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EOS Terra Validation Program

The EOS Terra mission will be launched in July 1999. This mission has great relevance to the atmospheric radiation community and global change issues. Terra instruments include Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multi-Angle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Measurements of Pollution in the Troposphere (MOPITT). In addition to the fundamental radiance data sets, numerous global science data products will be generated, including various Earth radiation budget, cloud and aerosol parameters, as well as land surface, terrestrial ecology, ocean color, and atmospheric chemistry parameters. Significant investments have been made in on-board calibration to ensure the quality of the radiance observations. A key component of the Terra mission is the validation of the science data products. This is essential for a mission focused on global change issues and the underlying processes. The Terra algorithms have been subject to extensive pre-launch testing with field data whenever possible. Intensive efforts will be made to validate the Terra data products after launch. These include validation of instrument calibration (vicarious calibration) experiments, instrument and cross-platform comparisons, routine collection of high quality correlative data from ground-based networks, such as AERONET, and intensive sites, such as the SGP ARM site, as well as a variety field experiments, cruises, etc. Airborne simulator instruments have been developed for the field experiment and underflight activities including the MODIS Airborne Simulator (MAS) AirMISR, MASTER (MODIS-ASTER), and MOPITT-A. All are integrated on the NASA ER-2 though low altitude platforms are more typically used for MASTER. MATR is an additional sensor used for MOPITT algorithm development and validation. The intensive validation activities planned for the first year of the Terra mission will be described with emphasis on derived geophysical parameters of most relevance to the atmospheric radiation community.

Starr, David↗

Sixteen Years of Terra MODIS On-Orbit Operation, Calibration, and Performance

Terra MODIS has successfully operated for more than 16 years since its launch in December 1999. From its observations, many science data products have been generated in support of a broad range of research activities and remote sensing applications. Terra MODIS has operated in a number of configurations and experienced a few anomalies, including spacecraft and instrument related events. MODIS collects data in 36 spectral bands that are calibrated regularly by a set of on-board calibrators for their radiometric, spectral, and spatial performance. Periodic lunar observations and long-term radiometric trending over well-characterized ground targets are also used to support sensor on-orbit calibration. Dedicated efforts made by the MODIS Characterization Support Team (MCST) and continuing support from the MODIS Science Team have contributed to the mission success, enabling well-calibrated data products to be continuously generated and routinely delivered to users worldwide. This paper presents an overview of Terra MODIS mission operations, calibration activities, and instrument performance of the past 16 years. It illustrates and describes the results of key sensor performance parameters derived from on-orbit calibration and characterization, such as signal-to-noise ratio (SNR), noise equivalent temperature difference (NEdT), solar diffuser (SD) degradation, changes in sensor responses, center wavelengths, and band-to-band registration (BBR). Also discussed in this paper are the calibration approaches and strategies developed and implemented in support of MODIS Level 1B data production and re-processing, major challenging issues, and lessons learned. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Xiong, X.↗

CCSDS File Delivery Protocol (CFDP): Why it's Useful and How it Works

Reliable delivery of data products is often required across space links. For example, a NASA mission will require reliable delivery of images produced by an on-board detector. Many missions have their own (unique) way of accomplishing this, requiring custom software. Many missions also require manual operations (e.g. the telemetry receiver software keeps track of what data is missing, and a person manually inputs the appropriate commands to request retransmissions). The Consultative Committee for Space Data Systems (CCSDS) developed the CCSDS File Delivery Protocol (CFDP) specifically for this situation. CFDP is an international standard communication protocol that provides reliable delivery of data products. It is designed for use across space links. It will work well if run over the widely used CCSDS Telemetry and Telecommand protocols. However, it can be run over any protocol, and will work well as long as the underlying protocol delivers a reasonable portion of the data. The CFDP receiver will autonomously determine what data is missing, and request retransmissions as needed. The CFDP sender will autonomously perform the requested transmissions. When the entire data product is delivered, the CFDP receiver will let the CFDP sender know that the transaction has completed successfully. The result is that custom software becomes standard, and manual operations become autonomous. This paper will consider various ways of achieving reliable file delivery, explain why CFDP is the optimal choice for use over space links, explain how the core protocol works, and give some guidance on how to best utilize CFDP within various mission scenarios. It will also touch on additional features of CFDP, as well as other uses for CFDP (e.g. the loading of on-board memory and tables).

