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DOE OSTI2020

Depth Thermography: Noninvasive 3D Temperature Profiling Using Infrared Thermal Emission

Here, we introduce a technique based on infrared thermal emission, termed depth thermography, that can remotely measure the temperature distribution beneath the surface of certain objects. Depth thermography utilizes the thermal-emission spectrum in the semitransparent spectral region of the target object to extract its temperature as a function of depth, in contrast with conventional thermography, which uses the spectrally integrated thermally emitted power to measure the surface temperature. Coupled with two-dimensional imaging, for example using an infrared hyperspectral camera or scanning a single-pixel spectrometer, this technique can yield volumetric temperature distributions. Furthermore, we carried out a proof-of-concept experiment on an asymmetrically heated fused-silica window, extracting the temperature distribution throughout the sample. Depth thermography may enable noncontact volumetric temperature measurements of microscopic objects such as multilayer electronic devices or macroscopic volumes of liquids and gases, as well as simultaneous all-optical measurements of optical and thermal properties of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2001

Imaging Radar in the Mojave Desert-Death Valley Region

The Mojave Desert-Death Valley region has had a long history as a test bed for remote sensing techniques. Along with visible-near infrared and thermal IR sensors, imaging radars have flown and orbited over the area since the 1970's, yielding new insights into the geologic applications of these technologies. More recently, radar interferometry has been used to derive digital topographic maps of the area, supplementing the USGS 7.5' digital quadrangles currently available for nearly the entire area. As for their shorter-wavelength brethren, imaging radars were tested early in their civilian history in the Mojave Desert-Death Valley region because it contains a variety of surface types in a small area without the confounding effects of vegetation. The earliest imaging radars to be flown over the region included military tests of short-wavelength (3 cm) X-band sensors. Later, the Jet Propulsion Laboratory began its development of imaging radars with an airborne sensor, followed by the Seasat orbital radar in 1978. These systems were L-band (25 cm). Following Seasat, JPL embarked upon a series of Space Shuttle Imaging Radars: SIRA (1981), SIR-B (1984), and SIR-C (1994). The most recent in the series was the most capable radar sensor flown in space and acquired large numbers of data swaths in a variety of test areas around the world. The Mojave Desert-Death Valley region was one of those test areas, and was covered very well with 3 wavelengths, multiple polarizations, and at multiple angles. At the same time, the JPL aircraft radar program continued improving and collecting data over the Mojave Desert Death Valley region. Now called AIRSAR, the system includes 3 bands (P-band, 67 cm; L-band, 25 cm; C-band, 5 cm). Each band can collect all possible polarizations in a mode called polarimetry. In addition, AIRSAR can be operated in the TOPSAR mode wherein 2 antennas collect data interferometrically, yielding a digital elevation model (DEM). Both L-band and C-band can be operated in this way, with horizontal resolution of about 5 m and vertical errors less than 2 m. The findings and developments of these earlier investigations are discussed.

Farr, Tom G.↗

NASA NTRS2011

CIRS-lite, a Fourier Transform Spectrometer for Low-Cost Planetary Missions

Passive spectroscopic remote sensing of planetary atmospheres and surfaces in the thermal infrared is a powerful tool for obtaining information about surface and atmospheric temperatures, composition, and dynamics (via the thermal wind equation). Due to its broad spectral coverage, the Fourier transform spectrometer (FTS) is particularly suited to the exploration and discovery of molecular species. NASA's Goddard Space Flight Center (GSFC) developed the CIRS (Composite Infrared Spectrometer) FTS for the NASA/ESA Cassini mission to the Saturnian system. CIRS observes Saturn, Titan, icy moons such as Enceladus, and the rings in thermal self-emission over the spectral range of 7 to 1000 ell11. CIRS has given us important new insights into stratospheric composition and jets on Jupiter and Saturn, the cryo-geyser and thermal stripes on Enceladus, and the winter polar vortex on Titan. CIRS has a mass of 43 kg, contrasted with the earlier GSFC FTS, pre-Voyager IRIS (14 kg). Future low-cost planetary missions will have very tight constraints on science payload mass, thus we must endeavor to return to IRIS-level mass while maintaining CIRS-level science capabilities ("do more with less"). CIRS-lite achieves this by pursuing: a) more sensitive infrared detectors (high Tc superconductor) to enable smaller optics. b) changed long wavelength limit from 1000 to 300 microns to reduce diffraction by smaller optics. c) CVD (chemical vapor deposition) diamond beam-splitter for broad spectral coverage. d) single FTS architecture instead of a dual FTS architecture. e) novel materials, such as single crystal silicon for the input telescope primary.

