Search NASA⌕ Search

SEARCH · Search NASA

Results for “Imaging System Camera”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Developing a high-speed terahertz imaging system based on parametric upconversion imaging for penetrative sensing

Imaging using THz waves has been a promising option for penetrative measurements in environments that are opaque to visible wavelengths. However, available THz imaging systems have been limited to relatively low frame rates and cannot be applied to study fast dynamics. This work explores the use of upconversion imaging techniques based on nonlinear optics to enable wavelength-flexible high frame rate THz imaging. UpConversion Imaging (UCI) uses nonlinear conversion techniques to shift the THz wavelengths carrying a target image to shorter visible or near-IR wavelengths that can be detected by available high-speed cameras. This report describes the analysis methodology used to design a prototype high-rate THz UCI system and gives a detailed explanations of the design choices that were made. The design uses a high-rate pulse-burst laser system to pump both THz generation and THz upconversion detection, allowing for scaling to acquisition rates in excess of 10 kHz. The design of the prototype system described in this report has been completed and all necessary materials have been procured. Assembly and characterization testing is on-going at the submission of this report. This report proposes future directions for work on high-rate THz UCI and potential applications of future systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

An Approach to Characterizing Spatial Aspects of Image System Blur

In imaging applications, such as X-ray radiography, the experimental system setup and data capture process introduce system blur and distortion. In images taken with thick scintillators, a spatially varying system blur is observed, requiring a nonstandard approach to blur and distortion estimation and removal. We demonstrate an approach to estimation of local point spread functions using checkerboard radiographs collected at the Naval Research Laboratory and extend that into a map defining the kernel over the camera field of view.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Method and system for unsynchronized structured lighting

A system and method to capture the surface geometry a three-dimensional object in a scene using unsynchronized structured lighting is disclosed. The method and system includes a pattern projector configured and arranged to project a sequence of image patterns onto the scene at a pattern frame rate, a camera configured and arranged to capture a sequence of unsynchronized image patterns of the scene at an image capture rate, and a processor configured and arranged to synthesize a sequence of synchronized image frames from the unsynchronized image patterns of the scene. Each of the synchronized image frames corresponds to one image pattern of the sequence of image patterns.

Taubin, Gabriel↗
DOE OSTI2026

Quantifying Operational Drivers of Multimodal Biometric Verification in Aerial Surveillance

Multimodal biometric verification is increasingly applied across operational contexts ranging from close-range security cameras and building-mounted surveillance to long-range ground sensors and unmanned aerial system (UAS) imagery. Variations in acquisition conditions—such as image resolution, viewing geometry, and motion artifacts—pose significant challenges for cross-domain algorithmic generalization. This study evaluates two independent multimodal biometric verification systems developed under the Intelligence Advanced Research Projects Activity (IARPA) Biometric Recognition and Identification at Altitude and Range (BRIAR) program, comparing performance on close-range and aerial datasets. Close-range video served as a baseline to quantify the decline in verification performance on aerial footage. The dataset included six UAS platforms, spanning small quadcopters at 10m altitude to medium-sized fixed-wing aircraft at 360m. Mixed-effects logistic regression identified image resolution (head and body pixel counts), head height, sensor characteristics, and algorithm selection as primary determinants of verification success, whereas demographic attributes and mission gait were not significant predictors. Activity type and collection site influenced performance in close-range data but had negligible impact on UAS imagery. These results clarify modality-specific strengths and limitations and highlight opportunities to enhance cross-domain biometric verification.

Peluso, Alina [ORNL] (ORCID:0000000328950406)↗
DOE OSTI2021

Real-Time Omnidirectional Stereo Rendering: Generating 360° Surround-View Panoramic Images for Comfortable Immersive Viewing

Surround-view panoramic images and videos have become a popular form of media for interactive viewing on mobile devices and virtual reality headsets. Viewing such media provides a sense of immersion by allowing users to control their view direction and experience an entire environment. When using a virtual reality headset, the level of immersion can be improved by leveraging stereoscopic capabilities. Stereoscopic images are generated in pairs, one for the left eye and one for the right eye, and result in providing an important depth cue for the human visual system. For computer generated imagery, rendering proper stereo pairs is well known for a fixed view. However, it is much more difficult to create omnidirectional stereo pairs for a surround-view projection that work well when looking in any direction. One major drawback of traditional omnidirectional stereo images is that they suffer from binocular misalignment in the peripheral vision as a user's view direction approaches the zenith / nadir (north / south pole) of the projection sphere. This paper presents a real-time geometry-based approach for omnidirectional stereo rendering that fits into the standard rendering pipeline. Our approach includes tunable parameters that enable pole merging - a reduction in the stereo effect near the poles that can minimize binocular misalignment. Results from a user study indicate that pole merging reduces visual fatigue and discomfort associated with binocular misalignment without inhibiting depth perception.

