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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Total Ionizing Dose (TID) Testing of the PA10 Power Operational Amplifier

This study was undertaken to determine the total ionizing dose (TID) sensitivity of the PA10 Power Op Amp Manufactured by APEX (figure 1), which is a candidate for use on the LDCM TIRS instrument. The test was conducted with interest in both parametric degradation and functional failure in the configuration like that of the TIRS application. (See figure 2). The DUT was irradiated in a stepwise fashion, with parametric and functional degradation measured between steps. The parts were irradiated with gamma rays at a low dose rate (~0.01 rads(Si)/sec.).

total ionizing dose (TID)↗
NASA NTRS2020

Prelaunch Radiometric Calibration and Uncertainty Analysis of Landsat Thermal Infrared Sensor 2

The Thermal Infrared Sensor-2 (TIRS-2) that will be onboard Landsat 9 has undergone a prelaunch testing campaign to characterize its radiometric, spectral, and spatial performances and demonstrate compliance to its requirements. This work reviews the key elements of the instrument-level radiometric testing using an SI-traceable source to derive its uncertainties. Those arising from on-orbit calibration using the TIRS-2 onboard blackbody are also discussed. We use a Monte Carlo approach to propagate the uncertainties through a nonlinear calibration equation and address both random and systematic uncertainty terms. Achieving the required performance demonstrates the instrument's potential for enhancing our understanding of the Earth's environment.

Aaron Pearlman↗
NASA NTRSDate not supplied

Landsat 9 pre-launch sensor characterization and comparison with Landsat 8 results

Landsat 9 is planned for launch in December 2020 to continue the mission of observing changes on the Earth’s surface that began in 1972 with the launch of Landsat 1. Like Landsat 8, Landsat 9 will carry two imaging instruments: Operational Land Imager 2 (OLI-2), designed and built by Ball Aerospace, and Thermal Infrared Sensor 2 (TIRS-2), manufactured by NASA Goddard Space Flight Center (GSFC). As of this writing, both sensors have completed the instrument-level ground testing and are ready for integration into the spacecraft. Data collected during the pre-launch performance testing are analyzed to assess the usability of responses of the video reference pixels (VRPs)located on the focal planes of OLI-2 and Landsat 8 OLI for more accurate detector bias estimates, develop a methodology to correct for nonlinearities in the OLI-2 response and compare it to the OLI correction approach, and determine the spatial performance of TIRS-2.

Esad Micijevic↗
NASA NTRS2021

The Thermal Infrared Optical Depth of Mineral Dust Retrieved from Integrated CALIOP and IIR Observations

Recent studies reveal that a higher fraction of coarse mineral dust particles than that estimated by climate model simulations has been observed in the atmosphere, leading to a more significant positive (i.e., warming) longwave (LW) thermal infrared (TIR) direct radiative effect (DRE). However, the magnitude of this DRE remains highly uncertain because our understanding of the radiative properties, quantitatively represented by the optical depth of dust, especially information on the TIR, remains limited. This study presents a simple approach to retrieve the thermal infrared dust aerosol optical depth (DAODTIR) over oceans during nighttime using the observations from the Infrared Imaging Radiometer (IIR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO. For each cloud-free dust-laden profile identified by the IIR-CALIOP observation, a Lookup-Table (LUT) of the 10.6 μm IIR band brightness temperatures difference (dBT) under different DAODTIR with respect to their dust-free BTs is constructed based on the CALIOP retrieved dust vertical profile and pre-assumed dust scattering properties using a fast radiative transfer model. Then the DAODTIR is retrieved by projecting the IIR-observed dBT on the LUT. Sensitivity studies show that the DAODTIR retrieval at 10.6 μm is more susceptible to the dust particle size distribution (PSD) assumption than dust refractive indices. To estimate the uncertainty caused by PSD assumption, two DAODTIR retrieval products, one based on the dust PSD from the AERONET at Cape Verde and the other on an in situ measured PSD from the recent Fennec campaign, are provided. The retrieval uncertainty is mainly contributed by the BT difference between the observation and simulation using auxiliary atmospheric data. The climatology of the retrieval from 2013 to 2019 shows confident spatiotemporal variations of DAODTIR with the global-averaged value of 0.006 and 0.008 based on different pre-assumed dust PSDs. Climatological results agree reasonably well with two independent DAODTIR retrieval products based on the Infrared Atmospheric Sounding Interferometer (IASI) over the active dust transport regions, such as North and Tropical Atlantic (r = 0.904 and 0.819) and Indian Ocean (r = 0.832). The seasonal and interannual variation is also well-compared (r = 0.758) with AERONET coarse-mode AOD at 97 selected sites. The synergic CALIOP observation allows the retrieved DAODTIR to directly compare with the extrapolated DAODTIR from DAOD in visible (i.e., 532 nm), which helps evaluate the observational constraints on DAODTIR. This study offers a unique prospect of collocating active lidar and passive IR observations for retrieving dust DAODTIR.