Ray, Tim↗

Proto-Examples of Data Access and Visualization Components of a Potential Cloud-Based GEOSS-AI System

Once a research or application problem has been identified, one logical next step is to search for available relevant data products. Thus, an early component of a potential GEOSS-AI system, in the continuum between observations and end point research, applications, and decision making, would be one that enables transparent data discovery and access by users. Such a component might be effected via the systems data agents. Presumably, some kind of data cataloging has already been implemented, e.g., in the GEOSS Common Infrastructure (GCI). Both the agents and cataloging could also leverage existing resources external to the system. The system would have some means to accept and integrate user-contributed agents. The need or desirability for some data format internal to the system should be evaluated. Another early component would be one that facilitates browsing visualization of the data, as well as some basic analyses.Three ongoing projects at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provide possible proto-examples of potential data access and visualization components of a cloud-based GEOSS-AI system. 1. Reorganizing data archived as time-step arrays to point-time series (data rods), as well as leveraging the NASA Simple Subset Wizard (SSW), to significantly increase the number of data products available, at multiple NASA data centers, for production as on-the-fly (virtual) data rods. SSWs data discovery is based on OpenSearch. Both pre-generated and virtual data rods are accessible via Web services. 2. Developing Web Feature Services to publish the metadata, and expose the locations, of pre-generated and virtual data rods in the GEOSS Portal and enable direct access of the data via Web services. SSW is also leveraged to increase the availability of both NASA and non-NASA data.3.Federating NASA Giovanni (Geospatial Interactive Online Visualization and Analysis Interface), for multi-sensor data exploration, that would allow each cooperating data center, currently the NASA Distributed Active Archive Centers (DAACs), to configure its own Giovanni deployment, while also allowing all the deployments to incorporate each others data. A federated Giovanni comprises Giovanni Virtual Machines, which can be run on local servers or in the cloud.

access↗

Science Requirements Document for OMI-EOS

A Dutch-Finnish scientific and industrial consortium is supplying the Ozone Monitoring Instrument (OMI) for Earth Observing System-Aura (EOS-Aura). EOS-Aura is the next NASA mission to study the Earth's atmosphere extensively, and successor to the highly successful UARS (Upper Atmospheric Research Satellite) mission. The 'Science Requirements Document for OMI-EOS' presents an overview of the Aura and OMI mission objectives. It describes how OMI fits into the Aura mission and it reviews the synergy with the other instruments onboard Aura to fulfill the mission. This evolves in the Scientific Requirements for OMI (Chapter 3), stating which trace gases have to be measured with what necessary accuracy, in order for OMI to meet Aura's objectives. The most important data product of OMI, the ozone vertical column, densities shall have a better accuracy and an improved global coverage than the predecessor instruments TOMS (Total Ozone Monitoring Spectrometer) and GOME (Global Ozone Monitoring Experiment), which is a.o. achieved by a better signal to noise ratio, improved calibration and a wide field-of-view. Moreover, in order to meet its role on Aura, OMI shall measure trace gases, such as NO2, OClO, BrO, HCHO and SO2, aerosols, cloud top height and cloud coverage. Improved accuracy, better coverage, and finer ground grid than has been done in the past are goals for OMI. After the scientific requirements are defined, three sets of subordinate requirements are derived. These are: the algorithm requirements, i.e. what do the algorithms need in order to meet the scientific requirements; the instrument and calibration requirements, i.e. what has to be measured and how accurately in order to provide the quality of data necessary for deriving the data products; and the validation requirements, i.e. a strategy of how the OMI program will assure that its data products are valid in the atmosphere, at least to the required accuracy.

Levelt, P. F.↗

Data Quality Screening Service

A report describes the Data Quality Screening Service (DQSS), which is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process often involves much research through quality documents followed by laborious coding, the DQSS is a Web Service that provides data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts. The DQSS design is based on a formal semantic Web ontology that describes data fields and the quality fields for applying quality control within a data product. The accompanying code base handles several remote sensing datasets and quality control schemes for data products stored in Hierarchical Data Format (HDF), a common format for NASA remote sensing data. Together, the ontology and code support a variety of quality control schemes through the implementation of the Boolean expression with simple, reusable conditional expressions as operands. Additional datasets are added to the DQSS simply by registering instances in the ontology if they follow a quality scheme that is already modeled in the ontology. New quality schemes are added by extending the ontology and adding code for each new scheme.

