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NASA NTRS2018

Harmonized Landsat/Sentinel-2 Products for Land Monitoring

The Harmonized Landsat-8 and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless, harmonized surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function normalization and bandpass adjustment. As of version 1.3, the HLS v1.3 data set covers 9.12 million km2 and spans from first Landsat-8 data (2013) to present. HLS products provide near-daily surface reflectance information with a common geometric framework, and are suitable for a variety of agricultural and vegetation monitoring tasks, including analysis of crop type, condition, and phenology.

Masek, Jeffrey↗
NASA NTRS2012

HyspIRI Cloud Mask Detection Algorithm Theoretical Basis Document

The Hyperspectral Infrared Imager (HyspIRI) satellite includes a thermal infrared (TIR) multispectral scanner with seven spectral bands in the thermal infrared (TIR) between 7 and 12 μm and one band in the mid-infrared between 3 and 5 μm designed to measure hot targets. The TIR bands have a NEΔT of <0.2 K at 300K and all bands have a spatial scale of 60 m. The two primary Level-2 products that will be generated by HyspIRI TIR data are land surface temperature and emissivity. A critical aspect of minimizing uncertainties in these products and in generating global Level-3 products is an accurate and reliable cloud mask algorithm. This document describes the methodology behind developing the HyspIRI Cloud Mask Algorithm (HyCMA), and challenges associated with cloud detection. The HyCMA will derive its heritage from previously well established cloud mask algorithms such as the Landsat ACCAA, MODIS MOD35 and AVHRR.

Hook, Simon J.↗
NASA NTRSDate not supplied

Air Quality Forecasting at Sub-City Scale by Combining Models, Satellites, and Surface Measures

While there are a variety of sources for air quality information, no one source simultaneously allows for high accuracy, low bias, fine spatial resolution, wide spatial coverage, high temporal frequency, and the capability for near-term forecasting of air quality. Global models, like the NASA’s Goddard Earth Observing System -Composition Forecasting (GEOS-CF) model, provide global coverage and forecasting capabilities, but operate at relatively coarse spatial resolution and require ground-truthing with in-situ data. Polar-orbiting satellite data products, like those of the ESA TROPOspheric Monitoring Instrument (TROPOMI), provide higher-spatial-resolution remote sensing of atmospheric composition, but are limited by cloud cover and overpass times and report column-integrated quantities. Surface measurements, both from regulatory-grade monitors and low-cost networks, measure “nose-level” air quality, but may not represent concentration variability across large spatial domains, and (in the case of low-cost sensors) are subject to interference and biases. There exists a great potential to combine these diverse data sources together, using the strengths of some to offset the weaknesses of others to build a more comprehensive picture of air quality. This presentation will summarize results from ongoing efforts to produce such a combined forecast, with application case studies for surface-level Nitrogen Dioxide forecasting in several major US cities. Furthermore, we will examine the relative impacts and benefits of different data sources on the forecasting accuracy at different spatial and temporal scales. Finally, we will examine the potential for integrating low-cost sensors into such a system, both in terms of using these integrated air quality estimates as a baseline from which to calibrate networks of low-cost sensors in the field, and in terms of using dense networks of low-cost sensors to refine the spatial resolution of integrated air quality forecasts.

Air Quality↗
NASA NTRSDate not supplied

GeoNEX: A Geostationary Earth Observatory

The latest generation of geostationary satellites (Himawari 8/9, GOES-16/17, FY-4, GK-2A) carries sensors that closely mimic the spatial and spectral characteristics of widely used polar-orbiting, global monitoring sensors such as MODIS and VIIRS. When combined, data from various currently operating/planned geostationary platforms provide a geo-ring of hyper-temporal (5-10 minutes), multispectral observations at spatial resolutions as high as 500 m. These high frequency observations offer exciting new possibilities for monitoring our planet, including better retrievals of geophysical variables by overcoming cloud cover, enabling studies of diurnally varying phenomena in the atmosphere, land, and the oceans, and support operational decision-making in agriculture, hydrology and disaster management. The NASA Earth Exchange (NEX) team, in collaboration with scientists from JAXA, KARI, NOAA and other international institutions, created the GeoNEX (www.nasa.gov/geonex) pipeline to integrate data from all available geostationary platforms and produce and distribute spatially, temporally, and radiometrically consistent data for the earth science community. We envision various institutions adapting the Geo component (e.g., GeoNOAA, GeoKARI, GeoChiba, GeoJAXA, GeoCMA) and customizing the pipeline and downstream products to serve the local/regional research and applied science communities. To facilitate collaborative work among the partners, we have established the OpenNEX platform on the public cloud. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of GeoNEX data assets and software tools.

