Thunderstorms Producing Sferic‐Geolocated Gamma‐Ray Flashes Detected by TETRA‐II
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Deirdre Smith↗
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The CZCS geolocation algorithms
The Coastal Zone Color Scanner (CZCS) on board the Nimbus 7 satellite was designed to measure surface radiance upwelled from the ocean in 6 spectral bands. The CZCS spectrometer obtains its information from a rotating mirror and is timed to collect data when the mirror views the Earth surface between ca. 40 degrees to the left and right of the subsatellite track. Each scan is divided into 1968 picture elements, pixels, of 0.04 degrees scan each. In order to avoid direct reflected Sun glint, the rotating mirror shaft can be tilted so that scans across the subsatellite track up to 20 degrees forward or aft of the point directed beneath the satellite. The CZCS is the first satellite borne instrument to have this tilted scan capability and therefore poses some new problems in locating the Earth surface position of viewed pixels.
Wilson, W. H.↗
Geolocation applications of the Gonets LEO messaging satellites
Geostationary satellites carry a majority of the international telecommunications traffic not carried by transoceanic cable. However, because the radio path links to and from geostationary satellites total at least 70,000 km and because of inherent on-board spacecraft power limitations, earth stations used in conjunction with geostationary satellites are usually large and expensive. This limits their installation to areas with a well-developed industrial and economic infrastructure. This reality helps perpetuate a chicken egg dilemma for the developing countries and isolated regions. Economic integration with the developed world requires being 'networked'. But for many developing entities, even the initial price of entry exceeds their modest resources. Exclusion from the global information highways virtually assures retardation of economic growth for developing nations, remote and isolated areas. Very Small Aperture Terminal (VSAT) earth stations are often thought of as a solution for networking developing regions. But economic considerations often forecloses this option. If VSAT size and cost is to be minimized, powerful spot beams from the satellite need to be focused on relatively small regions. This is not often feasible because of the high cost of the satellite itself. To dedicate a high power spot beam to a small region is usually not economically feasible.
Vlasov, Vladimir N.↗
Non-GPS Geolocation for Space and Terrestrial Applications
Some near and far term space missions involve formation flying, which requires that the positions of multiple spacecraft be accurately known relative to a hub spacecraft. Many such missions will be located far outside the radius of the GPS constellation. So in such missions it will not be possible to derive position knowledge through the capabilities afforded by the GPS service. Consequently, in such missions, it is necessary to determine relative positions by other means. Depending on how well a position must be known, thus far it has appeared necessary to use means other than RF ranging, due to technical limitations. Once spacecraft have been crudely positioned using RF ranging, other tools such as star trackers, ccd cameras, and laser ranging are to be used for precise and accurate ranging. NASA Glenn is investigating an innovation in RF ranging that could be very useful for extending the capabilities of RF ranging in many circumstances. Currently, this innovation is a technical secret, but this paper will discuss the possibility of using RF triangulation for the purposes stated in its title, without disclosing any proprietary information. This paper includes a simulation that successfully illustrates how this technology could be used to perform vehicle tracking.
Robinson, Daryl C.↗
What Can Geolocated Sferics Tell Us About Terrestrial Gamma-Ray Flashes?
The Fermi Gamma-ray Burst Monitor (GBM) has been detecting TGFs with increasing sensitivity over the past two years, owing to changes in flight software that have lowered its threshold for triggering and, recently, allowed a search for TGFs weaker than those which would cause an onboard trigger. Associations between TGFs detected in the first 18 months of operation and sferics detected using the World Wide Lightning Location Network (WWLLN) show that TGF peaks and lightning discharges are simultaneous to within tens of microseconds, and that GBM triggered on TGFs that occurred up to a distance of 300 km from the sub-spacecraft position. In the work presented here, we look for associations between TGFs detected by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and WWLLN sferics over the same 18 months, and we compare the match rate and detection horizon of the two instruments. We also look for associations between WWLLN sferics and more recent GBM TGFs, both triggered events and weaker TGFs uncovered in our untriggered search. We discuss whether in this new mode, GBM is detecting TGFs that are more distant from the sub-spacecraft point than 300 km, or whether the weaker TGFs are instead indicative of a luminosity distribution, either because the weaker ones originate deeper in the atmosphere or because they are intrinsically dimmer.
