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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

LaSRC (Land Surface Reflectance Code): Overview, Application and Validation Using MODIS, VIIRS, LANDSAT and Sentinel 2 Data's

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This technique builds on the extensive dataset acquired by the Terra platform by combining MODIS and MISR to derivean explicit and dynamic map of band ratio's between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. We will present the generic approach and the application to MODIS VIIRS, LANDSAT and Sentinel 2 data's and its validation using the AERONET data.

validation↗
NASA NTRS2008

The Use of Simulated Visible/Infrared Imager/Radiometer Suite (VIIRS) and Landsat Data Continuity Mission (LDCM) Imagery for Coral Reef Monitoring

Coral reefs are some of the most biologically rich and economically important ecosystems on Earth. Coral reefs are Earth's largest biological structures and have taken thousands of years to form. Coral reefs not only provide important habitat for many marine animals and plants, but they also provide humanity with food, jobs, chemicals, protection against storms, and life-saving pharmaceuticals. Severe bleaching events have occurred that have dramatic long-term ecological impacts to corals, including loss of reef-building corals, changes in benthic habitat, and, in some cases, changes in larval fish populations (Holden and Ledrew, 1998). Some researchers suggest that 10 percent of Earth s coral reefs have already been destroyed and that another 60 percent are in danger. Scientists have proposed that as much as 95 percent of Jamaica's reefs are dying or dead. This poster reports on a Rapid Prototyping Capability (RPC) experiment done to determine whether future NASA sensors - the Visible/Infrared Imager/Radiometer Suite (VIIRS) and Landsat Data Continuity Mission (LDCM) - could generate key data products for the Integrated Coral Reef Observation Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST) operated by the National Oceanic and Atmospheric Administration (NOAA).

Estep, L.↗
NASA NTRS2012

Evaluation and Validation of Global Land Surface Products Derived from Landsat, MODIS, and VIIRS

Data at medium and coarse resolution from the Landsat, MODIS, and VIIRS instruments provide crucial and indispensable time-series for the land component of the study of global change. This talk will be divided into two main sections. In the first part, a summary of the status of the processing, archiving, and early (Launch +6 months) on-orbit evaluation of the VIIRS Land Environmental Data Records (EDRs), will be presented. In the second part, results from an uncertainty analysis of MODIS- and Landsat-based albedo retrievals, based on collocated comparisons with tower and airborne multiangular measurements collected at the Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC'07), will be discussed.

Roman, Miguel O.↗
NASA NTRS2018

Evaluation of the Land Surface Reflectance Fundamental Climate Data Record

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. In this presentation, we present the validation of the Land surface reflectance used for MODIS, VIIRS, Landsat 8 and Sentinel 2 data. This methodology uses the 6SV Code and data from the AERONET network. The overall accuracy clearly reaches the satellite specifications. To understand how to improve the validation, we developed an exhaustive error budget. Results show an impact of the absorption of aerosol and of the fine mode volume concentration.

Atmospheric correction↗
NASA NTRS2016

Interactive Computing and Processing of NASA Land Surface Observations Using Google Earth Engine

Google's Earth Engine offers a "big data" approach to processing large volumes of NASA and other remote sensing products. h\ps://earthengine.google.com/ Interfaces include a Javascript or Python-based API, useful for accessing and processing over large periods of record for Landsat and MODIS observations. Other data sets are frequently added, including weather and climate model data sets, etc. Demonstrations here focus on exploratory efforts to perform land surface change detection related to severe weather, and other disaster events.

earth engine↗
NASA NTRSDate not supplied

Additional characterization of Libya-4 in support of post-launch vicarious calibration of satellite imagers

Libya-4 (28.55° N and 23.39° E) is one of the most characterized and utilized Pseudo Invariant Calibration Site (PICS) for post-launch radiometer drift monitoring and sensor pair radiometric scaling. Libya-4 is one of the driest and most reflective PICS located in an extensive sand dune region void of any vegetation with an elevation of 118 m. It is positioned near the northeast border with Egypt. With minimal cloud cover and the monthly mean precipitation of ~ 1mm, Libya-4 is one of the temporally, spectrally, and spatially stable CEOS recommended PICS and Cosnefroy et al. 1996 identified sites. The Libya-4 PICS has been extensively used for post-launch radiometric calibration and validation of high-, medium, and low-resolution satellite imagers, including Landsat, MODIS, VIIRS, and Meteosats. The CERES Imager and Geostationary Calibration Group (IGCG) at NASA LaRC utilizes Libya-4 to perform an independent assessment of the radiometric stability of the MODIS and VIIRS L1B products. The site is also used for absolute radiometric scaling between MODIS, VIIRS, and geostationary imagers to ensure consistent cloud and radiative flux retrievals. Multi-year Terra-MODIS, Aqua-MODIS , NPP-VIIRS and Metoesat-7 observations over Libya-4 show very similar TOA reflectance temporal variability. Although, the surface reflectance and atmospheric column varies seasonally, the inter-annual variability of the seasonal cycle should be small. Especially during 2013, the Libya-4 TOA reflectance was found to be greater than usual in all 4 satellite records. Preliminary comparisons with mean wind speed and aerosol optical depth (AOD) indicate that the year 2013 is marked by elevated levels of both conditions. The goal of this study is to tie the Libya-4 visible reflectance inter-annual variability with corresponding meteorological measurements to further improve the characterization of the site.