360° panorama↗
DOE OSTI2022

An automated fast neutron computed tomography instrument with on-line focusing for non-destructive evaluation

A fast neutron tomography imaging instrument has been designed, built, and tested at The Ohio State University 500 kW Research Reactor on a fast neutron beamline with a peak neutron flux ≈5.4 × 107 n·cm−2·s−1 at 1.6 MeV median neutron energy. The instrument and beamline are also configurable for thermal neutron imaging. The imaging apparatus is composed of a lens coupled, water-cooled Electron Multiplying Charge Coupled Device camera, a front-surface mirror, and a high light yield plastic Polyvinyl toluene scintillator. The instrument sits on a mobile cart. A total of 5 motion-control stages are built into the system for XYZ and rotational degrees of freedom for sample positioning; the fifth stage fine tunes the focal distance between the camera and the scintillator to achieve on-line focusing. A Python code with a user-friendly graphical user interface controls the fully automated image acquisition, not requiring user interaction, yet facilitating tracking of the image acquisition. A complete fast neutron computed tomography dataset with 360 projections requires less than 3 h, with 30 s per projection. On-line focusing is accomplished with a commercial, off-the-shelf, dielectrically actuated liquid lens. Finally, tomographic reconstructions are visualized using the Livermore Tomography Tools software package. The effective pixel size (width and height) is ≈0.1058 mm, yielding a minimum voxel size of 0.1058 × 0.1058 × 0.1058 mm3, and produces a spatial resolution of 231 μm when calculated from knife-edge measurements.

Bisbee, M. G. (ORCID:0000000313466697)↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Collision Tracking in OpenMC: Methods and Applications in Neutron Noise, Neutron Imaging, Time-of-Flight, and Multiplicity Counting

We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.

Monte Carlo code↗
DOE OSTI2023

Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP-SAIL)

The Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP) project was conducted to help improve the understanding of precipitation formation in orographically influenced terrain. Special focus is put on the two processes of riming and secondary ice production and their external drivers. Two instruments, a polarimetric W-band simultaneous transmission simultaneous reception (STSR) Doppler cloud radar manufactured by Radiometer Physics GmbH (RPG, instrument type RPG-FMCW-94-DP), from now on named LIMRAD94, and the video in situ snowfall sensor (VISSS), were deployed at the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) site in Gothic, Colorado between November 2022 and June 2023 during the second SAIL winter. Note that the exact dates of data availability differ between the instruments. Both instruments arrived at Gothic on November 2, 2022, 09:20 local time. VISSS, described by Maahn et al., is equipped with two camera systems with telecentric lenses. The two cameras are at a 90° angle to each other. This configuration allows for size-independent measurements by capturing images of hydrometeors from two sides at a high frame rate of 250 Hz. With a minimum detection size of 200 μm, VISSS provides valuable insights into particle size, number, shape, complexity, and fall velocity. The VISSS was deployed on the grassland next to the ARM facility with the amazing help of the ARM employees on site. The setup started on November 2, 2022, and was finished on November 5, 2022, without major problems. VISSS measurements were started on November 6, 2022. LIMRAD94 was installed on a scaffolding platform near Orehouse (Gothic) on November 9, 2022, with the great help of RMBL staff. LIMRAD94 was mounted on a cold temperature scanner prototype. After a short test of the setup on November 9, 2022, the digital control of the scanner elevation stopped working for (at that time) unknown reasons. All attempts to resolve the problem failed. This malfunction made it impossible to operate LIMRAD94 in scanning mode. The scanner was then manually moved to zenith pointing mode and between November 10 and November 15, 2022, vertical observations for polarimetric calibration were performed. On November 15, 2022, after the polarimetric calibration was applied, the scanner was manually moved to 40° elevation with azimuthal view towards the Ka-band ARM Zenith Radar (KAZR) and measurements were continued at constant elevation. Investigation of the scanner malfunction on February 6, 2023, by Benn Schmatz revealed a disengagement between the cogwheel of the elevation motor and the cogwheel moving the scanner in elevation. This mechanical issue was temporarily solved by re-engaging the cogwheels. This made the scanner operational again for about four weeks, until mechanical force disengaged the cogwheels again on March 15, 2023. This repeated scanner failure remained undetected for about three weeks until April 8, 2023; during this time the scanner was stuck at 72° elevation. However, the radar software continued to produce data files falsely indicating that the scanner was still operational. After the scanner failure was noticed, scanning was stopped again, and we returned to constant elevation measurements. On May 15, 2023, the cogwheels of the elevation motor were secured with additional screws sent by the manufacturer. At some point in May, the cogwheels of the azimuth motor were also disengaged by mechanical force, which still allowed for range height indicator (RHI) but no plan position indicator (PPI) scans in the last weeks of the campaign. The azimuth motor was repaired in Germany after the end of the campaign. Throughout the campaign, RMBL and ARM staff kept the radar and the VISSS free of snow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A microfluidic study of transient flow states in permeable media using fluorescent particle image velocimetry