Brasunas, J.↗

NASA NTRS2012

CIRS and CIRS-Lite as Designed for the Outer Planets: TSSM, EJSM, JUICE

Brasunas, J.↗

NASA NTRS2017

Estimating Leaf Water Status from Vis-Nir Reflectance and Transmittance

Remotely sensing the water status of plant canopies remains a long term goal of remote sensing research. Established approaches involve measurements in the thermal infrared and the 900-2000nm reflective infrared. Less popular UV-visible-NIR techniques presumably deserve research attention, because photochemical changes linked to plant water status manifest spectral light scattering and absorption changes. Here we monitored the visible and NIR light reflected from the leaf interior as well as the leaf transmittance as the relative water content of corn (Zeamays L.) leaves decreased. Our results highlight the importance of both scattering effects and effects due to absorption by leaf pigments.

VIS-NIR Reflectance↗

NASA NTRS1997

An Overview of Volcanological Applications of Infrared Remote Sensing

Infrared remote sensing has long been applied to the study of volcanic and geothermal phenomena. The initial investigations utilized single-channel thermal imagging systems, whereas more recent work has demonstrated the utility of multispectral infrared imaging.

Remote Sensing volcanic geothermal phenomena↗

NASA NTRS2026

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗

NASA NTRS1982

Radar and infrared remote sensing of geothermal features at Pilgrim Springs, Alaska

High-altitude radar and thermal imagery collected by the NASA research aircraft WB57F were used to examine the structural setting and distribution of radiant temperatures of geothermal anomalies in the Pilgrim Springs, Alaska area. Like-polarized radar imagery with perpendicular look directions provides the best structural data for lineament analysis, although more than half the mapped lineaments are easily detectable on conventional aerial photography. Radiometer data and imagery from a thermal scanner were used to evaluate radiant surface temperatures, which ranged from 3 to 17 C. The evening imagery, which utilized density-slicing techniques, detected thermal anomalies associated with geothermal heat sources. The study indicates that high-altitude predawn thermal imagery may be able to locate relatively large areas of hot ground in site-specific studies in the vegetated Alaskan terrain. This imagery will probably not detect gentle lateral gradients.

Dean, K. G.↗

NASA NTRS2011

Combining Observations in the Reflective Solar and Thermal Domains for Improved Mapping of Carbon, Water and Energy FLuxes

This study investigates the utility of integrating remotely sensed estimates of leaf chlorophyll (C(sub ab)) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. Day to day variations in nominal LUE (LUE(sub n)) were assessed for a corn crop field in Maryland U.S.A. through model calibration with CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. Changes in Cab exhibited a curvilinear relationship with corresponding changes in daily calibrated LUE(sub n) values derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for monitoring of carbon and water fluxes.

Houborg, Rasmus↗

NASA NTRS2010

Using Leaf Chlorophyll to Parameterize Light-Use-Efficiency Within a Thermal-Based Carbon, Water and Energy Exchange Model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.

Houlborg, Rasmus↗

NASA NTRS1993

ATTIRE (analytical tools for thermal infrared engineering): A sensor simulation and modeling package

The Advanced Sensor Development Laboratory (ASDL) at the Stennis Space Center develops, maintains and calibrates remote sensing instruments for the National Aeronautics & Space Administration (NASA). To perform system design trade-offs, analysis, and establish system parameters, ASDL has developed a software package for analytical simulation of sensor systems. This package called 'Analytical Tools for Thermal InfraRed Engineering' - ATTIRE, simulates the various components of a sensor system. The software allows each subsystem of the sensor to be analyzed independently for its performance. These performance parameters are then integrated to obtain system level information such as Signal-to-Noise Ratio (SNR), Noise Equivalent Radiance (NER), Noise Equivalent Temperature Difference (NETD) etc. This paper describes the uses of the package and the physics that were used to derive the performance parameters.

