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At least 199 records · Page 11

Landsat 9: Mission Status and Prelaunch Instrument Performance Characterization and Calibration

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is essentially a rebuild of Landsat 8 and has the same two sensors, the Operational Land Imager (OLI) and the Thermal Imaging Sensor (TIRS). The OLI-2 on Landsat 9, is being built by Ball Aerospace and has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, being built by Goddard Space Flight Center, is currently undergoing testing through Spring 2019 and also scheduled for summer 2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas-5.

Markham, Brian↗

LANDSAT 9: Mission Status and Prelaunch Instrument Performance Characterization and Calibration

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is largely a rebuild of Landsat 8 and has the same two sensors, an Operational Land Imager (OLI) and a Thermal InfraRed Sensor(TIRS). The OLI-2 on Landsat 9, being built by Ball Aerospace, has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, with improved stray light performance and increased redundancy for improved reliability, is being built by Goddard Space Flight Center. TIRS-2is undergoing testing through Spring 2019 and is also scheduled for summer2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas V.

Landsat↗

Fairfax County Urban Development: Identifying Urban Heat Mitigation Strategies for Climate Adaptation Planning in Fairfax County, Virginia

Extreme high temperatures lead to increased instances of cardiovascular disease, pulmonary disease, and even death, as well as increased energy consumption and infrastructure costs. People in urbanized areas experience higher temperatures than rural areas due to diminished vegetation and increased impervious surfaces which absorb and radiate heat. Fairfax County, Virginia has embarked on Resilient Fairfax, a program aimed at addressing climate adaptation and resilience. The DEVELOP team partnered with the Fairfax County Office of Environmental and Energy Coordination (OEEC) to assess the extent of the urban heat island effect on the county and its most vulnerable populations. The team used data from Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), as well as the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) for the years 2013 to 2021 and found that the hottest spots were in densely urbanized areas, with temperatures as much as 47°F above that of undeveloped reference areas. The team used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model and determined that areas with higher tree canopy cover had greater heat mitigation capacity. Estimates from the InVEST model showed that a 4.5% increase in canopy cover across the county could result in a temperature reduction of up to 2.4°F in some areas. The results will allow partners to assess heat distribution across Fairfax County and implement effective mitigation strategies, including locating prime locations for cooling centers and increasing canopy cover.

W. Pierce Holloway↗

Landsat-8 TIRS Thermal Radiometric Calibration Status

The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/JPL and RIT since launch. Soon after launch, it was discovered that the instrument had a significant stray light effect that was affecting the radiometric calibration. The stray light was corrected in the processing system in 2017. Since then, it has become apparent that there was an additional radiometric error, based on the vicarious calibration results. With a failure within the primary electronic system and subsequent switch to the redundant electronic system, the TIRS instrument effectively has two separate calibration regimes. The vicarious calibration found a statistically significant calibration error, primarily a constant over time, in Band 11 on the primary electronics (Feb 11,2013 through March 5,2015) of about -0.6K at 300K. The calibration error in Band 10 was smaller though still statistically significant at about 0.2K at 300K. On the redundant side(March 5,2015 to present), the calibration error is more signal dependent than time dependent. Both bands are affected, with Band 10 having an error between 1K and -0.4K (between 273-320K) and Band 11 having an error between 0.8K and -1.44K (between 273-320K).This calibration error will be corrected within the USGS Landsat Product Generation System with the release of Landsat Collection-2 products. The Collection-2 release also includes a correction to the relative radiometric calibration of TIRS data. Striping as a result of poor detector-to-detector normalization has been increasing in the imagery since launch. The TIRS relative radiometric calibration will be updated based on internal calibrator data to remove the stripes on a quarterly basis. The visible stripes are generally at 0.1-0.2% level, though there are some detectors in each band that have changed by 1% or more. The Collection-2 release will result in much more uniform TIRS images.

Julia A Barsi↗

Landsat 9: Status and Plans

The Landsat 9 mission, currently under development and proceeding towards a targeted launch in late 2020, will be very similar to the Landsat 8 mission, launched in 2013. Like Landsat 8, Landsat 9 is a joint effort between NASA and USGS with two sensors, the Operational Land Imager 2 (OLI-2), essentially a copy of the OLI on Landsat 8 and the Thermal Infrared Sensor 2 (TIRS-2), very similar to the TIRS on Landsat 8. The OLI-2, like OLI, provides 14-bit image data, though for Landsat 9, all 14 bits will be retained and transmitted to the ground. The focal plane modules to be used for OLI-2 were flight spares for OLI and are currently being retested by Ball Aerospace. Results indicate radiometric performance comparable to OLI. The TIRS was a class C instrument, with a 3-year design lifetime, and therefore had limited redundancy. TIRS-2 will be a class B instrument, with a 5-year design lifetime, like OLI (and OLI-2), necessitating design changes to increase redundancy. The stray light and Scene Select Mechanism (SSM) encoder problems observed on orbit with TIRS have also instigated a few design changes to TIRS-2. Stray light analysis and testing have indicated that additional baffles in the TIRS-2 optical system will suppress the out-of-field response. The SSM encoder problems have not been definitively traced to a route cause, though conductive anodic filament growth in the circuit boards is suspected. Improved designs for the encoder are being considered for TIRS-2. The spare Focal Plane Array (FPA) from TIRS is planned for use in TIRS-2; FPA spectral and radiometric performance testing is scheduled for September of this year at NASA's Goddard Space Flight Center.