aerosol↗
NASA NTRS2022

Wichita Climate II: Quantifying and Mapping Urban Heat to Inform Equitable and Sustainable Urban Planning Initiatives in Wichita, Kansas

Wichita, Kansas is experiencing a host of climate threats, particularly extreme heat manifested through Urban Heat Islands (UHI). Heat is unevenly distributed within cities due to factors such as income inequality, historical discriminatory practices like redlining, and divestment in neighborhoods of color. This leads to less vegetation and more heat-absorbing infrastructure in specific communities. Moreover, adverse effects of heat, including heat-related morbidity and mortality, disproportionately impact populations that experience vulnerability through social inequities and structural discrimination. Heat vulnerability is a combination of the factors of heat exposure, sensitivity, and adaptive capacity, and can be harnessed to guide urban heat interventions. This DEVELOP project partnered with the City of Wichita to understand the spatial distribution and drivers of UHIs and heat vulnerability indicators. The team modeled outcomes of tree cover interventions using Landsat 8’s Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI), Landsat 9 TIRS-2 and OLI-2, and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on the International Space Station (ECOSTRESS) sensor, along with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling model. The team also leveraged statistical analysis by implementing principal component analysis to develop a heat vulnerability index (HVI) specific to Wichita. Ultimately, the project’s outputs will inform the City of Wichita’s Climate Adaptation and Mitigation Plan, identify priority areas for heat mitigation initiatives, and be used in public-facing communications to educate communities on the impacts of urban heat.

Environmental Justice↗
NASA NTRSDate not supplied

Dual and Multi-Spectral Band SLS Infrared Camera Systems

Based on the recent success of our strained-layer superlattice (SLS)-based infrared (IR) camera that performed Earth imaging from the International Space Station (ISS) in 2019 we have built, what we consider, to be the next generation multi-band SLS imaging system. The Compact Thermal Imager (CTI) was installed on the Robotic Refueling Mission 3 (RRM3) and attached to the exterior of the ISS. From this location we were able to capture 15 million images of a multitude of fires around the globe in 2019. This unexpected trove of data initiated quite a bit of scientific interest to further utilize this imaging capability but would include features to more precisely monitor terrestrial fires and other surface phenomena. To this end, we developed a technique to install specific bandpass filters directly onto the SLS detector hybrid assembly. Utilizing this technique we have built a CTI-2 camera system with two filters, 4 and 11µm, and have made a second detector assembly with six filter bands from 4-12µm. This second system will also be used to supplement Landsat remote imaging monitoring approximate land surface temperatures, monitor evapotranspiration, sea ice and glacier dynamics. The CTI-2 camera is based on a 1,024x1,024 (1kx1k) format SLS detector hybridized to a FLIR ISC0404 readout integrated circuit (ROIC). The six band SLS focal plane array is based on the 640x512 FLIR ISC 9803 ROIC. This camera system is based on the Landsat 8 and 9 Thermal IR Sensors (TIRS) instrument and one of its purposes is to perform ground truthing for the Landsat 8/9 data at higher spectral resolution. Both Landsat TIRS instruments are dual band thermal IR sensors centered on 11 and 12µm (each with about a 1µm bandpass). Both of our SLS systems utilize a Ricor K548 cryocooler. To streamline costs and development time we used commercial optics and both commercial and custom NASA electronic components. A primary feature of these camera systems is the incorporation of specific filters to collect fire data at ~3.9µm and thermal data at ~11µm. The CTI-2 instrument is designed for 37 m /pixel spatial resolution from 410km orbit (ISS orbit). In this paper, we will present the design and performance of the focal plane, optics, electronics and mechanical structure of the dual‑band CTI-2 and the focal plane performance of the six‑band focal plane.