David R. Doelling↗
NASA NTRSDate not supplied

Consistent Pixel Resolution Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides global TOA shortwave and longwave fluxes for climate monitoring and validation that spans over 20 years. CERES utilizes broadband fluxes derived from geostationary (GEO) imagers to estimate broadband fluxes between the CERES observations. In order for these fluxes to be viable, the GEO imager calibration must be stable over time. One such calibration method used by CERES is to evaluate ensemble sets of deep convective clouds (DCC) as invariant targets (IT) over time. DCC targets can also provide radiometric scaling between sensors. An international collaboration through GSICS is also evaluating the DCC-IT calibration methodology to provide consistent calibration coefficients across geostationary sensors. Tropical DCC are the coldest, brightest, and most Lambertian TOA Earth targets identified using a window channel brightness temperature threshold. The DCC-IT technique involves a large ensemble of TOA pixel-level reflectances, which are binned into probability density functions (PDF). The PDF structure dependency on sensor pixel resolution, which can vary greatly among sensors, is not well known. This study will identify the impact of pixel resolution on the DCC PDFs by aggregating VIIRS and Landsat OLI/TIRS pixel resolutions into various coarser pixel resolutions and comparing the shape and statistics of the resulting PDFs. This study should assist in mitigating the pixel resolution dependency in the DCC-IT approach for providing scaling factors between sensors.

Conor Haney↗
NASA NTRS2017

On-Orbit Measurement of the Focal Length of the SNPP VIIRS Instrument

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is a whiskbroom system with 22 spectral bands split between 16 moderate resolution bands (M-bands), five imagery resolution bands (I-bands) and a panchromatic day-night band. Latitude and Longitude geolocation data are generated for each pixel at the M-band, I-band and day-night band spatial resolutions based upon various instrument parameters including focal length. In this study we measure the focal length of the VIIRS instrument from on-orbit data. This is achieved by simulating VIIRS band I2 using Landsat 8 OLI band 5 utilizing the VIIRS instrument system point spread function (PSF) and geolocation data generated with varying values of focal length. The focal length value that produces the highest spatial correlation between the original and simulated VIIRS data is taken to be the measured instrument focal length.

Image analysis↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the AquaMODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical D CC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

DCC↗
NASA NTRS2007

Coral Reef Remote Sensing using Simulated VIIRS and LDCM Imagery

The Rapid Prototyping Capability (RPC) node at NASA Stennis Space Center, MS, was used to simulate NASA next-generation sensor imagery over well-known coral reef areas: Looe Key, FL, and Kaneohe Bay, HI. The objective was to assess the degree to which next-generation sensor systems the Visible/Infrared Imager/Radiometer Suite (VIIRS) and the Landsat Data Continuity Mission (LDCM) might provide key input to the National Oceanographic and Atmospheric Administration (NOAA) Integrated Coral Observing Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST). The DST data layers produced from the simulated imagery concerned water quality and benthic classification map layers. The water optical parameters of interest were chlorophyll (Chl) and the absorption coefficient (a). The input imagery used by the RPC for simulation included spaceborne (Hyperion) and airborne (AVIRIS) hyperspectral data. Specific field data to complement and aid in validation of the overflight data was used when available. The results of the experiment show that the next-generation sensor systems are capable of providing valuable data layer resources to NOAA's ICON/CREWS DST.

Estep, Leland↗
NASA NTRS2008

Coral Reef Remote Sensing Using Simulated VIIRS and LDCM Imagery

The Rapid Prototyping Capability (RPC) node at NASA Stennis Space Center, MS, was used to simulate NASA next-generation sensor imagery over well-known coral reef areas: Looe Key, FL, and Kaneohe Bay, HI. The objective was to assess the degree to which next-generation sensor systems-the Visible/Infrared Imager/Radiometer Suite (VIIRS) and the Landsat Data Continuity Mission (LDCM)- might provide key input to the National Oceanographic and Atmospheric Administration (NOAA) Integrated Coral Observing Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST). The DST data layers produced from the simulated imagery concerned water quality and benthic classification map layers. The water optical parameters of interest were chlorophyll (Chl) and the absorption coefficient (a). The input imagery used by the RPC for simulation included spaceborne (Hyperion) and airborne (AVIRIS) hyperspectral data. Specific field data to complement and aid in validation of the overflight data was used when available. The results of the experiment show that the next-generation sensor systems are capable of providing valuable data layer resources to NOAA s ICON/CREWS DST.

