News

ARL, UASPO, and AOC Collaboration Set to Perform Groundbreaking Field Study

Article/Figures Provided By: Bruce Baker and Ed Dumas

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On March 4-6, a team of nine NOAA scientists and engineers will gather at Avon Park, a U.S. Air Force (USAF) test range north of Sebring, Florida, to conduct first-of-a-kind tests on two small unmanned aircraft systems (sUAS).  The team consists of personnel from the Atmospheric Turbulence and Diffusion Division (ATDD) of NOAA’s Air Resources Laboratory, NOAA’s Unmanned Aircraft Systems Program Office (UASPO), and NOAA’s Office of Marine and Aviation Operations (OMAO) Aircraft Operations Center (AOC). The two sUASs being tested are recent acquisitions by ATDD. They include a Meteomatics Meteodrone Severe Storms Edition (SSE), which performs a vertical takeoff and landing (Figure 1), and a BlackSwift Technologies S2 fixed-wing aircraft similar in design to an airplane (Figure 2).

Since Avon Park is a USAF bombing range, which NOAA AOC has utilized to test both full-size and drone systems in the past, its airspace is not subject to the same Federal Aviation Administration (FAA) restrictions imposed on the national airspace system. The relaxed limitations will enable the team to fly both sUAS(s) to their respective maximum flight altitudes of approximately 5,000 feet above ground level (AGL). Knowing each aircraft’s upper limit and the point at which the operator will lose visual line of sight are key to performing safer, higher flights in the future. During testing, the team will also employ a ground-based radar system integrated with geospatial software in an attempt to determine its capability to mitigate potential threats to the sUAS(s) by targets within the airspace (e.g. traditional airplanes, other sUAS(s), hot air balloons, birds, etc.). Essentially, this exercise will enable the team to measure the same kind of parameters used by air traffic controllers.

Taking measurements of temperature, relative humidity, wind speed and pressure (collectively known as vertical profiles) with a copter and fixed-wing aircraft at such a high altitude represents a new frontier for atmospheric observations and is currently being done operationally in only a few locations around the globe. Historical data is sparse, so there has always been a large gap in knowing what is happening with the thermodynamics of the atmosphere (e.g. the transformations responsible for weather and climate).  Flying the UAS(s) to higher altitudes will enable scientists to design increasingly useful experiments for the boundary layer - the layer of the atmosphere where we live, where weather happens, and where ARL focuses its research.

NOAA’s AOC and UASPO are working toward obtaining Certificates of Authorization (COA) from the FAA to fly up to 10,000 ft.  Once COAs are obtained, both of ATDD’s sUAS(s) will be used for vertical profile sampling within the lowest 1 km of the atmosphere. Higher altitude, more frequent measurements will greatly enhance operational weather forecasting by the National Weather Service (NWS), as well as future field intensive studies of the boundary layer.  The upcoming field test is paving the way toward eventually having autonomous vertical profiles occurring any time of the day in different locations around the U.S. Currently, there are only about 100 NWS weather forecast offices in the U.S. that perform vertical profiling. They all utilize weather balloons for this twice-daily analysis. ATDD plans to start working with its closest forecast office, in Morristown, Tennessee, to determine how more frequent, more localized vertical profiles help to improved forecasting. ATDD is also continuing to assess new technologies and instrumentation capable of utilization by UAS(s).

High Accuracy Trace Gas Measurements from a Lightweight UAV

Article/Figure Provided By: Colm Sweeney and Pieter Tans

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Recently, numerous studies have contested the global impact of fugitive emissions from oil and gas operations on the methane budget.  Consequently, precise quantification of gas leaks is needed to better constrain the total methane burden from this source.  In the past, high precision insitu analyzers mounted in a research aircraft have been used to circle the suspected leak and quantify the plume.  While this is a robust method, it is costly, and missions cannot be deployed quickly.  Quick deployment is needed because leaks can be transient, variable, and a huge safety hazard.  A lightweight UAV is uniquely suited to both fly through a plume generated by a leak, and deploy quickly at little cost. However, the UAV platform is too small to carry the 70-pound analysis system used on a plane.

NOAA GMD has developed a unique sampling system, called the Active AirCore, in which a pump compresses air into a 100-meter long, small diameter tube at a constant flow rate. This long tube acts as an “atmospheric tape recorder” by storing the sample stream in the long tube. When the sample is analyzed, the data is a “play back” of the air the UAV flew through while in flight.  The sampler can be removed from the UAV, and immediately analyzed using an ultra-high precision trace gas analyzer like those used on aircraft.  This new sampling system provides the same level of accuracy as an analyzer mounted on a larger aircraft, but is light enough to be flown on a UAV.  Because the measurements are done in a van at the flight location, data analysis and quantification of the leak is near-real time.  This near-real-time analysis allows highly flammable natural gas leaks to be quickly identified and quantified providing information that will help evaluate the safety and potential economic losses at an individual oil and gas production site.