Jaggi, S.↗

DOE OSTI2024

Mid-infrared photodetection with 2D metal halide perovskites at ambient temperature

The detection of mid-infrared (MIR) light is technologically important for applications such as night vision, imaging, sensing, and thermal metrology. Traditional MIR photodetectors either require cryogenic cooling or have sophisticated device structures involving complex nanofabrication. Here, we conceive spectrally tunable MIR detection by using two-dimensional metal halide perovskites (2D-MHPs) as the critical building block. Leveraging the ultralow cross-plane thermal conductivity and strong temperature-dependent excitonic resonances of 2D-MHPs, we demonstrate ambient-temperature, all-optical detection of MIR light with sensitivity down to 1 nanowatt per square micrometer, using plastic substrates. Through the adoption of membrane-based structures and a photonic enhancement strategy unique to our all-optical detection modality, we further improved the sensitivity to sub–10 picowatt-per-square-micrometer levels. The detection covers the mid-wave infrared regime from 2 to 4.5 micrometers and extends to the long-wave infrared wavelength at 10.6 micrometers, with wavelength-independent sensitivity response. Our work opens a pathway to alternative types of solution-processable, long-wavelength thermal detectors for molecular sensing, environmental monitoring, and thermal imaging.

Li, Yanyan [Yale University, New Haven, CT (United↗

NASA NTRS1969

The use of color infrared photography and thermal imagery in marshland and estuarine studies

Color infrared photography for remote sensing of shallow water areas by air

Anderson, R. R.↗

NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗

NASA NTRS1970

Geologic studies of Yellowstone National Park imagery using an electronic image enhancement system

The image enhancement system is described, as well as the kinds of enhancement attained. Results were obtained from various kinds of remote sensing imagery (mainly black and white multiband, color, color infrared, thermal infrared, and side-looking K-band radar) of parts of Yellowstone National Park. Possible additional fields of application of these techniques are considered.

Smedes, H. W.↗

NASA NTRS2001

Ground-Based IR Spectroscopy of Mercury for Composition

Remote sensing measurements of the Moon and Mercury in the thermal infrared have been plagued with problems due to atmospheric absorption and other effects. Controversial results have been discussed by Nash et al. and by Salisbury et al.. We have developed a technique to obtain thermal infrared spectra of Mercury together with solar and sky spectra in the 8-13 micrometer region suitable for determining the presence or absence of mineralogical features. High-resolution (0.05 cm(exp -1) between data points) spectra were obtained during daylight using the Fourier Transform Spectrograph (FTS) at the McMath-Pierce Solar Telescope Facility at Kitt Peak National Observatory, Arizona. The reduced data were independent of any model of the transmission of the Earth's atmosphere and rest on a calibration using sky spectra along the same line-of-sight through the atmosphere as the actual Mercury raw spectrum. This method can be applied at all solar elongation angles including small elongation angles (5 deg or less). The basic sequence and the technique are robust.

Killen, Rosemary M.↗

NASA NTRS1980

Eighth year projects and activities of the Environmental Remote Sensing Applications Laboratory (ERSAL)

Projects completed for the NASA Office of University Affairs include the application of remote sensing data in support of rehabilitation of wild fire damaged areas and the use of LANDSAT 3 return beam vidicon in forestry mapping applications. Continuing projects for that office include monitoring western Oregon timber clearcut; detecting and monitoring wheat disease; land use monitoring for tax assessment in Umatilla, Lake, and Morrow Counties; and the use of Oregon Air National Guard thermal infrared scanning data. Projects funded through other agencies include the remote sensing inventory of elk in the Blue Mountains; the estimation of burned agricultural acreage in the Willamette Valley; a resource inventory of Deschutes County; and hosting a LANDSAT digital workshop.

Lewis, A. J.↗

NASA NTRS1991

The application of geologic remote sensing to vertebrate biostratigraphy - General results from the Wind River Basin, Wyoming

Since 1986, remote sensing images derived from satellite and aircraft-borne sensor data have been used to study the stratigraphy and sedimentology of the vertebrate-bearing Wind River and Wagon Bed formations in the Wind River Basin (Wyoming). Landsat 5 TM and aircraft Thermal Infrared Multispectral Scanner data were combined with conventional geologic analyses. The remote sensing data have contributed significantly to: (1) geologic mapping at the formation, member, and bed levels; (2) stratigraphic correlation; (3) reconstruction of ancient depositional environments; and (4) identification of structural complexity. This information is critical to vertebrate paleontology in providing the stratigraphic, sedimentologic, and structural framework required for evolutionary and paleoecologic studies. Of primary importance is the ability to map at minimal cost the geology of large areas (20,000 sq km or greater) at a high level of precision. Remote sensing data can be especially useful in geologically and paleontologically unexplored or poorly understood regions.

Stucky, Richard K.↗