GeoNEX↗
NASA NTRS2018

NASA's Land, Atmosphere Near Real-Time Capability for EOS (LANCE): Delivering Data and Imagery to Meet the Needs of Near Real-Time Applications

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery from the AIRS, AMSR2, LIS (ISS), MISR, MLS, MODIS, MOPITT, OMI, OMPS, and VIIRS instruments, to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made phenomena. NRT imagery from LANCE are available through NASA's Global Imagery Browse Services (GIBS), Worldview, FIRMS and most recently through Worldview Snapshots – a low band width application that has replaced the Rapid Response Subsets. Over the past year: data and imagery from the Lightning Imaging Sensor (LIS) on board the International Space Station (ISS), OMPS and VIIRS-Land have been added to LANCE. In the coming year LANCE will integrate the MODIS NRT Global Flood product, VIIRS Black Marble nighttime lights and Cloud Mask and Aerosol Dark Target from VIIRS Atmosphere. Here we provide a brief overview of LANCE, focusing on what's new and describing how these new data sets have been used to monitor lightning flashes, hurricanes and fires. For more information on LANCE visit: https://earthdata.nasa.gov/lance.

Davies, Diane↗
NASA NTRS2015

Evaluating a New Homogeneous Total Ozone Climate Data Record from GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A

The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality ozone data products generated from different satellite sensors. For total ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the total ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI total ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Système D′Analyse par Observations Zénithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 total ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI total ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 plus or minus 1 percent level for all three sensors while the near-zero decadal stability of the total ozone columns (TOCs) provided by the three European instruments falls well within the 1-3 percent requirement of the European Space Agency's Ozone Climate Change Initiative project.

Satellite sensors↗
NASA NTRS1989

The neutral cloud and heavy ion inner torus at Saturn

Voyager plasma data are used in conjunction with laboratory data on water molecule sputter-yields and energy distributions to calculate the morphology of the Saturn neutral water molecule and dissociated water molecule-product torus coexisting with the E-ring and icy satellites of this planet. Plasma production rates determined for this cloud exhibit a structure with distance from Saturn as well as from the orbit plane; this suggests a lack of equilibrium for the heavy ion plasma at less than 7 planet radii. Attention is given to the possibility that the Saturn E-ring may be a precipitate of the neutral cloud that is initiated by low-energy ion-molecule reactions.

Johnson, R. E.↗
NASA NTRS2000

UV 380 nm Reflectivity of the Earth's Surface

The 380 nm radiance measurements of TOMS (Total Ozone Mapping Spectrometer) have been converted into a global data set of daily (1979 to 1992) Lambert equivalent reflectivities R of the Earth's surface and boundary layer (clouds, aerosols, surface haze, and snow/ice). Since UV surface reflectivity is between 2 and 8% for both land and water during all seasons of the year (except for ice and snow cover), reflectivities larger than the surface value indicates the presence of clouds, haze, or aerosols in the satellite field of view. Statistical analysis of 14 years of daily data show that most snow/ice-free regions of the Earth have their largest fraction of days each year when the reflectivity is low (R less than 10%). The 380 nm reflectivity data shows that the true surface reflectivity is 2 to 3% lower than the most frequently occurring reflectivity value for each TOMS scene. The most likely cause of this could be a combination of frequently occurring boundary-layer water or aerosol haze. For most regions, the observation of extremely clear conditions needed to estimate the surface reflectivity from space is a comparatively rare occurrence. Certain areas (e.g., Australia, southern Africa, portions of northern Africa) are cloud-free more than 80% of the year, which exposes these regions to larger amounts of UV radiation than at comparable latitudes in the Northern Hemisphere. Regions over rain-forests, jungle areas, Europe and Russia, the bands surrounding the Arctic and Antarctic regions, and many ocean areas have significant cloud cover (R greater than 15%) more than half of each year. In the low to middle latitudes, the areas with the heaviest cloud cover (highest reflectivity for most of the year) are the forest areas of northern South America, southern Central America, the jungle areas of equatorial Africa, and high mountain regions such as the Himalayas or the Andes. The TOMS reflectivity data show the presence of large nearly clear ocean areas and the effects of the major ocean currents on cloud production.