Murzy Jhabvala↗
NASA NTRS2022

Orbital Trade Study for the PREFIRE Mission

The Polar Radiant Energy in the Far-Infrared Experiment (PREFIRE) is a low-cost cubesat-based Earth Science mission selected for rapid implementation through NASAs Earth Ventures-Instrument program. Two cubesats carrying thermal infrared spectrometers (TIRS) in polar orbits will test long-held assumptions regarding radiative balance at long wavelengths where the cold-dry Arctic and Antarctic surfaces expel significant amounts of the earth's radiant energy. Thermal radiometry with better than one micron sampling at wavelengths beyond 15 microns will provide critical observational bounds for inputs into glacier melt and climate change models through improvements in surface emissivities, longwave greenhouse effect parameterizations, and cloud presence/types. Additional information on potential far-infrared surface/atmosphere feedbacks during rapid melt processes may be captured with sub-diurnal revisits of targeted areas. A baseline mission with two cubesats in different orbits provides a means for optimization of sub-diurnal sampling for science purposes. In this presentation we provide details of orbit studies that inform expected sampling metrics. Candidate orbits are modeled in SGP and then TIRS sampling is projected into surface footprints with appropriate geo-location. Matching algorithms then compile statistics for time-delayed revisits between and within the two orbits. Binning of results by latitude allows for abstraction of precession issues as well as for correlations with surface types as defined by radiometric classification schemes. Multiple acceptable pairs of science-driven orbits were found that optimize sampling in areas known to experience rapid melt events. The final choice of PREFIRE orbital parameters includes the systems trade-space, particularly the power budget, as well as the availability of launch opportunities.

"L'Ecuyer, Tristan"↗
NASA NTRSDate not supplied

Using Mineralogy to Interpret Martian Geologic History

The surface mineralogy of Mars is key to interpreting the planet’s geologic history and constraining when and where Mars may have been habitable to microbial life. Orbital mineralogical data from infrared spectrometers collected over the last two decades have demonstrated that Mars is more than a basaltic planet. Thermal infrared (TIR) emission spectrometers have identified regional variations in igneous minerals, iron oxides, and chloride salts, showing evidence for magmatic evolution and aqueous alteration. Orbital visible/shortwave infrared reflectance spectra provide detailed information about the aqueous history of Mars through the identification of clay minerals, sulfates, carbonates, zeolites, and amorphous materials in ancient ~3-4-billion-year-old terrains. Mineralogical data from rovers allow us to better characterize mineral formation mechanisms by identifying mineral assemblages and placing them in geologic context using outcrop- to grain-scale images. TIR and Mössbauer data from the Mars Exploration Rovers helped identify an ancient dune-interdune playa environment with multiple episodes of groundwater at Meridiani Planum and volcanism-induced hydrothermalism at Gusev crater. The CheMin X-ray diffractometer on the Mars Science Laboratory Curiosity rover in Gale crater is the first fully quantitative mineralogical instrument sent to another planetary surface. CheMin data allow the quantification of minerals and X-ray amorphous materials with a mineral detection limit of <1 wt.% and provide crystal chemistry of major phases from refined unit-cell parameters. CheMin has revealed local mineralogical changes in ancient sedimentary rocks not seen from orbit and helped identify habitable environments. Throughout the 600+ m of vertical stratigraphy studied so far, changes in clay mineralogy, Fe-oxides/oxyhydroxides, sulfates, and carbonates demonstrate a long history of surface and groundwater at Gale crater with variable salinity, pH, Eh, and temperature. Recent CheMin data document a decrease in clay minerals and an increase in sulfate minerals in younger strata that corresponds with a change from fluvio-lacustrine to eolian depositional environments, potentially documenting a change to a drier climate across the planet.

E. B. Rampe↗
NASA NTRS2023

Huntsville Urban Development II: Utilizing NASA Earth Observations to Map the Urban Heat Island and Evaluate Vulnerability in Huntsville, Alabama

Huntsville, Alabama has seen a boom in growth over recent years. One consequence of this urban expansion is the exacerbation of the Urban Heat Island (UHI) effect across the city. This project identified the areas within Huntsville the greatest potential for heat reduction and community health benefits from tree-planting efforts. The team created maps of land surface temperature (LST), the normalized difference vegetation index (NDVI), and the normalized difference built-up index (NDBI) over June through August from 2019 to 2022 using data from ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station, Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Landsat 9 OLI-2 and TIRS-2. The team identified areas with high LST, low NDVI, and high NDBI as areas with the greatest potential for heat reduction via tree-planting. Social factors relating to age, race, income, and self-reported health were adapted from Tree Equity Score to map community need for tree cover. When combining social with environmental factors, the team determined areas with the greatest potential for UHI mitigation: west-central and north downtown Huntsville. The team’s partner organization, the City of Huntsville, can use this priority map to guide their future tree-planting, and weigh the factors assessed according to their preference.