Strub, Richard↗

Managing Current Earth Observation Needs through User-Driven Implementation of Upcoming Satellite Needs Working Group (SNWG) Solutions

Since 2016, the Satellite Needs Working Group (SNWG), an initiative of the U.S. Group on Earth Observations (USGEO), has surveyed federal agencies every two years to identify their satellite earth observation needs. For each expressed need, NASA-led assessment teams coordinate with responding agencies to devise remote sensing solutions that benefit multiple partners and span across a number of thematic areas including, but not limited to, Atmospheric Composition, Carbon Cycle and Ecosystems, Earth Surface and Interior, and Oceans and Cryosphere. Solutions can comprise existing or modified data products as well as the construction of new data products and technologies: since 2016, a multitude of SNWG activities have been theorized and developed, reaching a wide range of users in the science community. Due to an increase in survey responses in 2020 and to assure solution delivery to users within five years of budget appropriations, the SNWG Management Office was established to oversee the assessment of agency needs and the implementation and operations of solution development. The SNWG MO’s unique implementation strategy creates multiple touchpoints with agencies during solution development helping fulfill Earth Science to Action priorities (the 2024 NASA Earth Science Division strategic plan) and ensuring solutions are accessible, usable, and support decision-making for their intended audience. This presentation will outline the ways in which SNWG supports complementary goals of the Decadal Survey, with specific attention on the SNWG MO’s renewed user-centric implementation strategy for upcoming SNWG solutions.

Jenny Wood↗

Full-waveform, Laser Altimeter Measurements of Vegetation Vertical Structure and Sub-canopy Topography in Support of the North American Carbon Program

Full-waveform, scanning laser altimeters (i.e. lidar) provide a unique and precise view of the vertical and horizontal structure of vegetation across wide swaths. These unique laser altimeters systems are able to simultaneously image sub-canopy topography and the vertical structure of any overlying vegetation. These data reveal the true 3-D distribution of vegetation in leaf-on conditions enabling important biophysical parameters such as canopy height and aboveground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted in the summer of 2003 in support of preliminary studies for the North America Carbon Program. NASA's Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 sq km in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate numerous bio- and geophysical investigations. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces (i.e. the return waveform). Data are currently available at the LVIS website (http://lvis.gsfc.nasa.gov/). Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products are available on the website and will be presented. Future applications including potential fusion with other remote sensing data sets and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.

Blair, B.↗

Global Change Data Center: Mission, Organization, Major Activities, and 2001 Highlights

Rapid efficient access to Earth sciences data is fundamental to the Nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase further and missions with constellations of satellites start to appear. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink. The Global Change Data Center's (GCDC) mission is to provide systems, data products, and information management services to maximize the availability and utility of NASA's Earth science data. The specific objectives are (1) support Earth science missions be developing and operating systems to generate, archive, and distribute data products and information; (2) develop innovative information systems for processing, archiving, accessing, visualizing, and communicating Earth science data; and (3) develop value-added products and services to promote broader utilization of NASA Earth Sciences Enterprise (ESE) data and information. The ultimate product of GCDC activities is access to data and information to support research, education, and public policy.

Wharton, Stephen W.↗

EOSDIS - Its role in the EOS program and its importance to the scientific community

In order to manage the global data sets required to understand the earth as a system, the EOS Data and Information System (EOSDIS) will collect and store satellite, aircraft, and in situ measurements and their resultant data products, and will distribute the data conveniently. EOSDIS will also provide product generation and science computing facilities to support the development, processing, and validation of standard EOS science data products. The overall architecture of EOSDIS, and how the Distributed Active Archive Centers fit into that structure, are shown. EOSDIS will enable users to query data bases nationally, make use of keywords and other mnemonic identifiers, and see graphic images of subsets of available data prior to ordering full (or selected pieces of) data sets for use in their 'home' environment.

Price, Robert D.↗

TPSAS-NF1676L-33912-DND

The agricultural, renewable energy management, and science communities need global surface and top-of-atmosphere (TOA) radiative fluxes on a near real-time basis for uses such as building energy performance monitoring and seasonal crop yield modeling. The Clouds and Earth's Radiant Energy System (CERES) FLASHFlux (Fast Longwave and SHortwave radiative Flux) data products address this need by enhancing the speed of CERES processing using simplified calibration, averaging techniques and fast radiation parameterizations to produce global fluxes within a week of satellite observations. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1degree x 1degree gridded data that combines Aqua and Terra observations. The CERES FLASHFlux Version4A includes an update to process MODIS Collection 6.1 in an improved cloud retrieval algorithm, and an update to the CERES Edition 4 angular distribution models. We inter-compared FLASHFlux Version4A, FLASHFlux Version3C, and CERES EBAF (Energy Balanced and Filled) Top-of-Atmosphere fluxes to evaluate these improvements. We also compare both SSF overpass and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement. FLASHFlux TISA and CERES EBAF are used in the analysis of TOA anomalies for the annual State of Climate report. This also poster highlights the methodology use to merge the two data products by correcting the bias in FLASHFlux TISA and inter-calibrate to CERES EBAF.

