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Publications

The National Innovation Center partnership development and science support has generated numerous publications over the last decade.

UAS Research

We support various projects using UAS to assess and monitor stream velocity, active volcanic lava flows, snow depth, and soil moisture and to characterize wildfire and dust as well as volcanic and methane gas emissions. 

Next Generation Wildlife Tracking

Working with our partners to develop next generation wildlife tracking and monitoring technologies to better characterize behavior and movement as more rapid information delivery. 

Next Generation Streamgaging

Working with technology partners who built EnviSense, an ultra-low power environmental sensing system, the USGS has deployed over a dozen systems across two locations in Northern California for hydrological monitoring applications. 

Filter Total Items: 31

Mapping river flow from thermal images in approximately real time: Proof of concept on the Sacramento River, California, USA Mapping river flow from thermal images in approximately real time: Proof of concept on the Sacramento River, California, USA

Image velocimetry has become an effective method of mapping flow conditions in rivers, but this analysis is typically performed in a post-processing mode after data collection is complete. In this study, we evaluated the potential to infer flow velocities in approximately real time as thermal images are being acquired from an uncrewed aircraft system (UAS). The sensitivity of thermal...
Authors
Carl J. Legleiter, Paul J. Kinzel, Michael Dille, Massimo Vespignani, Uland Wong, Isaac E Anderson, Elizabeth Hyde, Christopher L. Gazoorian, Jennifer Marie Cramer
By
Water Resources Mission Area, National Innovation Center, New York Water Science Center, Woods Hole Coastal and Marine Science Center

A framework to facilitate development and testing of image-based river velocimetry algorithms A framework to facilitate development and testing of image-based river velocimetry algorithms

Image-based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER)...
Authors
Carl J. Legleiter, Paul J. Kinzel
By
Water Resources Mission Area, National Innovation Center

Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity

Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500...
Authors
Daniel Mark Griffith, Kristin B. Byrd, Lee Anderegg, Elijah Allen, Demetrios Gatziolis, Dar A. Roberts, Rosie Yacoub, Ramakrishna Nemani
By
National Innovation Center, Western Geographic Science Center

Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time

Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data from across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and...
Authors
Daniel M. Griffith, Kristin B. Byrd, Nicole Chin Taylor, Elijah Allan, Liz Bittner, Bart O’Brien, V. Thomas Parker, Michael C Vasey, Ryan Pavlick, Ramakrishna R. Nemani
By
National Innovation Center, Western Geographic Science Center

From data to interpretable models: Machine learning for soil moisture forecasting From data to interpretable models: Machine learning for soil moisture forecasting

Soil moisture is critical to agricultural business, ecosystem health, and certain hydrologically driven natural disasters. Monitoring data, though, is prone to instrumental noise, wide ranging extrema, and nonstationary response to rainfall where ground conditions change. Furthermore, existing soil moisture models generally forecast poorly for time periods greater than a few hours. To...
Authors
Aniruddha Basak, Kevin M. Schmidt, Ole Mengshoel
By
Ecosystems Mission Area, National Cooperative Geologic Mapping Program, Geology, Minerals, Energy, and Geophysics Science Center, National Innovation Center

Achieving sub-nanoTesla precision in multirotor UAV aeromagnetic surveys Achieving sub-nanoTesla precision in multirotor UAV aeromagnetic surveys

An uncrewed aerial vehicle (UAV) multirotor aeromagnetic system using a 5-m sling load for a magnetic sensor system is described and characterized. Four magnetic surveys with identical flight lines were completed, at two nominal altitudes of 25 and 40 m. The surveys were used to assess the repeatability of data collected with the described UAV aeromagnetic system, and comparison with a...
Authors
Geoffrey Phelps, Robert E. Bracken, John Spritzer, David S. White
By
Geology, Minerals, Energy, and Geophysics Science Center, National Innovation Center

In situ enhancement and isotopic labeling of biogenic coalbed methane In situ enhancement and isotopic labeling of biogenic coalbed methane