James Karroum↗
NASA NTRS2024

Big Cypress Water Resources: Using Earth Observations to Assess Water Quality in Big Cypress Reservation, FL

Upstream agricultural development and runoff are driving harmful algal blooms in the Big Cypress Reservation. The Seminole Tribe of Florida Environmental Resource Management Department monitors water quality in the Big Cypress Reservation, located on the north end of Big Cypress National Preserve. The Environmental Resource Management Department aims to incorporate Earth observations into its investigative approach, which consists of Geographic Information Systems and in situ water sampling. We assessed the feasibility of using Earth observations to measure harmful algal blooms over time and identify vulnerable areas. We analyzed data from multiple remote sensing platforms and sensors, including Landsat 8 Thermal Infrared Spectrometer(TIRS), Landsat 9 TIRS-2, Landsat 9 Operational Land Imager 2, Sentinel-2 MultiSpectral Instrument, and Sentinel-3 Ocean and Land Color Instrument. We determined that it was challenging to use Sentinel-3, Landsat 8, and Landsat 9 imagery for monitoring the canals within the Reservation, and that Sentinel-2 was the most capable platform for the study area. Using Sentinel-2, we created spectral indices for the detection of algal blooms. We used these indices to measure algal blooms at 8 stations across the Big Cypress Reservation. We then created time series and seasonal decompositions of in situ water sample data and indices to visualize relationships between datasets, along with correlation matrices. Our correlations were not conclusive. However, we found that the spectral indices have the potential to detect algal blooms. Lastly, we evaluated Maxar WorldView-3 imagery and found that using data from sensors with higher spatial resolutions would improve results.

Remote sensing↗
NASA NTRS2024

San José Urban Development: Quantifying Canopy Cover and Land Surface Temperature in San José to Identify Future Tree Planting Sites

The urban heat island effect refers to the phenomenon of substantially increased temperatures in urban areas compared to their surrounding suburban or rural counterparts. The City of San José’s Department of Parks, Recreation and Neighborhood Services (PRNS) and Department of Transportation (DOT) work to mitigate the UHI effect through urban forestry initiatives. The PRNS and DOT partnered with NASA DEVELOP to identify areas in need of tree plantings. We examined land surface temperature (LST) throughout the city using data from the Thermal Infrared Sensor (TIRS) and TIRS-2 on NASA’s Landsat 8 and 9 satellites from 2013 to 2024. We also assessed canopy cover in parks using LiDAR data collected in 2020 for the United States Geological Survey’s 3D Elevation Program, and measured vegetation greenness using the Normalized Difference Vegetation Index (NDVI) with PlanetScope imagery from 2018 to 2024. We evaluated social and environmental factors that influence the distribution of heat event impacts by creating a heat vulnerability index. We found that heat is concentrated in urban areas and that poor vegetation health is associated with high LST. We also found that socially vulnerable communities are disproportionately located in areas of high environmental risk. These analyses allow the partners to prioritize tree plantings in parks near areas of high social and environmental risk. We determined that Earth observations can be used to inform urban forestry decision making, but because methodologies for using LiDAR to assess canopy cover vary greatly, it is difficult to make comparisons across different canopy cover assessments.

land surface temperature↗
NASA NTRS2011

Scheduling Onboard Processing for the Proposed HyspIRI Mission

The proposed Hyspiri mission is evaluating a X-band Direct Broadcast (DB) capability that would enable data to be delivered to ground stations virtually as it is acquired. However the HyspIRI VSWIR and TIR instruments will produce 1 Gbps data while the DB capability is 15 M bps for a ~60x oversubscription. In order to address this data volume mismatch a DB concept has been developed thatdetermines which data to downlink based on both: 1. The type of surface the spacecraft is overflying and 2. Onboard processing of the data to detect events. For example when the spacecraft is overflying polar regions it might downlink a snow/ice product. Additionally the onboard software will search for thermal signatures indicative of a volcanic event or wild fire and downlink summary information (extent, spectra) when detected. The process of determining which products to generate when, based on request prioritization and onboard processing and downlink constraints is inherently a prioritized scheduling problem - we describe work to develop an automated solution to this problem.

