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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Web-Based Satellite Products Database for Meteorological and Climate Applications

The need for ready access to satellite data and associated physical parameters such as cloud properties has been steadily growing. Air traffic management, weather forecasters, energy producers, and weather and climate researchers among others can utilize more satellite information than in the past. Thus, it is essential that such data are made available in near real-time and as archival products in an easy-access and user friendly environment. A host of Internet web sites currently provide a variety of satellite products for various applications. Each site has a unique contribution with appeal to a particular segment of the public and scientific community. This is no less true for the NASA Langley's Clouds and Radiation (NLCR) website (http://www-pm.larc.nasa.gov) that has been evolving over the past 10 years to support a variety of research projects This website was originally developed to display cloud products derived from the Geostationary Operational Environmental Satellite (GOES) over the Southern Great Plains for the Atmospheric Radiation Measurement (ARM) Program. It has evolved into a site providing a comprehensive database of near real-time and historical satellite products used for meteorological, aviation, and climate studies. To encourage the user community to take advantage of the site, this paper summarizes the various products and projects supported by the website and discusses future options for new datasets.

Phan, Dung↗
NASA NTRSDate not supplied

Overview of SatCORPS Satellite-Derived Cloud and Radiation Retrieval Coverage of ARM Domains

The ARM Climate Research Facility program maintains a number of climatically representative sites, which provide long-term cloud- and climate-monitoring records via ground-based instrumentation. These measurements provide a valuable data record over a localized region, but can be greatly enhanced by use of satellite monitoring. Satellite analyses over larger domains can provide parameters helpful for monitoring climate and evaluating models. The NASA/Langley Cloud group routinely derives such cloud and radiative parameters, from various geostationary and polar-orbiting satellite coverage over ARM sites; the group provides near-realtime analyses covering the 3 ARM fixed sites, as well as the GO-Amazon AMF site. This is accomplished by employing a suite of algorithms including VISST (Visible Infrared Solar Split-Window Technique), SIST (Solar Infrared Split-Window Technique), and SINT (Solar-infrared Infrared Near-Infrared Technique), now collectively called SatCORPS (Satellite Cloud Observations and Radiative Property retrieval System). An overview and catalog of SatCORPS-derived datasets processed for ASR, and available from both the ARM archive and the NASA/Langley Cloud group website, is provided. Specific improvements included in recently added datasets such as GO-Amazon and Azores are highlighted, including an improved cloud-detection mask, as well as improvements in derived Top-of-Atmosphere (TOA) SW albedoes and LW fluxes. New narrowband-to-broadband (NB-BB) fits and corrections for improved TOA fluxes are illustrated, including MTSAT-1/CERES Aqua NB-BB fits for the TWPICE field campaign, as well as new fits covering the Azores region which incorporate GERB TOA fluxes (Geostationery Earth Radiation Budget). Finally, validation of the reprocessed SatCORPS datasets is shown.

M M Khader↗
NASA NTRS1994

Quantitative 3-D imaging topogrammetry for telemedicine applications

The technology to reliably transmit high-resolution visual imagery over short to medium distances in real time has led to the serious considerations of the use of telemedicine, telepresence, and telerobotics in the delivery of health care. These concepts may involve, and evolve toward: consultation from remote expert teaching centers; diagnosis; triage; real-time remote advice to the surgeon; and real-time remote surgical instrument manipulation (telerobotics with virtual reality). Further extrapolation leads to teledesign and telereplication of spare surgical parts through quantitative teleimaging of 3-D surfaces tied to CAD/CAM devices and an artificially intelligent archival data base of 'normal' shapes. The ability to generate 'topogrames' or 3-D surface numerical tables of coordinate values capable of creating computer-generated virtual holographic-like displays, machine part replication, and statistical diagnostic shape assessment is critical to the progression of telemedicine. Any virtual reality simulation will remain in 'video-game' realm until realistic dimensional and spatial relational inputs from real measurements in vivo during surgeries are added to an ever-growing statistical data archive. The challenges of managing and interpreting this 3-D data base, which would include radiographic and surface quantitative data, are considerable. As technology drives toward dynamic and continuous 3-D surface measurements, presenting millions of X, Y, Z data points per second of flexing, stretching, moving human organs, the knowledge base and interpretive capabilities of 'brilliant robots' to work as a surgeon's tireless assistants becomes imaginable. The brilliant robot would 'see' what the surgeon sees--and more, for the robot could quantify its 3-D sensing and would 'see' in a wider spectral range than humans, and could zoom its 'eyes' from the macro world to long-distance microscopy. Unerring robot hands could rapidly perform machine-aided suturing with precision micro-sewing machines, splice neural connections with laser welds, micro-bore through constricted vessels, and computer combine ultrasound, microradiography, and 3-D mini-borescopes to quickly assess and trace vascular problems in situ. The spatial relationships between organs, robotic arms, and end-effector diagnostic, manipulative, and surgical instruments would be constantly monitored by the robot 'brain' using inputs from its multiple 3-D quantitative 'eyes' remote sensing, as well as by contact and proximity force measuring devices. Methods to create accurate and quantitative 3-D topograms at continuous video data rates are described.