Velocity fields in flow in permeable media are of great importance to many subsurface processes such as geologic storage of CO 2 , oil and gas extraction, and geothermal systems. Steady-state flow is characterized by velocity fields that do not change significantly over time. The flow field transitions to a new steady state once it experiences a disturbance such as a change in flow rate or in pressure gradient. This transition is often assumed to be instantaneous, which justifies the expression of constitutive relations as functions of instantaneous phase saturations. This work examines the evolution of velocity fields in a surrogate quasi-2D permeable medium using a microfluidic device, a microscopy system, and a high-speed camera. Tracer particles are injected into the medium along with DI water. The evolution of the velocity field is examined by tracing these particles in the captured images using the standard high-density particle image velocimetry algorithm founded on cross-correlation. The results suggest that the transition between steady states for an incompressible fluid takes a finite and non-negligible amount of time that is independent of the magnitude of the change in pressure gradient. The existence of transient states and the nature of the response during these states are readily interpreted by the principle of least action where flow gradually establishes an optimal configuration such that energy dissipation is 2 minimized. The findings provide evidence against the applicability of the assumption that flowing phases relax instantaneously to their steady states and, hence, against the accuracy of the classical multiphase extension of Darcy's law.

42 ENGINEERING↗
DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems: Evaluating Radar, Lidar and Camera: Preprint

Intelligent transportation systems (ITS) are at the forefront in advancing the way we interact with and perceive the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as radar, lidar, and video imaging, which are the most popular modalities for ITS. Real-time perception data from these sensors allow intelligent infrastructure-side decision-making to improve the energy, efficiency, and safety at traffic intersections. As traffic departments across the United States transition from traditional loop detectors and emulators and embrace newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception that is reliable, inexpensive, and easy to set up and that has robust performance in varying weather conditions. However, choosing a sensor that checks all these boxes is not straightforward, as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long-range vehicles and weather resistance but lacks high resolution. Lidar is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines radar, lidar, and camera sensor capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like radar, lidar, and cameras offers the most robust solution for enhancing the safety and efficiency of ITS. Through this evaluation, we hope to draw attention to the necessity of the National Renewable Energy Laboratory's infrastructure perception and control framework, which presents a multisensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Evaluation of H-Canyon Ventilation Exhaust Tunnel Inspection at the Savannah River Site - 20052