visible shortwave infrared (VSWIR)↗
NASA NTRS2020

Pre-launch Radiometric Calibration and Uncertainty Analysis of Landsat Thermal Infrared Sensor 2

The Thermal Infrared Sensor-2 that will be on-board Landsat 9 has undergone a pre-launch testing campaign to characterize its radiometric, spectral, and spatial performance and demonstrate compliance to its requirements. This work reviews key elements of the instrument-level radiometric testing using an SI traceable source to derive its uncertainties. Those arising from on-orbit calibration using the TIRS-2 on-board blackbody are also discussed. We use a Monte Carlo approach to propagate the uncertainties through a non-linear calibration equation and address both random and systematic uncertainty terms. Achieving the required performance demonstrates the instrument’s potential for enhancing our understanding of the Earth’s environment.

Landsat↗
NASA NTRS2023

Los Angeles Urban Development: Utilizing NASA Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

Over the last several decades the city of Los Angeles, California, has been experiencing increased temperatures resulting from the urban heat island effect. This is largely due to the expansion of developed areas which allow for the trapping of heat, posing dangerous health risks. As a solution, many organizations have turned to urban greening and tree planting initiatives to help cool vulnerable communities. NASA DEVELOP has partnered with City Plants and the City of Los Angeles, Office of Forest Management to study the role of trees in urban environments and their relation to the mitigation of local urban heat islands. This team used NASA Earth observation data spanning from 2016 to 2022, including land surface temperature and Normalized Difference Vegetation Index (NDVI) data collected from Landsat 8 Thermal Infrared Sensor (TIRS) and International Space Station (ISS) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), respectively. Data from the National Agriculture Imagery Program (NAIP) were also used to obtain a supervised classification of tree canopy cover. Our analysis reveals a spatial and temporal connection between temperature and vegetation, suggesting that areas with more vegetation are less likely to suffer high summertime temperatures. Results also highlight the impacts of tree planting programs, such as the Vermont Corridor planting project, which increased tree canopy cover by up to 5% in the community between 2016 and 2022. These findings support the implementation of urban greening practices and inform residents and officials about how investing in trees will help mitigate increasing heat within Los Angeles.

Urban heat island↗
NASA NTRS2023

Portland Urban Development: Quantifying and Visualizing Urban Heat with Compounding Vulnerabilities to Support Community Depaving Initiatives

Urban heat is a pressing concern in Portland, Oregon as climate change induced heat waves increase. Cities experience higher temperatures due to the urban heat island effect (UHI), and environmental injustice and disenfranchisement in minority communities expose low-income and Black, Indigenous, and People of Color (BIPOC) residents to more extreme and debilitating heat events. Our team identified Portland’s communities on the frontlines of urban heat impacts by overlapping environmental and social vulnerabilities using NASA Earth observations. We partnered with Depave, a Portland-based nonprofit that works alongside communities to replace pavement with greenspace in historically disenfranchised areas. Using Landsat 8 Thermal Infrared Sensor (TIRS) imagery, we mapped Land Surface Temperature (LST) and developed a heat-specific Social Vulnerability Index (SVI) through a Principal Component Analysis (PCA) to identify Portland’s communities with the highest potential heat vulnerability. Then, we calculated the temperature change of depaving in six case studies to quantify Depave's efforts in heat mitigation and environmental justice. Our analysis demonstrated that, throughout Portland, there are frontline communities experiencing high potential social vulnerability to extreme temperatures due to environmental injustices and over-pavement. Finally, Depave’s impact on urban heat is observable and quantifiable using remote-sensing data and tools, with an average of 1ºF LST decrease across the six case studies. We illustrated the significance of local urban heat mitigation efforts and propose next steps for conducting inclusive and intentional research that highlights the lived experiences and resilience of frontline communities.

