Home

NUSO 2021 Research Missions


Collecting UAS Derived Lidar for Slackwater Harbor Assessment

Dardanelle, Arkansas
Natural-color topographic lidar point cloud data of the proposed slack water harbor location of the Arkansas River.
Natural-color topographic lidar point cloud data of the proposed slack water harbor location of the Arkansas River.

USGS NUSO, USGS Central Midwest Water Science Center, and U.S. Army Corps of Engineers, Little Rock District conducted a lidar topographic and bathymetry survey for the future development of a slack water harbor along the Arkansas River near Dardanelle, Arkansas. Evaluation of shoreline stability and the adjacent development of a new harbor along the Arkansas River navigation system at River Mile 202.6 is essential in establishing a baseline for potential impacts and future sediment monitoring. USGS used a combination of multi- and single-beam sonar and high-resolution aerial lidar to provide data for future monitoring, maintenance of the river shoreline, and floodplain management.

USGS collected topographic data in a lidar point cloud (LPC) format using an unmanned aircraft system (UAS) with a Yellowscan Vx20-100 lidar payload. This system consists of a lidar scanner and an integrated inertial navigation unit. The UAS followed two perpendicular transects orientations (north-south and east-west) on separate flights while collecting the LPC. The point cloud data was corrected using a post-processed kinematic (PPK) solution with a Trimble R8s base station. A field team surveyed ground control points using Propeller AeroPoint smart targets, PPK corrected to a nearby continuously operated reference station tower. The features of the LPC were attributed to the American Society for Photogrammetry and Remote Sensing point classification standards. The LPC was colorized from a UAS-collected natural-color orthoimage using a Ricoh GRII camera.

USGS Data Release: Use of High-Resolution Topo-Bathymetry to Assess Shoreline Topography and Future Development of a Slackwater Harbor near Dardanelle, Arkansas, October 2021

Study Points of Contact:
Matt A. Burgess, Ph.D., UAS Operations / Geospatial Analyst
National Uncrewed Systems Office, Geosciences and Environmental Change Science Center
maburgess@usgs.gov

Richard J. Huizinga, Hydrologist
Central Midwest Water Science Center
huizinga@usgs.gov

Radiometric Calibration Comparisons

Table Mountain outside of Boulder, Colorado
UPO researchers Joe Adams and Matt Burgess work with the MicaSense Dual sensor
NUSO researchers Joe Adams and Matt Burgess work with the MicaSense Dual sensor

NEON is a national-scale monitoring initiative funded by the National Science Foundation and operated by Battelle. To better understand how U.S. ecosystems are changing, NEON has been designed to collect long-term open access ecological data at diverse sites across the country for 30 years (https://www.neonscience.org/). This includes airborne remote sensing surveys conducted at a subset of sites each year using the NEON Airborne Observation Platform (AOP), Twin Otter aircrafts carrying payloads consisting of three sensor types: high-resolution true color digital camera, imaging spectrometer to capture hyperspectral data with over 400 spectral bands, and discrete and full-waveform lidar systems (https://www.neonscience.org/data-collection/airborne-remote-sensing). NEON performs a series calibration flights before and after each flight season, which typically stretches between March and September to capture the peak greenness of vegetation.

In October of 2021, the NUSO joined the NEON AOP team to collect coincident UAS data for comparison with the NEON airborne remote sensing data at the NOAA Table Mountain site just north of Boulder, CO. In between AOP flight lines, NUSO flew two UAS to collect multispectral and hyperspectral data using MicaSense Dual and Resonon Pika-L sensors, respectively. To verify the accuracy of the AOP spectral data, NEON deploys calibration tarps with 3% and 48% reflectance to be mapped during these flights (https://www.neonscience.org/data-collection/imaging-spectrometer). NEON and NUSO scientists collected handheld spectral radiance and reflectance measurements of these tarps, the road, and vegetation using ASD FieldSpec spectroradiometer instruments to calibrate/validate the imagery.


Spectroradiometer Testing and Multispectral Mapping of Invasive Coastal Grasses

Cape Cod, Massachusetts
Using RTK GPS to survey field measurements for the white quadrat and make notes of vegetation species and height
Using RTK GPS to survey field measurements for the white quadrat and make notes of vegetation species and height

A UAS mission was conducted to collect multispectral imagery within a four-hour time window of field-based spectral measurements at the Sage Lot marsh on Cape Cod, MA. This site includes an invasive grass species (Phragmites) which USGS scientists aim to detect in coastal environments. There is evidence for invasives as a result of natural hazards. These flights also kept USGS pilots proficient and prepared to fly during emergencies. The AIM team conducted the UAS flight with a 3DR Solo quadcopter carrying a MicaSense RedEdge 5-band multispectral camera. NUSO and AIM researchers operated field spectrometers to collect spectral reflectance measurements at within a four-hour window of the UAS overflight. Two handheld spectroradiometers were used to collect data for comparison: the industry standard (ASD FieldSpec 4) and a potential cost-saving alternative (Ocean Insight HDX).