Estep, Leland↗
NASA NTRSDate not supplied

Ground control points refresh for MODIS and VIIRS geolocation monitoring

The Control Point Matching (CPM) program and a set of over 1200 globally distributed ground control points (GCPs ) have been successfully used to develop more than 20 years of MODIS geolocation products. In this research, we refresh current GCP library with more than 2500 new GCPs using the latest Landsat 8 Collection 2 images. The refreshed GCPs are distributed from 56 S to 80 N latitude, with more than 2000 shoreline and 500 inland GCP chips. The size of these GCPs are extended from800*800 to 1400*1400 Landsat pixels and the CPM program correspondingly increase s t h e searching distance from 0.8 pixels to 2.5 pixels, which also extends the geolocation error measurement from +/-45 to the edge of scan at +/-55 degree in scan angle. This will allow the algorithm to catch geolocation errors that are larger than one MODIS pixel. The geolocation errors measured with the refreshed GCP library are comparable to the previous results, yet with 2-3more times of matched GCPs. The daytime Aqua ascending orbits and Terra descending orbits enable us to identify a few GCP outliers which might be due to the quality of the original Landsat images. Most importantly, the refreshed GCP library will include images from both Landsat band 4 to match with VIIRS I1, and Landsat band 6 to match with VIIRS I3. This will allow us to measure and correct on orbit band-to-band registration at both track and scan directions, which will help understanding and improving future JPSS mission’s prelaunch geometric performance.

VIIRS↗
NASA NTRS2021

Evaluation of VIIRS and MODIS snow cover fraction in High-Mountain Asia using Landsat 8 OLI

We present thefirst application of the Snow Covered Area and Grain size model (SCAG) tothe Visible Infrared imaging Radiometer Suite (VIIRS) and assess these retrievals withfiner-resolution fractional snow cover maps from Landsat 8 Operational Land Imager (OLI).Because Landsat 8 OLI avoids saturation issues common to Landsat 1–7 in the visiblewavelengths, we re-assess the accuracy of the SCAG fractional snow cover maps fromModerate Resolution Imaging Spectroradiometer (MODIS) that were previously evaluatedusing data from earlier Landsat sensors. Use of the fractional snow cover maps fromLandsat 8 OLI shows a negative bias of−0.5% for MODSCAG and−1.3% for VIIRSCAG,whereas previous MODSCAG evaluations found a bias of−7.6% in the Himalaya. Wefindsimilar root mean squared error (RMSE) values of 0.133 and 0.125 for MODIS and VIIRS,respectively. The Recall statistic (probability of detection) for cells with more than 15%snow cover in this challenging steep topography was found to be 0.90 for both MODSCAGand VIIRSCAG, significantly higher than previous evaluations based on Landsat 5Thematic Mapper (TM) and 7 Enhanced Thematic Mapper Plus (ETM+). In addition,daily retrievals from MODIS and VIIRS are consistent across gradients of elevation, slope,and aspect. Different native resolutions of the gridded products at 1 km and 500 m forVIIRS and MODIS, respectively, result in snow cover maps showing a slightly differentdistribution of values with VIIRS having more mixed pixels and MODIS having 7% morepure snow pixels. Despite the resolution differences, the snow maps from both sensorsproduce similar total snow-covered areas and snow-line elevations in this region, withR2values of 0.98 and 0.88, respectively. Wefind that the SCAG algorithm performsconsistently across various spatial resolutions and that fractional snow cover mapsfrom the VIIRS instruments aboard Suomi NPP, JPPS–1, and JPPS–2 can be asuitable replacement as MODIS sensors reach their ends of life.

Karl Rittger↗
NASA NTRS2017

On-Orbit Line Spread Function Estimation of the SNPP VIIRS Imaging System from Lake Pontchartrain Causeway Bridge Images

The visible infrared imaging radiometer suite (VIIRS) instrument was launched 28 October 2011 onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The VIIRS instrument is a whiskbroom system with 22 spectral and thermal bands split between 16 moderate resolution bands (M-bands), five imagery resolution bands (I-bands) and a day-night band. In this study we estimate the along-scan line spread function (LSF) of the I-bands and M-bands based on measurements performed on images of the Lake Pontchartrain Causeway Bridge. In doing so we develop a model for the LSF that closely matches the prelaunch laboratory measurements. We utilize VIIRS images co-geolocated with a Landsat TM image to precisely locate the bridge linear feature in the VIIRS images as a linear best fit to a straight line. We then utilize non-linear optimization to compute the best fit equation of the VIIRS image measurements in the vicinity of the bridge to the developed model equation. From the found parameterization of the model equation we derive the full-width at half-maximum (FWHM) as an approximation of the sensor field of view (FOV) for all bands, and compare these on-orbit measured values with prelaunch laboratory results.

Tilton, James C.↗
NASA NTRS2007

Regional Sediment Management Experiment Using the Visible/Infrared Imager/Radiometer Suite and the Landsat Data Continuity Mission Sensor

The central aim of this RPC (Rapid Prototyping Capability) experiment is to demonstrate the use of VIIRS (Visible/Infrared Imager/ Radiometer Suite and LDCM (Landsat Data Continuity Mission) sensors as key input to the RSM (Regional Sediment Management) GIS (geographic information system) DSS (Decision Support System). The project affects the Coastal Management National Application.

Estep, Leland↗