Subsurface microbial (biogenic) methane production is an important part of the global carbon cycle that has resulted in natural gas accumulations in many coal beds worldwide. Laboratory studies suggest that complex carbon-containing nutrients (e.g., yeast or algae extract) can stimulate methane production, yet the effectiveness of these nutrients within coal beds is unknown. Here, we use...
Authors
Elliott Barnhart, Leslie F. Ruppert, Randy Heibert, Heidi J. Smith, Hannah Schweitzer, Arthur Clark, Edwin Weeks, William H. Orem, Matthew S. Varonka, George A. Platt, Jenna L. Shelton, Katherine J Davis, Robert Hyatt, Jennifer C. McIntosh, Kilian Ashley, Shuhei Ono, Anna M. Martini, Keith Hackley, Robin Gerlach, Lee Spangler, Adrienne Phillips, Mark Barry, Alfred B. Cunningham, Matthew W. Fields
By
Water Resources Mission Area, Energy Resources Program, Geology, Energy & Minerals Science Center, National Innovation Center, Wyoming-Montana Water Science Center

Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland

Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Observatory Ecological Network (NEON) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high-resolution...
Authors
Stephanie Pau, Jesse Nippert, Ryan Slapikas, Daniel Mark Griffith, Seton Bachle, Brent Helliker, Rory O’Connor, William J. Riley, Christopher J. Still, Marissa Zaricor
By
National Innovation Center, Western Geographic Science Center

Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy

This work investigates bituminite (amorphous sedimentary organic matter) in Upper Jurassic Kimmeridge Clay source rock via confocal laser scanning microscopy (CLSM) and atomic force microscopy (AFM). These petrographic tools were used to provide better understanding of the nature of bituminite, which has been historically difficult to identify and differentiate from similar organic...
Authors
Paul C. Hackley, Jolanta Kus, Joao Graciano Mendonca Filho, Andrew D. Czaja, Angeles G. Borrego, Dragana Životić, Brett J. Valentine, Javin J. Hatcherian
By
Energy Resources Program, Geology, Energy & Minerals Science Center, National Innovation Center

Representing plant diversity in land models: An evolutionary approach to make ‘Functional Types’ more functional Representing plant diversity in land models: An evolutionary approach to make ‘Functional Types’ more functional

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land...
Authors
Leander D.L. Anderegg, Daniel Mark Griffith, Jeannine Cavender-Bares, William J. Riley, Joseph A. Berry, Todd E. Dawson, Christopher J. Still
By
National Innovation Center, Western Geographic Science Center

Experiences in LP-IoT: EnviSense deployment of remotely reprogrammable environmental sensors Experiences in LP-IoT: EnviSense deployment of remotely reprogrammable environmental sensors

The advent of Low Power Wide Area Networks (LPWAN) has improved the feasibility of wireless sensor networks for environmental sensing across wide areas. We have built EnviSense, an ultra-low power environmental sensing system, and deployed over a dozen of them across two locations in Northern California for hydrological monitoring applications with the U.S. Geological Survey (USGS). This...
Authors
Reese Grimsley, Mathieu D. Marineau, Robert A. Iannucci
By
Water Resources Mission Area, California Water Science Center, National Innovation Center

Activity-based, genome-resolved metagenomics uncovers key populations and pathways involved in subsurface conversions of coal to methane Activity-based, genome-resolved metagenomics uncovers key populations and pathways involved in subsurface conversions of coal to methane

Microbial metabolisms and interactions that facilitate subsurface conversions of recalcitrant carbon to methane are poorly understood. We deployed an in situ enrichment device in a subsurface coal seam in the Powder River Basin (PRB), USA, and used BONCAT-FACS-Metagenomics to identify translationally active populations involved in methane generation from a variety of coal-derived...
Authors
Luke J. McKay, Heidi J. Smith, Elliott Barnhart, Hannah S. Schweitzer, Rex R. Malmstrom, Danielle Goudeau, Matthew W. Fields
By
Water Resources Mission Area, National Innovation Center, Wyoming-Montana Water Science Center
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