Environmental justice↗
DOE OSTI2020

Extrinsic Absorption Pathways in Vanadium-Doped SiC Measured Using a Total Internal Reflection Geometry

Vanadium-doped SiC is under study for high-power photoconductive switches and is receiving increased attention as a potential material system for quantum computing, as the V can act as a quantum emitter at telecom wavelengths. Knowledge of the defect-mediated electronic transition pathways from sub-bandgap illumination in this material with low absorption and multi-photon and multi-path transition probability is important in optimizing quantum efficiency. Herein, the optical transitions of vanadium-doped SiC for two polytypes as a function of dopant concentration using a total internal reflection (TIR) geometry are examined. Furthermore, normalized quantum efficiency is reported and correlated with both dopant concentrations (V, N, B, and Al) measured by secondary ion mass spectroscopy (SIMS) and absorption measurements. Although both polytypes respond well to 532 nm light, efficiency at longer wavelengths does not correlate 1:1 with absorption coefficient and strongly depends on the polytype and net background co-dopant concentration. This has important implications for efficient excitation of both carriers for optoelectronics and for the use of V as a quantum emitter.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Identification of a QTL region for tomato brown rugose fruit virus resistance in Solanum pimpinellifolium

Abstract Tomato (Solanum lycopersicumL.), one of the most widely grown vegetables in the world, has been seriously impacted in the past decade by the emerging tomato brown rugose fruit virus (ToBRFV). ToBRFV is a seed-borne tobamovirus, with ability to overcome the commonly usedTm-2 2 resistance gene in tomato. The objective of this study was to conduct quantitative trait locus (QTL) mapping and identify single-nucleotide polymorphism (SNP) markers associated with ToBRFV resistance in tomato. Two F 2 populations were used for QTL mapping: One derived from a cross betweenS. pimpinellifoliumUSVL333 (PI 390718) × USVL332 (PI 390717) and another from ‘Moneymaker’ × USVL332 (PI 390717), with population sizes of 195 and 79 plants, respectively. The resistance trait was derived from theS. pimpinellifoliumaccession USVL332 (PI 390717). A major QTL for ToBRFV resistance was identified on chromosome 11 (SL4.0ch11), with the peak located at approximately 46.84 Mbp. This QTL spans a 22-kb interval between 46,825,788 bp and 46,847,421 bp, as determined through both genome-wide association study (GWAS) and QTL linkage mapping. Three SNP markers, SL4.0ch11_46825788, SL4.0ch11_46847421, and SL4.0ch11_46850215, demonstrated the most significant association with high LOD values (LOD = 13 in the Blink model) in GWAS analysis. In this genomic region, two disease resistance gene analogs, Solyc11g062150 (TIR-NBS-LRR resistance protein, Toll-Interleukin receptor) and Solyc11g062180 (disease resistance protein, leucine-rich repeat), were identified, which may serve as candidates for ToBRFV resistance. The QTL identified in this study could be valuable for plant breeders in facilitating tomato breeding with ToBRFV resistance.

Agriculture↗
DOE OSTI2024

Hot, cold, or just right? An infrared biometric sensor to improve occupant comfort and reduce overcooling in buildings via closed-loop control

To improve occupant comfort and save energy in buildings, we have developed a closed-loop air conditioning (AC) sensor-controller that predicts occupant thermal sensation from the thermographic measurement of skin temperature distribution, then uses this information to reduce overcooling (cooling-energy overuse that discomforts occupants) by regulating AC output. Taking measures to protect privacy, it combines thermal-infrared (TIR) and color (visible spectrum) cameras with machine vision to measure the skin-surface temperature profile. Since the human thermoregulation system uses skin blood flow to maintain thermoneutrality, the distribution of skin temperature can be used to predict warm, neutral, and cool thermal states. We conducted a series of human-subject thermal-sensation trials in cold-to-hot environments, measuring skin temperatures and recording thermal sensation votes. We then trained random-forest classification machine-learning models (classifiers) to estimate thermal sensation from skin temperatures or skin-temperature differences. The estimated thermal sensation was input to a proportional integral (PI) control algorithm for the AC, targeting a sensation level between neutral and warm. Our sensor-controller includes a sensor assembly, server software, and client software. The server software orients the cameras and transmits images to the client software, which in turn assesses occupant skin temperature distribution, estimates occupant thermal sensation, and controls AC operation. A demonstration conducted in a conference room in an office building near Houston, TX showed that our system reduced overcooling, decreasing AC load by 42% when the room was occupied while improving occupant comfort (fraction of “comfortable” votes) by 15 percentage points.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