Landsat↗

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↗

Virtual Sensors Determined Through Machine Learning

We propose a method that increases the capability of a conventional sensor/instrument, transforming it into an enhanced virtual sensor/instrument. This paper focuses on a virtual thermal IR sensor based on a conventional visual (RGB) sensor. The estimation of thermal IR images can enhance the ability of terrain classification, which is crucial for autonomous navigation of rovers. The estimate in IR from visual band has inherent limitations, as these are different bands, yet correlations between visual/RGB and thermal IR images exist, as different terrains, which visually may appear different, also have different thermal inertia. We developed a deep learning-based algorithm that estimates thermal IR images from RGB images of terrains, providing the feasibility of the idea with average 1.21 error [degree].

Kurazume, Ryo↗

LDCM Preliminary Thermal Trades

The expected cost of adding thermal bands to the next generation Landsat Data Continuity Mission (LDCM) could be significant. This viewgraph presentation investigates both traditional cooled cross-track scanners and new architectures (cooled and uncooled) which could enable a low cost thermal capability. The presentation includes surveys of applications of Landsat thermal data and the architecture of thermal instruments. It also covers new thermal architecture sensor trades, ALI Architecture with Uncooled TIR Detectors, and simulated thermal imagery.

Ryan, Robert↗

Sarasota Climate: Monitoring Heat and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

The coastal county of Sarasota, Florida, is located within the humid subtropical climate region and experiences an average of 250 days of sunshine every year. The county has large, urbanized communities which are vulnerable to urban heat island (UHI) effects. These rapidly growing communities contribute to the increasing surface temperatures and placing more residents at risk of heat-related illness. In partnership with Sarasota County Sustainability, the Sarasota Climate team utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS), and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the Summer for the last five years, 2019 to 2023. Data analysis with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Urban Heat Exposure Assessment Tempe 1.0 (UHEAT 1.0) models and within ModelBuilder produced maps that identified the land surface temperature (LST) variance within the county, the regions that are most susceptible to extreme heat, and areas least capable of mitigating the effects of UHI. The results revealed that heat intensity varies significantly across Sarasota County with the highest temperatures in the more developed western part of the county. Additionally, the team identified that there are at least three vulnerable communities that exist in high-heat regions, including North Sarasota, Venice, and North Port. These regions have an overlap between socioeconomic sensitivity and environmental hazard that indicate a high priority in future heat mitigation efforts.

Remote sensing↗

Monitoring and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

Located in the coastal subtropical region, Florida’s Sarasota County receives plenty of sunlight for more than half of the year. However, the ongoing rise in summer temperatures attributed to climate change poses an increasing vulnerability to extreme heat for the residents. Moreover, the area's high relative humidity exacerbates the discomfort of high temperatures, thereby intensifying the severity of heat events and elevating the risks of heat-related illnesses. Our collaborations with Sarasota County Sustainability underscore shared concerns about the impact of urban heat island (UHI) on the community. We utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS) and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the summer from 2019 to 2023. By implementing the open-source Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling software model, ArcGIS ModelBuilder, and principal component analysis, we identified the land surface temperature variance within the county and areas that are least capable of mitigating the effects of UHI. In addition, we use socioeconomic and demographic data as indicators to quantify vulnerability at the census tract level. The results revealed that heat intensity varies significantly across Sarasota County, with the highest temperatures being in the more developed western part of the region. We pinpointed that at least three vulnerable communities reside in high-heat regions: North Sarasota, Venice, and North Port. These areas demonstrate a confluence between socioeconomic sensitivity and environmental hazard, indicating a high priority in future heat mitigation efforts.