The Department of Energy (DOE) H-Canyon Facility at the Savannah River Site (SRS) is operated by Savannah River Nuclear Solutions (SRNS). The Facility Structural Integrity Program [1] provides a process to inspect, evaluate, and document the conditions of passive safety related structural systems and components, their degradation mechanisms and their impact on the safety envelope. The Structural Integrity Program performs periodic visual inspections to confirm the systems and components can perform their safety function and recommend corrective actions before the function is compromised. The H-Canyon Exhaust Tunnel is part of the H-Canyon Ventilation System and is periodically inspected under the Structural Integrity Program. The Tunnel performs a Safety Class passive design feature function that is available 100% of the time. The underground reinforced concrete Tunnel directs Canyon process air from the Canyon to the Sand Filter System. The radiological and chemical airborne activity coupled with the physical configuration of the tunnel precludes a manned entry into the tunnel to perform the inspection. Unlike active systems that can be subjected to physical testing to confirm capability, qualification calculations, including modeling, is performed to assess passive design feature capabilities relative to operational, accident and natural phenomena hazards events. Input for these calculations come from knowledge of field conditions, design drawings and conservative assumptions. The knowledge of field conditions comes from concrete and soil testing activities as well as inspection data. The use of cameras on crawlers to obtain inspection data and how that data is used in qualification calculations is the focus of this discussion. Remote Tunnel inspections have been performed using cameras on a stick, referred to as pole cameras, prior to Calendar Year 2003 (CY2003). Since CY2003, six camera equipped crawlers have been used. Crawlers have evolved and improved by incorporating lessons learned from the previous inspections. The latest 2019 crawler successfully traveled the entire length of the tunnel between the Canyon and Sand Filter System and captured images that were previously unseen, thus providing key visual data for the Structural Integrity Program report [2]. The inspection data serves as 1) input to qualification calculations, 2) validates current conditions remain bounded by qualification calculations, and 3) documents a record of change over time. This data is vital for the effective evaluation of the tunnel structure and aids with predicting the life cycle service life safety envelope to protect the public, environment, and facility worker. The goal of the 2019 deployment was to use a more robust vehicle to ensure travel over obstacles, perform the inspection with higher resolution cameras, and have the ability to elevate the cameras to view surfaces previously obscured by abandon-in-place ducts in the tunnel. The inspection information will serve to strengthen the input basis for qualification calculations, versus using excessive conservative calculation assumptions. This 2019 inspection was compared with previous crawler visual evidence to identify change over time to project remaining service life and confirm field conditions remain bounded by qualification calculations. The results of the 2019 Exhaust Tunnel inspection continue to improve and provide a firm basis to make sound engineering judgements regarding tunnel capability and approaches in projecting remaining service life with an aging system and component. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Integrated photonic encoder for low power and high-speed image processing

Abstract Modern lens designs are capable of resolving greater than 10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made data acquisition rates of Terapixel/second a real possibility. The main bottlenecks preventing such high data-rate systems are power consumption and data storage. In this work, we show that analog photonic encoders could address this challenge, enabling high-speed image compression using orders-of-magnitude lower power than digital electronics. Our approach relies on a silicon-photonics front-end to compress raw image data, foregoing energy-intensive image conditioning and reducing data storage requirements. The compression scheme uses a passive disordered photonic structure to perform kernel-type random projections of the raw image data with minimal power consumption and low latency. A back-end neural network can then reconstruct the original images with structural similarity exceeding 90%. This scheme has the potential to process data streams exceeding Terapixel/second using less than 100 fJ/pixel, providing a path to ultra-high-resolution data and image acquisition systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Design and calibration of an optically segmented single volume scatter camera for neutron imaging

The Optically Segmented Single Volume Scatter Camera (OS-SVSC) aims to image neutron sources for non-proliferation applications using the kinematic reconstruction of elastic double-scatter events. Our prototype system consists of 64 EJ-204 organic plastic scintillator bars, each measuring 5mm × 5mm × 200mm and individually wrapped in Teflon tape. The scintillator array is optically coupled to two silicon photomultiplier ArrayJ-60035 64P-PCB arrays, each comprised of 64 individual 6x6mm J-Series sensors arranged in an 8 × 8 array. We report on the design details, including component selections, mechanical design and assembly, and the electronics system. The described design leveraged existing off-the-shelf solutions to support the rapid development of a phase 1 prototype. Several valuable lessons were learned from component and system testing, including those related to the detector's mechanical structure and electrical crosstalk that we conclude originates in the commercial photodetector arrays and the associated custom breakout cards. We detail our calibration efforts, beginning with calibrations for the electronics, based on the IRS3D application-specific integrated circuits, and their associated timing resolutions, ranging from 3090ps. With electronics calibrations applied, energy and position calibrations were performed for a set of edge bars using 22 Na and 90 Sr, respectively, reporting an average resolution of 12.07±0.03mm for energy depositions between 900keVee and 1000keVee. We further demonstrate a position calibration method for the internal bars of the matrix using cosmic-ray muons as an alternative to emission sources that cannot easily access these bars, with an average measured resolution of 14.86+-0.29mm for depositions between 900keVee and 1000keVee. The coincident time resolution reported between pairs of bars measured up to 400ps from muon acquisitions. Energy and position calibration values measured with muons are consistent with those obtained using particle emission sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Design and Analysis of a Halo-Measurement Diagnostics