Connaughton, V.↗
ICESat-2 Photon Classification: Finding Signal Photons in the ATL03 Geolocated Photon Data Product
ICESat-2 carries NASA's next-generation laser altimeter, ATLAS, (Advanced Topographic Laser Altimeter System), designed to measure changes in ice sheet height, sea ice freeboard, and vegetation canopy height. ATLAS contains a photon-counting lidar which transmits green (532-nm) pulses at 10kHz. Each pulse is split into 3 pairs of beams (one strong and one weak). Approximately 1014 photons per pulse travel from ATLAS through the atmosphere to reflect off the Earth's surface. Some return back into the ATLAS telescope where they are recorded. Photons from sunlight and instrument noise at the same wavelength are also recorded. The flight software time tags all photons within a 500m to 6 km range window and generates histograms. Using the histograms, it selects a telemetry window which varies from 20m over flat surfaces to hundreds of meters over rougher terrain. ATL03 contains the time, height (relative to the WGS-84 ellipsoid), latitude and longitude of every photon within the telemetry window. The basic challenge is to determine which of these photons were reflected off the surface. We have developed an algorithm that identifies these signal photons and assigns a confidence level (low, medium, or high) to each signal photon based on the signal to noise ratio. We present an overview of the signal identification algorithm and show the results on actual ICESat-2 data over ice sheet, sea ice, vegetated, and water surfaces. Higher level ATLAS products work with aggregations of the photons in order to determine the ellipsoidal height of the Earth, canopy height and structure, and other quantities of geophysical interest.
Remote Sensing↗
The Ice, Cloud, and Land Elevation Satellite-2 Mission: A Global Geolocated Photon Product Derived from the Advanced Topographic Laser Altimeter System
The Ice, Cloud, and land Elevation Satellite – 2 (ICESat-2) observatory was launched on 15 September 2018 to measure ice sheet and glacier elevation change, sea ice freeboard, and enable the determination of the heights of Earth’s forests. ICESat-2’s laser altimeter, the Advanced Topographic Laser Altimeter System (ATLAS) uses green (532 nm) laser light and single-photon sensitive detection to measure time of flight and subsequently surface height along each of its six beams. In this paper, we describe the major components of ATLAS, including the transmitter, the receiver and the components of the timing system. We present the major components of the ICESat-2 observatory, including the Global Positioning System, star trackers and inertial measurement unit. The ICESat-2 Level 1B data product (ATL02) provides the precise photon round-trip time of flight, among other data. The ICESat-2 Level 2A data product (ATL03) combines the photon times of flight with the observatory position and attitude to determine the geodetic location (i.e. the latitude, longitude and height) of the ground bounce point of photons detected by ATLAS. The ATL03 data product is used by higher-level (Level 3A) surface-specific data products to determine glacier and ice sheet height, sea ice freeboard, vegetation canopy height, ocean surface topography, and inland water body height.
ICESat-2↗
Impact of Ionospheric Range Delay on the Geolocation of Low-Frequency SAR Data: Implications for NISCAR
No abstract provided
Aoki, Yosuke↗
Using airborne LiDAR and enhanced-geolocated GEDI metrics to map structural traits over a Mediterranean forest
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Aaron Cardenas-Martinez↗
Geolocation of the Ionospheric Irregularities in the Equatorial F Layer by Back Propagation of COSMIC‐2 Radio Occultation Signals
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S. Sokolovskiy↗
Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications
Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.
Stefanov, William L.↗
An end-to-end pointing budget approach to planetary observing systems with application to EOS
Previously published error budgets have focused on spacecraft error sources for pointing error and have tended to include only spacecraft pointing rather than the ultimate geolocation of each pixel of dam onto a well-defined spot on the surface of the Earth. A systematic approach to geolocation error budgeting, including all contributors in the geolocation process is presented. Its structure allows simultaneous expression of the needs of instrument teams as well as spacecraft design teams. It allows explicit acknowledgement of approximations made for on-board control as well as the ultimate geolocation accuracy achievable after ground processing and exploits the commonality inherent in the on-board and post-processing error budgets. It also includes the uncontrolled and unmeasured spacecraft jitter. This approach can be used to investigate the mission-wide benefit of a variety of design choices, (such as on-board sensing and ground correction of measurements contrasted with on-board correction of measurements). Additionally, in light of increasing accuracy requirements as sensor resolution improves, numerous non-spacecraft contributors to geolocation error are quantified.