Upon completion of this field work, NUSO and AIM researchers are producing two deliverables: (1) a report that quantitatively and qualitatively compares these two spectrometer instruments based on laboratory- and field- based measurements, and (2) a land cover classification study led by Alexandra Evans (USGS and Woods Hole Oceanographic Institute) to assess the feasibility of mapping the invasive Phragmites grass using multispectral UAS imagery and field-based reflectance data.

Jennifer Cramer (USGS Woods Hole) calibrates the Ocean Insight HDX spectroradiometer using a white reference panel on grass
Jennifer Cramer (Woods Hole) calibrates the Ocean Insight HDX spectroradiometer using a white reference panel on grass
Jennifer Cramer calibrates the Ocean Insight HDX and collects reflectance spectra of beach sand
Jennifer Cramer calibrates the Ocean Insight HDX spectroradiometer and collects reflectance spectra of beach sand
Victoria Scholl (NUSO) with ASD FieldSpec and Jennifer Cramer with Ocean Insight HDX collecting reflectance of asphalt
Study Points of Contact:
Victoria Scholl, Physical Scientist
USGS National Uncrewed Systems Office
vscholl@usgs.gov

Jennifer Cramer, Geographer
USGS Woods Hole Coastal and Marine Science Center
jcramer@usgs.gov

Alexandra Evans, Postdoc Investigator
Woods Hole Oceanographic Institution
alexandra.evans@whoi.edu

Photogrammetric Data Collection Techniques for 3D Modeling of a Vertical Canyon Feature

Cimarron Canyon in New Mexico
Animation of part of the 3D Textured Model of the Cimarron Canyon

The Cimarron Canyon, NM project aims to safely allow USGS Geologists to measure stratigraphic layers on vertical rock faces in areas inaccessible by traditional on-foot surveys. To obtain this, the NUSO deployed a field team to generate a 3D model acquired using photogrammetric collection techniques from a UAS. The outcrops exposed along Cimarron Canyon are of the Paleocene Poison Canyon Formation, a geological unit that represents an uplift of the adjacent Sangre de Cristo Mountains. This area contains a complex geologic history of sedimentary layering of ancient river deposits. The high-resolution geologic mapping of Cimarron Canyon is currently ongoing by USGS Geologists.

Due to the complex nature of mapping vertical faces, the NUSO approached this photogrammetric data collection using a few unique techniques. The overlapping photos were collected using a Sony A7r camera with a locked focus using a 14mm wide-angle lens. The mapping payload consists of a stabilized gimbal with vibration dampening. The gimbal also allows the team to collect a complex series of images (with ideal geometry) from various angles around the outcrops. The gimbal stabilization allowed scientists to push smaller lens apertures, achieving a sharply focused set of overlapping images covering a considerable depth-of-field.

Theresa Schwartz, Amy Gilmer and Victoria Scholl (NUSO) hiking into the study site to place ground targets and scale bars
Theresa Schwartz, Amy Gilmer and Victoria Scholl (NUSO) hiking into the study site to place ground targets and scale bars
Aeropoint survey target deployed in the field to collect GPS data to help georeference UAS collected imagery
Study Point of Contact:
Theresa M. Schwartz, Research Geologist
USGS Geosciences and Environmental Change Science Center
tmschwartz@usgs.gov

Particle Sampling at Grassland Burning

Konza Prairie Biological Station (KPBS), Manhattan, Kansas
Grassland burn on the Flint Hills grasslands of Kansas.
Grassland burn on the Flint Hills grasslands of Kansas

U.S. Environmental Protection Agency (EPA) researcher Brian Gullett and his team are developing the Kolibri system, an air emission sampler instrument for use on an uncrewed aircraft system (UAS). In spring and fall of 2021, aerial, ground, and remote sensors were deployed during annual grassland burns at Konza Prairie Biological Station in the Flint Hills grasslands of Kansas to study the seasonal effects on smoke emissions. Joe Adams of USGS NUSO flew a UAS into the smoke column to sample smoke emissions using the Kolibri sensor.

UAS technology was well-suited for this mission since it could be easily positioned to hover at fixed flight altitudes within the smoke column. A helium balloon has been used to carry emission samplers such as the Kolibri in the past, but it required operators to be much closer to the fire and isn’t as straightforward to maintain a consistent sensor position within the shifting smoke column.