Parnchai K Sawaengphokhai↗

The TOLNet 2.0 Website: How an API Can Promote Open Science and FAIR Principles

The Tropospheric Ozone Lidar Network (TOLNet) has generated over a decade of ozone vertical profile data products over North America. The science value of the TOLNet data has been demonstrated in numerous peer-reviewed publications on air quality and other ozone relevant research. To support the broad spectrum of data use, the TOLNet team launched a major effort to upgrade the web-based data repository aiming to enhance the data discoverability and to enable machine-to-machine data upload and download processes. Specifically, the TOLNet website included an application programming interface (API), which supports machine-to-machine data search and data download. The API also extracts selected variables from the files, which can be retrieved as JSON objects and used to create data displays without having to download or open the underlying files. The TOLNet science team members can also use the API for automated data upload, including a data file scanning feature to ensure data product integrity. To be presented will include a summary of key features of data repositories, an actual use case of machine-to-machine data access/use, as well as our journey to make TOLNet data more FAIR, i.e., more findable, accessible, interoperable, and (re)usable.

Crystal Gummo↗

International collaboration in SAR ground data systems

A set of considerations that are pertinent to future international cooperation in the area of synthetic aperture radar (SAR) ground data systems are presented. The considerations are as follows: (1) success of future spaceborne SAR missions will require multi-agency and/or multi-national collaboration; (2) ground processing is typically performed by each agency for their user base; (3) international standards are required to achieve a uniform data product independent of the processing center; (4) to reduce the aggregate cost of the ground data systems, collaboration is required in design and development; (5) effective utilization of the data by an international user community; (6) commercialization of data products; and (7) security of data systems.

Curlander, John C.↗

The Role of Declining Snow Cover in the Desiccation of the Great Salt Lake, Utah, using MODIS Data

The Great Salt Lake (GSL) in Utah has been shrinking since the middle of the 19th Century, leading to decreased area and volume, and increased salinity. We use satellite data products from the Terra and Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the Landsat-7 and -8 satellites, along with meteorological and streamflow data, and modeled data products to study the relationship between changing snow-cover conditions and the decline of the GSL since 2000 in the context of the historical record of lake levels. The GSL basin includes much of the snow-dominated Wasatch and Uinta mountain ranges to the east of the lake. Snowmelt feeds the Bear, Jordan, and Weber rivers which are the three main rivers that flow into the lake. Snowmelt-timing maps, derived from a new MODIS standard snow-cover product, MOD10A1F, show that snow melted ~9.5 days earlier in the GSL basin during the study period, extending from 2000 – 2018. Air temperatures derived from 26 meteorological stations and surface temperatures measured by the Aqua MODIS land-surface temperature (LST) products, MYD21A1D and MYD21A1N, show trends of increasing temperature of ~0.94°C (a=0.05), and ~2.18°C, respectively, with most of the LST trends in the GSL basin being statistically significant (a=0.05). Increasing air temperatures in the basin have led to less precipitation falling as snow, lower snow depth (by ~34.5 mm (=0.01)) and snow-water equivalent (0.02 mm (a=0.01)), and earlier snowmelt. Also during the study period, Global Land surface Evaporation Amsterdam Model data show evaporation increasing by ~3.2 mm/yr, with trends in much of the basin being statistically significant (a=0.05). Trends calculated from the various products are generally in agreement indicating higher temperatures, greater evaporation, less snowfall and snow-on-the ground, and earlier snowmelt. Earlier snowmelt contributes to increasing evaporative loss from water flowing toward the lake. Furthermore, a lower mountain snowpack and less precipitation falling as snow (versus rain) is associated with lower stream discharge even if overall precipitation stays the same. The surface-water temperature of the GSL also increased over the study period by ~ 0.69°C, according to the MODIS LST data products, and the surface-water elevation of the lake dropped by ~1.7 m between 2000 and 2018 based on United States Geological Survey measurements, and the areal extent of the lake decreased by ~901 km2 as measured using Landsat imagery. Desiccation of the lake is associated with deleterious effects on wildlife, recreational activities, and some local industries. And, importantly, an expanding lake bed can also fuel dust storms that promote dangerous air quality along the Wasatch Front. This work elucidates the key role that satellite remote sensing can play in documenting earlier snowmelt and other changes in the GSL basin that influence the ongoing decline of the Great Salt Lake.