Throckmorton, A.↗
On-Orbit Performance of the NOAA-21 Advanced Technology Microwave Sounder (ATMS)
The Advanced Technology Microwave Sounder (ATMS) instrument provides sounding measurements of Earth’s atmosphere to collect temperature and water vapor data for NOAA’s Joint Polar Satellite System (JPSS) program. ATMS is a total-power passive microwave radiometer with 22 channels spanning a frequency range from 22 to 183 GHz. A general description of the ATMS instrument is detailed in [1]. Three ATMS units are currently on-orbit. The Suomi National Polar-orbiting Partnership (SNPP) unit was launched in 2011 and the NOAA-20 (previously JPSS-1) unit was launch in 2017. Both SNPP and NOAA-20 ATMS units are currently operational and the data is used for numerical weather prediction (NWP) models. The NOAA-21 (formerly JPSS-2) ATMS unit was launched on November 10, 2022 from Vandenberg Space Force Base in California [2]. The ATMS instrument began generating radiance data on November 21, 2022. At the time of this abstract NOAA-21 ATMS is currently completing on-orbit commissioning and checkout activities; it is expected that the commissioning activities will be complete by the IGARSS 2023 conference. This paper will focus on the on-orbit performance of the NOAA-21 ATMS instrument based on measurements and activities from the commissioning period. Comparisons will be made to specifications and to expected performance based on pre-launch test activities. Pre-launch JPSS-2 (NOAA-21) ATMS performance is detailed in [4]. Additionally, the NOAA-21 performance will be compared to the on-orbit performance of the SNPP and NOAA-21 ATMS units. The post-launch performance of SNPP ATMS is detailed in [1][5][6][7]. The post-launch performance of NOAA-20 ATMS is detailed in [5][7][8]. On-orbit performance is evaluated through data collects from nominal mission operations as well as specific post-launch tests and spacecraft maneuvers. Nominal mission operations can be used to evaluate parameters such as instrument thermal stability, Noise Equivalent Delta Temperature (NEDT)/radiometric sensitivity, geolocation, inter-channel noise correlation, striping, and radiometric bias and stability. Shortly after instrument activation, the instrument thermal stability as measured from onboard temperature sensors is evaluated to demonstrate stable and steady-state behavior. Methods for computing NEDT are described in [9][10][11]. Passive geolocation measurements are performed using the coastline inflection point (CIP) method, described in [8][12]. The striping index, used as a metric to quantify striping, is the ratio of along-track variance to cross-track variance of the observed brightness temperature [4][8][14]. Inter-channel noise correlation has been previously reported for SNPP and NOAA-20 [1][8]. Dedicated post-launch tests and spacecraft maneuvers are utilized during the commissioning phase for further evaluation of on-orbit instrument performance. These activities provide information on the optimal space view selection, noise power spectral density (PSD), gain stability, scan bias, interference from onboard transmitters, reflector emissivity, active geolocation, and radiometric bias and stability detection methods. The optimal space view selection is used to determine which of ATMS space view sectors is preferred for minimizing contamination of the space view [1]. Point and stare testing is used to generate noise PSD and gain stability information, as described in [1][8]. Spacecraft roll and pitch maneuvers allow the ATMS to view different zones, including deep space, and the data can be used to provide information on scan biases and antenna sidelobe contamination [1][8]. The pitch maneuver can also be used to assess interference from onboard Ka-band transmitters and reflector emissivity [8]. Active geolocation is evaluated as a method for geolocation, described in [15].
Edward Kim↗
Level 1 Processing of MODIS Direct Broadcast Data From Terra
In February 2000, an effort was begun to adapt the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1 production software to process direct broadcast data. Three Level 1 algorithms have been adapted and packaged for release: Level 1A converts raw (level 0) data into Hierarchical Data Format (HDF), unpacking packets into scans; Geolocation computes geographic information for the data points in the Level 1A; and the Level 1B computes geolocated, calibrated radiances from the Level 1A and Geolocation products. One useful aspect of adapting the production software is the ability to incorporate enhancements contributed by the MODIS Science Team. We have therefore tried to limit changes to the software. However, in order to process the data immediately on receipt, we have taken advantage of a branch in the geolocation software that reads orbit and altitude information from the packets themselves, rather than external ancillary files used in standard production. We have also verified that the algorithms can be run with smaller time increments (2.5 minutes) than the five-minute increments used in production. To make the code easier to build and run, we have simplified directories and build scripts. Also, dependencies on a commercial numerics library have been replaced by public domain software. A version of the adapted code has been released for Silicon Graphics machines running lrix. Perhaps owing to its origin in production, the software is rather CPU-intensive. Consequently, a port to Linux is underway, followed by a version to run on PC clusters, with an eventual goal of running in near-real-time (i.e., process a ten-minute pass in ten minutes).
Lynnes, Christopher↗
Geometric Assessment of PlanetScope Imagery
Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.
Alana G. Semple↗