengths, simulating the installation of the new pipe.
One of the SAPL2 project’s major goals was to avoid closing and excavating two major roads. If the sliplining technique had not been possible, the project would have required a very traditional excavation, removal, and replacement of the pipeline, which would have been costly and inconvenient to the public. The survey helped confirm that the proposed sliplining technique could be accomplished effectively without road closures.
Airborne and Satellite Data Acquisition –
Quantum Spatial Inc.
In the fall of 2017, the U.S. Geological Survey (USGS) contracted Quantum Spatial Inc., (QSI) to collect and process topo-bathymetric LiDAR, natural color imagery and hyperspectral imagery for a 54-mile stretch of the Kootenai River in northern Idaho. Modeling the bathymetry of rivers is particularly challenging and requires unique technologies to model submerged terrain with the same accuracy and resolution as can be achieved for terrestrial landscapes. Historically, boat-mounted sonar surveys have provided inland bathymetry data, but this technology is fraught with shortcomings for shallow waters. New technologies such as topo-bathymetric LiDAR combined with hyperspectral imagery present an opportunity to analyze and model inland shallow water floodplains and riverine environments like never before, providing valuable new insights into water resource management and aquatic habitats.
The Kootenai River project has contributed in significant ways to the geospatial field, as the larger lessons learned from the project have greatly redefined the marketplace for LiDAR mapping. It has led by example in presenting the capacity for topo-bathymetric LiDAR to ‘fill in the gaps’ in topographic modeling for underwater landscapes.
By contributing to USGS’ Inland Bathymetry Research Project, the Kootenai River project has fed valuable information into the 3D Nation Requirements and Benefits Study, led by the USGS and NOAA.
Photogrammetry/Elevation Data Generation –
In 2008, the Alaska Statewide Mapping Initiative (SDMI) contracted with Dewberry to prepare the Alaska DEM Whitepaper in order to identify mapping problems and propose solutions. Dewberry determined that Alaska’s surveying and mapping challenges were extremely complex because: (1) geodetic control was almost non-existent; (2) cloud-free satellite imagery was not available — even after many years of trying; and (3) the DEM from the National Elevation Dataset (NED) was so poor that satellite imagery didn’t fit the DEM as it should, causing maps to appear as though rivers flowed over mountains rather than through the valleys.
Between 2010 and 2018, Dewberry received 26 separate IFSAR task orders for small areas that were not contiguous and would have cost stakeholders much more to acquire later to fill in the gaps. To minimize costs, Fugro over-collected ~71 percent of its assigned area on speculation, while Intermap over-collected ~20 percent of its assigned area on speculation. Additionally, Dewberry hired JOA Surveys on speculation to acquire QA/QC checkpoints to have them ready when IFSAR datasets were funded. Without these speculative acquisitions to reduce overall acquisition costs, this project would easily have cost over $90 million. In 2019, the entire state is expected to be completed for ~$68.5 million. (This is also $8.8 million below the original 2009 estimate.) Hydro-enforced deliverables exceed product specifications and the Dewberry team will complete this project well below the estimated budget because of team-wide initiatives to minimize costs.
Remote Sensing –
Merrick & Company
In 2016, the Southern Nevada Water Authority (SNWA) retained Merrick & Company to collect LiDAR (elevation point clouds) over an approximate 1,162-square-mile area of the Las Vegas Valley. Merrick’s role was to plan, manage, and perform the airborne acquisition of LiDAR to support the remote sensing objectives of SNWA and its funding partners.
Merrick used its Optech Galaxy LiDAR sensor to collect high resolution elevations that met USGS Quality Level 1 and 2 (QL1 and QL2) specifications. It processed the LiDAR point cloud to facilitate SNWA’s remote sensing vegetation analysis.
After a rigid and unique post-process, the LiDAR derived digital elevation models and hydro-enforced breaklines were integrated by the SNWA into its analysis to identify the mass/volume of various types of vegetation. SNWA refined the LiDAR model to further classify vegetation and trees by height categories including: Class 5: High – 7+ feet, Class 4: Medium - 2- to 7-feet,, and Class 3: Low – 0.3- to 2-feet.
Because Las Vegas has very unique man-made features within its many themed hotels and resorts (Sphynx, rollercoasters, Eiffel Tower, pyramid, etc.), special attention was needed during the filtering process that classifies elevation points into the USGS LAS attribute levels.