Dorothy K Hall↗

An Update on the Hydrological Land Surface Data and Services at NASA GES DISC

"The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth Observing System data centers that document, process, archive and distribute data from Earth science missions and related projects. The GES DISC hosts many hydrological land surface data products including North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and assimilated-Gravity Recovery and Climate Experiment (GRACE). The Land Surface Model (LSM) products contain model output, including heat fluxes, rain, snow, soil temperature, soil moisture and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at the GES DISC ranges from hourly to monthly and the spatial resolution 0.1 degree to 1.0 degree. The variability of Earth’s water and energy cycles can be characterized with these spatially and temporally consistent, and quality controlled hydrological land surface data. These data could support ongoing modeling activities, and help improve our understanding of land-surface-atmosphere interactions and their impact on climate. Over the years, new data is added, and older data is reprocessed and updated. This presentation provides a summary table of the hydrological data and discusses recent updates to the data and data services at the GES DISC. New data products include (1) GRACE Global Version 3.0 drought indicators and (2) FLDAS monthly global and Central Asia daily data. Reprocessed and updated products include (1) NLDAS Version 2.0 and (2) GRACE United States Version 4.0 drought indicators. Lastly, this presentation will discuss the opportunities for accessing some of our hydrology data from the cloud. As the hydrology land surface data is moved to the cloud, users can expect faster service for longer time series, notably the hydrology data rods time series service."

Ashley Heath↗

The Advantages of Synergy-Quantitative Earth Science Data Visualization and Analysis with Giovanni, Panoply, and Excel

The NASA Giovanni data analysis system provides a multitude of basic analysis capabilities for numerous Earth science data products which are available in the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archive, as well as for additional selected data products provided by other NASA Distributed Active Archive Center (DAAC) archives. In Giovanni, users can easily generate time-averaged data maps, area-averaged time-series, Latitude-Time and Longitude-Time Hovmoeller diagrams, correlation maps, accumulation maps, and map animations (22 analysis options are available in total). While ASCII text output is available for time-series plots, it is not included as an option for data maps. In order to provide a quantitative, easy-to-use numerical output in ASCII text form, the NetCDF file output from a Giovanni visualization is downloaded and then opened with the free NASA visualization software package Panoply. Panoply provides the capability of translating the Giovanni file into comma-separated-variable (CSV) output. Panoply also provides additional visualization options, including the facile calculation of difference maps and quasi-anomaly maps using Giovanni output files. The CSV files from Panoply can then be imported into an Excel spreadsheet, where an Excel macro converts the CSV files. The output consists of latitude-longitude-data value triads in text form for maps, and either longitude-time-data value or latitude-time-data value triads in text form for Hovmoeller diagrams. This presentation will explicate the basic procedure for the conversion, and then provide several examples where the procedure is applied to Giovanni output from different analysis options.

Earth science↗

The EOSDIS Version 0 Distributed Active Archive Center for physical oceanography and air-sea interaction

The Distributed Active Archive Center (DAAC) at the Jet Propulsion Laboratory will support scientists specializing in physical oceanography and air-sea interaction. As part of the NASA Earth Observing System Data and Information System Version 0 the DAAC will build on existing capabilities to provide services for data product generation, archiving, distribution and management of information about data. To meet scientist's immediate needs for data, existing data sets from missions such as Seasat, Geosat, the NOAA series of satellites and the Global Positioning Satellite system will be distributed to investigators upon request. In 1992, ocean topography, wave and surface roughness data from the Topex/Poseidon radar altimeter mission will be archived and distributed. New data products will be derived from Topex/Poseidon and other sensor systems based on recommendations of the science community. In 1995, ocean wind field measurements from the NASA Scatterometer will be supported by the DAAC.

Hilland, Jeffrey E.↗

Full-Waveform, Wide-Swath Lidar Imaging of Forested and Urban Areas in Leaf-On Conditions: Development, Results and Future Direction

Full-Waveform lidar measurements provide unprecedented views of the vertical and horizontal structure of vegetation and the topography of the Earth s surface. Utilizing a high signal-to-noise ratio lidar system, larger than typical laser footprints (10-20 m), and the recorded time history of interaction between a short-duration (approx. 10 ns) pulse of laser light and the surface of the Earth, full-waveform lidar is able to simultaneously image sub-canopy topography as well as the vertical structure of any overlying vegetation. These data reveal the true 3-D vegetation structure in leaf-on conditions enabling important biophysical parameters such as above-ground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted July-August 2003 in support of the North America Carbon Program. NASA s Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 km$^2$ in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate as many bio- and geophysical investigations as possible. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces. Data will be publicly distributed within 6- 12 months of collection. Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products will be presented. Future applications including detection of ground and vegetation canopy changes and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.

Blair, James B.↗