Herman, J. R.↗
NASA NTRS2004

MODIS Direct Broadcast and Remote Sensing Applications

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

Tsay, Si-Chee↗
NASA NTRS2007

Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS): Imaging and Tracking Capability

The geosynchronous-imaging Fourier transform spectrometer (GIFTS) engineering demonstration unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 microns, 6.0 to 4.4 microns) using two 128 128 detector arrays with a spectral resolution of 0.57/cm with a scan duration of approx. 11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which atmospheric status, cloud parameters, wind field profiles, and other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated its extensive capabilities and potential for geosynchronous and other applications (e.g., Earth observing environmental measurements). This paper addresses the experiment objectives and overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept.

Zhou, D. K.↗
NASA NTRS2007

Ground-Based Measurement Experiment and First Results with Geosynchronous-Imaging Fourier Transform Spectrometer Engineering Demonstration Unit

The geosynchronous-imaging Fourier transform spectrometer (GIFTS) engineering demonstration unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 microns, 6.0 to 4.4 microns) using two 128 x 128 detector arrays with a spectral resolution of 0.57 cm(exp -1) with a scan duration of approximately 11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which atmospheric status, cloud parameters, wind field profiles, and other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated its extensive capabilities and potential for geosynchronous and other applications (e.g., Earth observing environmental measurements). This paper addresses the experiment objectives and overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept.

Zhou, Daniel K.↗
NASA NTRS2014

Stereoscopic Retrieval of Smoke Plume Heights and Motion from Space-Based Multi-Angle Imaging, Using the MISR INteractive eXplorer(MINX)

Airborne particles desert dust, wildfire smoke, volcanic effluent, urban pollution affect Earth's climate as well as air quality and health. They are found in the atmosphere all over the planet, but vary immensely in amount and properties with season and location. Most aerosol particles are injected into the near-surface boundary layer, but some, especially wildfire smoke, desert dust and volcanic ash, can be injected higher into the atmosphere, where they can stay aloft longer, travel farther, produce larger climate effects, and possibly affect human and ecosystem health far downwind. So monitoring aerosol injection height globally can make important contributions to climate science and air quality studies. The Multi-angle Imaging Spectro-Radiometer (MISR) is a space borne instrument designed to study Earths clouds, aerosols, and surface. Since late February 2000 it has been retrieving aerosol particle amount and properties, as well as cloud height and wind data, globally, about once per week. The MINX visualization and analysis tool complements the operational MISR data products, enabling users to retrieve heights and winds locally for detailed studies of smoke plumes, at higher spatial resolution and with greater precision than the operational product and other space-based, passive remote sensing techniques. MINX software is being used to provide plume height statistics for climatological studies as well as to investigate the dynamics of individual plumes, and to provide parameterizations for climate modeling.

aerosols↗
NASA NTRS2019

Surface Height and Sea Ice Freeboard of the Arctic Ocean from ICESat-2: Characteristics and Early Results

We present the first winter season of surface height and sea ice freeboards of the Arctic Ocean from the new ICESat-2 (IS-2) mission. The Advanced Topographic Laser Altimeter System (ATLAS) onboard has six photon-counting beams for surface profiling with a 10-kHz pulse-rate (inter-pulse distance ~0.7m) and footprints of ~17m. Geolocated heights assigned to individual photons scattered from the surface allow significant flexibility in the construction of height distributions used in surface finding. For IS-2 sea ice products, a fixed 150-photon aggregate is used to control height precision and obtain better along-track resolution over high reflectance surfaces. Quasi-specular returns in openings as narrow as ~27m, crucial for freeboard calculations, are resolved. The fixed photon aggregate results in unique variable along-track resolutions and non-uniform sampling (17m x 27m to 17m x 200m for the strong beams) of the surface. The six profiling beams – three pairs separated by 3.3 km with a strong and weak beam in each pair – provide correlated statistics at regional length scales for assessment of beam-to-beam retrieval consistency and accuracy. Analysis shows along-track height precisions of ~2cm, and agreement in the monthly freeboard distributions across the strong beams to 1-2cm. In this paper, we describe briefly the approaches used in surface height and freeboard retrievals from ATLAS photon clouds, and detail the key features of these along-track sea ice products, focusing on the first release of data collected over the Arctic Ocean, which spans the period between October 14, 2018 – the start of data collection – and the end of March 2019.