In addition, following rigorous testing, the USGS approved the SNWA LiDAR products for inclusion in the National Elevation Dataset.
The Geospatial Excellence Award for GIS/IT –
Quantum Spatial, Inc.
The mission of Bureau of Ocean Energy Management’s Marine Minerals Program (MMP) is to facilitate access to and manage the nation’s Outer Continental Shelf (OCS) non-energy marine minerals, particularly sand and gravel, through environmentally responsible stewardship of resources, prudent assessments of exploration and leasing activities, coordination with governmental partners, engagement of stakeholders, strategic planning, and mission-focused scientific research to improve decision-making and risk management. To enable access and dissemination of derived geological and geophysical data and support regional coastal resilience planning efforts, BOEM contracted with Quantum Spatial Inc., to develop a GIS that would serve as a central authoritative system of record for all available ocean sand and minerals geospatial data and non-geospatial documentation — the Marine Minerals Information System (MMIS).
Initiated in 2014, the project’s overarching goals were two-fold: 1) to coalesce all available data into an enterprise GIS (eGIS) with a standardized data model, and 2) to develop tools for viewing, analysis, and collaboration. After four years (phases) of work, QSI has completed the first goal, with associated deliverable products accepted by BOEM in April 2018.
QSI identified, collected, organized, evaluated and incorporated 150,000 digital data assets as well as non-digital documents with associated metadata into the GIS. This volume of data represented 30+ years of records collected and/or catalogued by a diversity of agencies and entities.
The Geospatial Excellence Award for Technology Innovation –
LiDAR is a standard tool in the industry. As companies employing the technology have continued to grow, their needs have been rapidly changing and evolving, and the demands on LiDAR sensors and systems have been increasing accordingly.
Riegl’s VMX-2HA high speed, high performance dual scanner mobile mapping system is comprised of two Riegl VUX-1HA high accuracy LiDAR sensors and a high-performance INS/GNSS unit, housed in an aerodynamically-shaped protective cover, which provides an accurate and long-term stable system calibration. The alignment and placement of the two VUX-1HA scanners maintains a simultaneous forward/backward look to reduce shadows within the scan.
A camera interface for up to nine optional cameras enables complementation of the LiDAR data with precisely geo-referenced images. These multiple high-resolution Riegl cameras allow for unique capture angles and a high degree of details in the images. The VMX-2HA mobile mapping system provides interface and SYNC for up to nine external devices, and allows for a flexible combination of different camera configurations such as high-sensitivity 5MP, 9MP, and 12MP RIEGL cameras, FLIR Ladybug 5+, and DSLR cameras such as Nikon D810 or Sony Alpha. The modular setup of the system allows the camera configuration to be changed or upgraded at any time.
The VMX-CU control unit, equipped with a high performance third generation Intel Core i7 processor, precisely controls management of power, data acquisition, and operation of the laser scanners, INS/GNSS sensors and the optional cameras.
The Geospatial Excellence Member’s Choice Award –
In continuing support of NOAA’s nautical charting mission, TerraSond was tasked in 2017 with performing a hydrographic survey in Southwest Alaska covering 271 NM2 (930 KM2) of seafloor.
The project area intersected approximately 108 NM of rocky coastline, over which verification and identification of potentially navigationally significant shoreline features such as rocks, reefs and ledges were required. Instead of the traditional investigation technique of visiting individual features with a skiff deployed from a larger vessel, TerraSond utilized unmanned aerial systems (UAS) to accomplish the investigations, achieving marked improvements to personnel safety, while simultaneously providing a more accurate and comprehensive product and reducing cost.
A 105-foot vessel (RV Q105) was mobilized to the site and acquired multibeam data around the clock. An 18-foot autonomous surface vessel (ASV) was also deployed and collected multibeam data concurrently, focusing on areas too shallow, dangerous or otherwise inaccessible for the larger vessel. Over 4,800 linear NM (8,890 km) of multibeam data was collected. Preliminary data processing and QC was completed onboard in near real-time.
For more information on the MAPPS Geospatial Excellence Awards, go to www.mapps.org.
This project was the first U.S. nautical charting project to utilize UAS for shoreline feature investigation. As a first of its kind, it was necessary to develop purpose-built methodology on the project to optimize UAS altitude, speed, flight path overlap, and camera settings to achieve raw data sets of sufficient photo density from which SfM processing techniques could be used to produce suitable results.