Development of an Autonomous Payload for Detection of Seals and Polar Bears on Sea Ice

Article Provided By: Erin Moreland (NMFS/AFSC/NMML)

Kenneth Vierra 0 2282 Article rating: 5.0

Polar bears and Ice-associated seals (bearded, ringed, spotted, and ribbon seals) are key components of Arctic marine ecosystems and are important resources for coastal Alaska Native communities. Reliable abundance estimates for ice seals are needed for developing sound management decisions under the Marine Mammal Protection Act and extinction risk assessments under the Endangered Species Act. The animals’ broad and patchy geographic distributions and rapidly changing sea ice habitat make these species particularly challenging to study.

An autonomous payload is required to integrate UAS into surveys of ice-associated mammals, in order to improve the efficiency and human safety in gathering essential data for NOAA stewardship. Moving from occupied aircraft to long-range UAS operations will require an efficient and “smart” payload to collect images needed for abundance estimation and habitat analysis while providing situational awareness to the pilot in command.

The Alaska Fisheries Science Center’s Marine Mammal Lab is developing a system that can run advanced machine learning algorithms on-board the aircraft to process multispectral imagery in real time, minimizing the collection of extraneous imagery that requires burdensome data storage, management, and processing.  Algorithm development is utilizing a neural network approach known as YOLO, which processes imagery at a rate of 60-100 frames per second.  Over 1.8 million color and thermal images are being used to train YOLO to detect animals on the sea ice and classify detections to species. This algorithm will be tested in-flight during April 2019.

Nighttime Fire Observations eXperiment (NightFOX)

ARTICLE/FIGURE PROVIDED BY: RUSHAN GAO AND TROY THORNBERRY (OAR/ESRL/CSD)

Kenneth Vierra 0 2350 Article rating: 4.0

Biomass burning produces major impacts on local and regional air quality which potentially plays an interactive role in climate change. A capable small, fixed-wing unmanned aircraft system (sUAS) can serve as an ideal platform for measurements of biomass burning emissions, plume distribution, fire extent and perimeter, and supporting meteorological data, especially at night when manned aircraft typically do not operate. The NOAA UASPO-funded Nighttime Fire Observations eXperiment (NightFOX) project aims to develop and deploy a sUAS observation system utilizing two modular and easily exchangeable payloads. One payload will provide in situ measurements of CO2, CO and fine- and coarse-mode aerosol size distributions in biomass burning plumes for characterization of fire combustion efficiency and emissions. A filter sampler will collect bulk aerosol samples for off-line composition analysis. The second payload will be flown over the fire to make remote sensing measurements of fire perimeter and fire radiative power using visible and short-, mid-, and long-wavelength IR observations. The multi-spectral remote sensing data will be used to provide sub-pixel information for comparison with satellite fire observations, and along with measured meteorological parameters, will be used to inform, test, and improve the WRF-SFIRE fire-atmosphere model.

Prototype in-situ and remote-sensing instrument payloads have been developed and are operational. Initial test flights with the payloads have recently been conducted. The performance of the prototype payloads has proven satisfactory and new versions are currently under development that will be used for the NIghtFOX operational deployment to study western wildfires next summer during the NOAA/NASA FIREX-AQ mission. Preliminary data processing algorithms for the remote sensing observations have been developed based on test flight results. A nighttime high-altitude FAA COA was obtained and a nighttime flight to an altitude of 2000 ft (0.61 km) was conducted on November 08, 2018, as a stepping stone to the 1 km design altitude for remote sensing operations.

NOAA Evaluates Using Drones for Lidar and Imagery in the National Estuarine Research

Article/Figures Provided By: Kirk Waters (OCM/NOS)

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Office for Coastal Management (OCM) scientists and their partners tested the utility of private sector drone technology to map marsh habitat in three estuarine research reserves. The team evaluated the quantitative spatial accuracy of both imagery and lidar products, as well as the qualitative gains for habitat mapping in multiple ecosystems.

Obtaining good solid earth elevation data is particularly difficult in dense marsh areas where it is also a critical component to understanding marsh vulnerability to sea level rise. The potential of lidar drone technology to penetrate to the ground with a smaller laser footprint and higher point density could provide a product that is currently unattainable from manned aircraft. Similarly, the detail in imagery that drone technology offers has the potential to provide finer delineations of habitat than the reserves have had from manned imagery. Contract spatial accuracy specifications were set at 10 cm root mean square error (RMSE) vertically for the lidar data and 15 cm RMSE horizontally for the imagery.

During the mission, Quantum Spatial and PrecisionHawk operated the drones, collected the data, and processed it. Staff from OCM and the three reserves (Jacques Cousteau, Grand Bay, and San Francisco Bay) collected independent ground-truth validation data and evaluated the drone deliverables. The two square mile area in San Francisco Bay reserve generated over 380,000 images and had lidar point density of over 400 points per square meter.

The two-year project (Fiscal Years 2016-2018) was funded by NOAA’s Office of Oceanic and Atmospheric Research. The project team includes partners from OCM, Jacque Cousteau NERR, Grand Bay NERR, San Francisco Bay NERR, Wells NERR, Quantum Spatial, and PrecisionHawk.

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