Theresia Phoa↗

The 2019-2020 Australian drought and bushfires altered the partitioning of hydrological fluxes

Though coarse in spatial resolution, the nearly all weather measurements from passive microwave sensors can help in improving the spatiotemporal coverage of optical and thermal infrared sensors for monitoring vegetation changes on the land surface. This study demonstrates the use of vegetation optical depth retrievals from the Soil Moisture Active Passive mission for capturing the vegetation alterations from the recent 2019-2020 Australian bushfires and drought. The impact of vegetation disturbance s on terrestrial water budget is examined by assimilating the vegetation optical depth retrievals into a dynamic phenology model. The results demonstrate that assimilating vegetation optical depth observations lead to improved simulation of evapotranspiration, runoff, and soil moisture states. The study also demonstrates that the vegetation changes from the 2019-2020 Australian drought and fires led to significant modifications in the partitioning of evaporative and runoff fluxes, resulting in increased bare soil evaporation, reduced transpiration, and higher runoff.

data assimilation↗

Analysis of the transient calibration of heat flux sensors: One dimensional case

The effect of transient heat flux on heat flux sensor response and calibration is analyzed. A one dimensional case was studied in order to elucidate the key parameters and trends for the problem. It has the added advantage that the solutions to the governing equations can be obtained by analytic means. The analytical results obtained to date indicate that the transient response of a heat flux sensor depends on the thermal boundary conditions, the geometry and the thermal properties of the sensor. In particular it was shown that if the thermal diffusivity of the sensor is small, then the transient behavior must be taken into account.

Dybbs, A.↗

Augmented Method to Improve Thermal Data for the Figure Drift Thermal Distortion Predictions of the JWST OTIS Cryogenic Vacuum Test

The JWST Optical Telescope Element (OTE) assembly is the largest optically stable infrared-optimized telescope currently being manufactured and assembled, and is scheduled for launch in 2018. The JWST OTE, including the 18 segment primary mirror, secondary mirror, and the Aft Optics Subsystem (AOS) are designed to be passively cooled and operate near 45K. These optical elements are supported by a complex composite backplane structure. As a part of the structural distortion model validation efforts, a series of tests are planned during the cryogenic vacuum test of the fully integrated flight hardware at NASA JSC Chamber A. The successful ends to the thermal-distortion phases are heavily dependent on the accurate temperature knowledge of the OTE structural members. However, the current temperature sensor allocations during the cryo-vac test may not have sufficient fidelity to provide accurate knowledge of the temperature distributions within the composite structure. A method based on an inverse distance relationship among the sensors and thermal model nodes was developed to improve the thermal data provided for the nanometer scale WaveFront Error (WFE) predictions. The Linear Distance Weighted Interpolation (LDWI) method was developed to augment the thermal model predictions based on the sparse sensor information. This paper will encompass the development of the LDWI method using the test data from the earlier pathfinder cryo-vac tests, and the results of the notional and as tested WFE predictions from the structural finite element model cases to characterize the accuracies of this LDWI method.

Thermal Modeling↗

Active Thermal Isolation For Hot-Film Anemometers

Local heating compensates for conduction of heat from sensors into modules. Two hot-film sensors stacked on wind-tunnel model. Outer sensor detects changes in boundary-layer flow. Inner sensor provides active thermal isolation between outer sensor and model. Thermal boundary condition controlled at response time of detection hot-film sensor, significantly less than response time of internally heated model. Requires less power to maintain outer hot-film sensor at given temperature, enabling system to respond over greater dynamic range before power limits of instrument reached. Stacked sensors bonded to surface of most wind-tunnel models, even to curved surfaces, and removed after completion of experiments.

Martinson, Scott D.↗

Thermal control for the ground simulation of a space IR sensor system

Active and passive thermal controls for simulations of a space IR sensor system operating in cryogenic temperatures were designed, built, and tested from a component level to a system level. The test results from component tests and integrated system tests have compared very well with theoretical predictions, and thus verify component and integrated thermal math models. These verified models can be modified for use to predict flight systems thermal performance. Thermal vacuum simulations and demonstrations of a space IR system consisted of a target and background scene generator, telescope mirrors supported by a graphite-epoxy metering structure, and an IR sensor. These components are required to operate at cryogenic temperature levels. Each component has its unique thermal control needs. Descriptions are presented of thermal control systems for the test article from component design level to integrated system level along with discussions of component and integrated demonstration tests, and correlation of test data with thermal finite difference models.

Lee, E.↗

Reassessment of net radiation measurements in the atmosphere of Venus

An analysis was performed of the possible error mechanisms which degraded the IR net flux measurements made by the three small atmospheric probes dispatched from the Pioneer Venus spacecraft. The larger errors began below 30 km, and caused the data to be inconsistent with previous estimates of the atmospheric opacity. Evaluations were made of the possible radiation field perturbations behind each probe, cloud particle deposition on the sensor windows, and thermal disturbances within the sensors because of gas flow through the window retainers. The gas flow through the retainers was identified as the most likely error source, and was demonstrated in laboratory tests. A strong Reynolds number dependence was also found. Radiative transfer calculations were performed to account for the errors, using the constraints defined by the tests. Upper and lower bounds were calculated for the true net flux for both day and night conditions.

Revercomb, H. E.↗

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses, and the validation of the results.

Schieldge, John↗