Altschuler, Bruce R.↗
NASA NTRS2015

NASA ROVER, Tackling Citizen Science With Grand Challenges and Everyday Problems

ROVER is the Citizen Science arm of the NASA Clouds and the Earth's Radiant Energy System (CERES) Students' Cloud Observations On-Line (S'COOL) Project. Since 2007, participants around the world have been making and reporting ground truth observations of clouds to assist in the validation of the NASA CERES satellite instrument. NASA scientists are very interested in learning how clouds affect our atmosphere, weather, and climate (relating to climate change). It is the clouds, in part, that affect the overall temperature and energy balance of the Earth. The more we know about clouds, the more we will know about our Earth as a system and citizen scientists are an important piece of that puzzle! As a ROVER cloud observer, all participants follow simple online tutorials to collect data on cloud type, height, cover and related conditions. Observations are sent to NASA to be matched to similar information obtained from satellites and sent back to participants for comparison and analysis. The supporting ROVER website houses a searchable database archiving all participant reports and matching satellite data. By involving Citizen Scientists in cloud observations and reporting we can gain a valuable set of data that would have been previously unavailable to science teams due to funding, manpower, and resource limitations or would have taken an unreasonable amount of time to collect. Reports from a wide range of Citizen Scientist locations are helpful to assess the satellite data under different conditions. With nothing more than their eyes and an internet connection participants provide a different perspective and analysis of clouds, adding to a more complete picture of what's happening in the atmosphere in which we live.

Crecelius, Sarah↗
NASA NTRS1998

Operational processing and cloud boundary detection from micro pulse lidar data

Micro Pulse Lidar (MPL) was developed at NASA Goddard Space Flight Center (GSFC) as the result of research on space-borne lidar techniques. It was designed to provide continuous, unattended observations of all significant atmospheric cloud and aerosol structure with a rugged, compact system design and the benefit of eye safety (Spinhirne 1993). The significant eye safety feature is achieved by using low pulse energies and high pulse repetition rates compared to standard lidar systems. MPL systems use a diode pumped 10 microj, 2500 Hz doubled Nd:YLF laser. In addition, a solid state Geiger mode avalanche photo diode (GAPD) photon counting detector is used allowing for quantum efficiencies approaching 70%. Other design features have previously been noted by Spinhirne (1995). Though a commercially available instrument, with nearly 20 systems operating around the world, the most extensive MPL work has come from those operated by the Atmospheric Radiation Measurement (ARM) (Stokes and Schwartz 1994) program. The diverse ability of the instrument relating to the measurement of basic cloud macrophysical structure and both cloud and aerosol radiative properties well suits the ARM research philosophy. MPL data can be used to yield many parameters including cloud boundary heights to the limit of signal attenuation, cloud scattering cross sections and optical thicknesses, planetary boundary layer heights and aerosol scattering profiles, including those into the stratosphere in nighttime cases (Hlavka et al 1996). System vertical resolution ranges from 30 m to 300 m (i.e. high and low resolution respectively) depending on system design. The lidar research group at GSFC plays an advisory role in the operation, calibration and maintenance of NASA and ARM owned MPL systems. Over the past three years, processing software and system correction techniques have been developed in anticipation of the increasing population of systems amongst the community. Datasets produced by three ARM-owned systems have served as the basis for this development. With two operating at the southern Great Plains Cloud and Radiation Testbed Site (SGP CART) since December 1993 and another at the Manus Island Atmospheric Radiation and Cloud Station (TWP ARCS) location in the tropical western Pacific since February 1997, the ARM archive contains over 4 years of observations. In addition, high resolution systems planning to come on-line at the North Slope, AK CART shortly with another scheduled to follow at the TWP ARCS-II will diversify this archive with more extensive observations.