R Kwok↗
NASA NTRSDate not supplied

Comparison of the CALIPSO Level 3 Ice Cloud Product with the DARDAR and 2C-ICE products

Understanding the vertical distribution of ice clouds is crucial for climate modeling and weather forecasting. Since its launch to space in 2006, the Cloud-Aerosol Lidar with Orthogonal Polarization instrument (CALIOP) onboard the CALIPSO spacecraft has been providing unprecedented high-quality profiles of ice clouds, especially optically thin cirrus clouds, during both day and night, on a global scale. Recently the lidar science working group at the NASA Langley Research Center delivered a level 3 (L3) ice cloud product which reports monthly statistics of ice cloud extinction coefficient and ice water content on a uniform 3-dimensional spatial grid. This presentation compares the ice cloud climatology derived from this product with two other ice cloud products, namely the raDAR/liDAR(DARDAR) ice cloud product and the CloudSat-CALIPSO Ice Cloud Property Product (2C-ICE). Using processing similar to the CALIPSO L3 product, granules of DARDAR and 2C-ICE data have been processed into monthly statistics for a better comparison. Similarities and differences will be presented and discussed. The findings illustrate the strengths of the different products and help to identify which product might be most appropriate for a given research topic.

Xia Cai↗
NASA NTRS1972

Project Fog Drops. Part 2: Laboratory investigations

Measurements of the total nucleus concentration and cloud condensation nuclei (CCN) were acquired for several conditions representing both high normal and severe pollution levels for the Los Angeles Basin as well as clean filtered air. The data show that in filtered air there is a large photochemically induced increase in the total particle content within a few minutes after starting the lamp. The concentration of CCN remains near zero, until sufficient coagulation and condensation occurs on the smaller Aitken particles. The addition of gaseous pollutants to filtered air results in large increases in the photochemical production of both the cloud and Aitken nucleus concentration. Fogs were also generated under controlled, reproducible conditions in the cloud chamber and seeded with aerosols of various compounds which form monomolecular surface films at air-water interfaces. Visibility characteristics and droplet data were obtained. The data suggest that droplet growth on treated nuclei can be retarded but fog formation was not significantly altered by the chemical seeding.

Kocmond, W. C.↗
NASA NTRS1997

Investigation of Cloud Properties and Atmospheric Profiles with Modis

A major milestone was accomplished with the delivery of all five University of Wisconsin MODIS Level 2 science production software packages to the Science Data Support Team (SDST) for integration. These deliveries were the culmination of months of design and testing, with most of the work focused on tasks peripheral to the actual science contained in the code. LTW hosted a MODIS infrared calibration workshop in September. Considerable progress has been made by MCST, with help from LTW, in refining the calibration algorithm, and in identifying and characterization outstanding problems. Work continues on characterizing the effects of non-blackbody earth surfaces on atmospheric profile retrievals and modeling radiative transfer through cirrus clouds.

Menzel, Paul↗
NASA NTRS2022

Comparisons Between the Distributions of Dust and Combustion Aerosols in MERRA-2, FLEXPART and CALIPSO and Implications for Deposition Freezing Over Wintertime Siberia

Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface (< ∼ 2 km) where FLEXPART may be overpredicting local dust emissions. Comparisons to ground data suggest that MERRA-2 Arctic dust concentrations can be improved by the addition of local dust sources. All three products predicted that wintertime dust and combustion aerosols occur most frequently over the same Siberian regions where diamond dust is most common in the winter. This suggests that dust aerosol impacts on ice phase processes may be particularly high over Siberia, although further wintertime model validation with non-CALIPSO observations is needed. This assessment paves the way for applying the model-based aerosol simulations to a range of regional-scale Arctic aerosol–cloud interaction studies with greater confidence.

MERRA-2↗
NASA NTRS1996

Second International Airborne Remote Sensing Conference and Exhibition

The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus cloud cover analysis, Quadantid meteor shower studies, extra-solar far infrared ionic structure lines measurement, Cape Kennedy launch support, and studies in air pollution, The Products and Services Exhibit showcased new sensor and image processing technologies, aircraft data collection services, unmanned vehicle technology, platform equipment, turn-key services, software a workstations, GPS services, publications, and processing and integration systems by 58 exhibitors. The participation of aircraft users and crews provided unique dialogue between those who plan data collection a operate the remote sensing technology, and those who supply the data processing and integration equipment. Research results using hyperspectral imagery, radar and optical sensors, lidar, digital aerial photography, a integrated systems were presented. Major research and development programs and campaigns we reviewed, including CNR's LARA Project and European Space Agency's 1991-1995 Airborne Campaign. The pre-conference short courses addressed airborne video, photogrammetry, hyperspectral data analysis, digital orthophotography, imagery and GIS integration, IFSAR, GPS, and spectrometer calibration.

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