A large dynamical-range diagnostics (LDRD) design at Jefferson Lab will be used at the FAST-IOTA injector to measure the transverse distribution of halo associated with a high-charge electron beam. One important aspect of this work is to explore the halo distribution when the beam has significant angular momentum (i.e. is magnetized). The beam distribution is measured by recording radiation produced as the beam impinges a YAG:Ce screen. The optical radiation is split with a fraction directed to a charged-couple device (CCD) camera. The other part of the radiation is reflected by a digital micromirror device (DMD) that masks the core of the beam distribution. Combining the images recorded by the two cameras provides a measurement of the transverse distribution with over a large dynamical range. The design and analysis of the optical system will be discussed including optical simulation using SRW and the result of a mockup experiment to test the performances of the system will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Evaluation of a fiber-coupled x-ray diffraction detector for dynamic compression experiments

The long-term x-ray diffraction (XRD) detector scheme compatible with Z-containment experiments will involve conversion of the diffracted x-rays to optical light, which will be transported away from the Z-Dynamic Materials Properties (DMP) load and detected on a fast-gated camera. In this so-called DIffraction SCintillator Optic (DISCO) scheme , the scintillator is coupled to a long, coherent imaging fiber bundle using a custom lens system with high numerical aperture. In addition, the DISCO diagnostic incorporates time-gating to allow measurement only during the short time window of the x-ray pulse in which XRD occurs, thereby significantly reducing unwanted background generated by the Z-DMP load. Dynamic compression experiments were performed at the Chama target chamber to evaluate the DISCO diagnostic . Specifically, a Zr sample was laser-shocked with the Chaco laser while the Z-Beamlet (ZBL) laser was used to generate x-rays, which enabled time-gated 6.7-keV XRD patterns from the compressed Zr sample to be obtained.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Surveillance & Detection (CRADA 567 Final Report)

This Cooperative Research and Development Agreement (CRADA) Final Report covers the work achieved by PNNL and it's commercial partner (Consolidated Resource Imaging, LLC) on video analytics for the DHS S&T Surveillance & Detection project. This project has been focused on development of the next-generation camera system (Guardian iiS) with extremely high resolution and video analytics specifically designed for crowded urban environments and congested transportation hubs.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

A multi-scale temperature-based strategy to map hydrologic exchange flows in highly dynamic systems

Mapping and quantifying hydrologic exchange flows (HEFs) is critical to environmental monitoring and remediation at contaminated sites; however, these objectives are challenging in highly dynamic systems, e.g., along dam-regulated rivers, where HEFs vary rapidly. Direct seepage measurements are labor-intensive and difficult to automate, whereas indirect (e.g., thermal) and remote sensing methods have potential to allow continuous monitoring with limited field effort. We present a preliminary assessment of a multi-scale temperature-based strategy for monitoring HEFs along the Hanford Reach of the Columbia River, in eastern WA, United States. Five thermal methods were assessed. First, a vertical temperature profile (VTP) was installed into the streambed. The VTP data were analyzed using a data assimilation algorithm designed for automated real-time estimation in dynamic systems. Second, a thermal infrared (TIR) camera was used in roving surveys to identify seeps. Third, a TIR camera was stationed at the VTP site to collect images at 1-h intervals. Together, the two TIR datasets provided a basis to assess the potential for drone-based TIR. Fourth, temperature was measured at the sediment/water interface to assess fiber-optic distributed temperature sensing. Fifth, imagery from the ECOSTRESS satellite mission was acquired to assess the potential of spaceborne thermal monitoring. Based on our preliminary assessment, VTP, TIR, and bed temperature measurements provide complementary spatial coverage, temporal sampling, and resolution; these methods have potential for long-term, automated monitoring of HEFs. The publicly available spaceborne imagery, however, proved inadequate because of insufficient spatial resolution and data gaps resulting from cloud cover and revisit frequency.

54 ENVIRONMENTAL SCIENCES↗