Campbell, James R.↗
NASA NTRS2003

Enhancing and Archiving the APS Catalog of the POSS I

We have worked on two different projects: 1) Archiving the APS Catalog of the POSS I for distribution to NASA's NED at IPAC, SIMBAD in France, and individual astronomers and 2) The automated morphological classification of galaxies. We have completed archiving the Catalog into easily readable binary files. The database together with the software to read it has been distributed on DVD's to the national and international data centers and to individual astronomers. The archived Catalog contains more than 89 million objects in 632 fields in the first epoch Palomar Observatory Sky Survey. Additional image parameters not available in the original on-line version are also included in the archived version. The archived Catalog is also available and can be queried at the APS web site (URL: http://aps.umn.edu) which has been improved with a much faster and more efficient querying system. The Catalog can be downloaded as binary datafiles with the source code for reading it. It is also being integrated into the SkyQuery system which includes the Sloan Digital Sky Survey, 2MASS, and the FIRST radio sky survey. We experimented with different classification algorithms to automate the morphological classification of galaxies. This is an especially difficult problem because there are not only a large number of attributes or parameters and measurement uncertainties, but also the added complication of human disagreement about the adopted types. To solve this problem we used 837 galaxy images from nine POSS I fields at the North Galactic Pole classified by two independent astronomers for which they agree on the morphological types. The initial goal was to separate the galaxies into the three broad classes relevant to issues of large scale structure and galaxy formation and evolution: early (ellipticals and lenticulars), spirals, and late (irregulars) with an accuracy or success rate that rivals the best astronomer classifiers. We also needed to identify a set of parameters derived from the digitized images that separate the galaxies by type. The human eye can easily recognize complicated patterns in images such as spiral arms which can be spotty, blotchy affairs that are difficult for automated techniques. A galaxy image can potentially be described by hundreds of parameters, all of which may have some relation to the morphological type. In the set of initial experiments we used 624 such parameters, in two colors, blue and red. These parameters include the surface brightness and color measured at different radii, ratios of these parameters at different radii, concentration indices, Fourier transforms and wavelet decomposition coefficients. We experimented with three different classes of classification algorithms; decision trees, k-nearest neighbors, and support vector machines (SVM). A range of experiments were conducted and we eventually narrowed the parameters to 23 selected parameters. SVM consistently outperformed the other algorithms with both sets of features. By combining the results from the different algorithms in a weighted scheme we achieved an overall classification success of 86%.

Humphreys, Roberta M.↗
NASA NTRS2019

2018 NISAR Applications Workshop: Forest and Disturbance; Workshop Report

Forest lands cover the globe and are important sources for providing ecosystem services including: carbon sequestration, biodiversity, timber, air and water quality. As such, counties around the world have dedicated programs for managing them. Accurate and timely information concerning the status of these forests (moisture, biomass, disturbance type, etc.) is essential to those Nations’ human and ecological health as well as economy. The joint NASA/US Forest Service workshop focused on arming forest land managers with observations and remote sensing information from the upcoming NASA-ISRO (Indian Space Research Organization) SAR (Synthetic Aperture Radar) (NISAR) satellite mission (expected to launch early 2022). Participants included representatives from different US Federal Agencies, private sector, and non-governmental organizations (NGO) that are key players in facilitating integration of Earth Observations (EO) into forest management and decision support workflows. They included scientists, technicians, and program managers with a responsibility for data acquisition and exploitation such as product development, delivery, and use, and capacity building. Discussions were held over two days to convey the broader forest and disturbance community information needs for various representative participants and programs and to facilitate the delivery of NISAR mission geospatial products and observational capabilities. Case studies were presented to demonstrate the current state of practice in the use of SAR remote sensing for applications of direct importance to forest and disturbance land management community. Eleven organizations presented their information requirements in response to a set of questions provided by the NASA team, then the NASA team responded by describing the degree to which NISAR could meet these requirements. Discussion ensued about needed data product specifications to increase utility (e.g., projection, latency, etc.), tools and capacity building. The general findings of this workshop were that (a) NISAR observations will be particularly useful to the global forest carbon and disturbance monitoring applications, but that certain data product design decisions (projections and radiometric and terrain corrections) need to be considered to increase utility; b) the biomass and disturbance detection algorithms meet many of the community needs, however there are other information products of value (e.g., soil moisture or disturbance classification, not just detection) and all products should be compliant with existing community standards for reporting uncertainty; c) providing SAR education to the community will be key specifically thinking about putting the information first and the SAR theory second, providing a simple guide of standard data processing steps (e.g., dB (decibel) to power conversion and speckle filtering); d) the community needs a user-friendly interface for finding free, archived data over their geographic regions of interest; e) user-friendly tools that connect to open-sources GIS (Global Information System) software (e.g., QGIS (Quantum GIS)) that include a graphical user interface (GUI) for SAR processing that enables both download and cloud processing. To integrate these findings and prepare the community before NISAR launches, it was suggested that there be a dedicated NISAR Forest and Disturbance Applications Working Group (as per the specifications in the NISAR Utilization Plan). After launch, it was decided that the community continue capacity building activities.

Stavros, Natasha↗