Learn more about the EPA Kolibri gas sampler: https://www.epa.gov/air-research/kolibri-system-enables-mobile-measurement-air-emissions-source-fact-sheet

Kolibri system mounted on a UAS
Kolibri system mounted on a UAS
Study Points of Contact:
Joe Adams, IT Specialist and Remote Pilot
USGS National Uncrewed Systems Office
jdadams@usgs.gov

Brian Gullet
Office of Research and Development, Environmental Protection Agency (EPA)
gullett.brian@epa.gov

Matthew Struckhoff, Ecologist
Columbia Environmental Research Center (CERC), U.S. Geological Survey
mstruckhoff@usgs.gov

Post-Wildfire Mapping of the East Troublesome Fire Burn Area

Granby, Colorado
Ricoh image of the burn scar taken 8 months after the start of the East Troublesome fire
Ricoh image of the burn scar taken 8 months after the start of the East Troublesome fire

This project aims to extend previous research into more complex vegetation/fuel types and within a post-catastrophic fire component. Three sample areas exhibiting various levels of fire intensity and fuel types were chosen within the 2020 East Troublesome burn perimeter located near Granby, Colorado. This study collected centimeter-level UAS multispectral (10-band) and natural color (RGB) imagery, processed using Structure-from-Motion (SfM) techniques. In addition to the imagery, centimeter-level lidar point clouds were acquired using UAS to estimate vegetation/fuels characteristics such as Canopy Cover, Canopy Height, Canopy Base Height, and Canopy Bulk Density.

The DOI OWF and the USGS desire to implement optimum data gathering and processing techniques to create best practices applying UAS technology into the DOI fuels and BAER programs. This project explores mapping processes that could display contact zones between fire intensity and burn severity. Fire Science is fundamental to understanding the causes, consequences, and benefits of wildfire and helps prevent and manage significant, catastrophic events.

Study Point of Contact:
Craig Thompson, Geospatial Data Analyst
DOI Office of Wildland Fire
craig_thompson@ios.doi.gov

Multiscale Spectroscopy of Intertidal Biofilm

San Francisco Bay, California
Joe Adams (NUSO) flying the M600 UAS
Joe Adams (NUSO) flying the M600 UAS

Intertidal biofilm (a slimy green layer of fungi and bacteria growing on top of mud) inhabits mudflats and is an essential component of shorebirds’ diets in San Francisco Bay, CA. Scientists at the USGS Western Ecological Research Center (WERC) are leading a project to study the quantity and composition of biofilm to inform wetland restoration and resulting habitat quality in this ecosystem.

NUSO joined researchers from the USGS WERC, the USGS Western Geographic Science Center, the USGS Spectroscopy Lab, and California State University Monterey Bay during a multi-scale hyperspectral remote sensing data collection in May 2021. The NUSO collected true-color, multispectral, and 4cm spatial resolution hyperspectral imagery using a Resonon Pika L Visible and near-infrared (VNIR) UAS camera. The UAS data provides an intermediate perspective between a ground-based field spectrometer, HySpex VNIR/Short-wave infrared (SWIR) imaging spectrometer mounted in a tripod (5 mm resolution), and the AVIRIS-NG airborne imaging spectrometer (4 m resolution).

This work is part of a larger WERC-led project on "Quantifying Drivers and Stressors of Intertidal Biofilm Resources at the Largest Tidal Wetland Restoration on the U.S. West Coast". Results will support managers' need to measure and visualize habitat quality for shorebirds and understand the influence of wetland restoration activities on biofilm resources (Kristin Byrd, USGS, DOI Highlight).

Study Points of Contact:
Joe Adams, IT Specialist and Remote Pilot
USGS National Uncrewed Systems Office
jdadams@usgs.gov

Susan de la Cruz, Research Wildlife Biologist
Western Ecological Research Center
sdelacruz@usgs.gov

Kristin Byrd, Research Physical Scientist
Western Geographic Science Center
kbyrd@usgs.gov

Raymond Kokaly, Spectroscopy Expert / Research Geophysicist
Geology, Geophysics, and Geochemistry Science Center
raymond@usgs.gov

Measuring Snow Depth with Lidar Data

Winter Park, Colorado
Image of an Aeropoint target deployed to collect GPS data for use in georeferencing
Image of an Aeropoint target deployed to collect GPS data for use in georeferencing

Approximately 2 billion people are expected to experience diminished water supplies because of seasonal snowpack decline this century. Over the last 50 years, particularly in some regions of the Western U.S., annual snowpack levels have declined and contributed to reduced streamflow levels; a trend supported by both models and in-situ observations. (USGS, From Snow to Flow, https://labs.waterdata.usgs.gov/visualizations/snow-to-flow/index.html#).

The USGS field team conducted three separate UAS data collects of the Winter Park, Colorado study site in September 2020, February 2021, and April 2021. The team flew a UAS equipped with a YellowScan VX20-100 lidar payload and surveyed ground-based targets for control and accuracy validation. A bare-earth digital elevation model and a snow-surface model (vegetation removed) was generated from the LPC data. Snow-depth maps were generated by subtracting the bare-earth terrain from the snow-surface model.

Study Point of Contact:
Graham A. Sexstone, PhD, Research Hydrologist
U.S. Geological Survey
sexstone@usgs.gov