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At least 199 records · Page 11

Spectral modelling of multicomponent landscapes in the Sahel

Simple additive models are used to examine the infuence of differing soil types on the spatial average spectral reflectance and normalized difference vegetation index (NDVI). The spatial average NDVI is shown to be a function of the brightness (red plus near-infrared reflectances), the NDVI, and the fractional cover of the components. In landscapes where soil and vegetation can be considered the only components, the NDVI-brightness model can be inverted to obtain the NDVI of vegetation. The red and near-infrared component reflectances of soil and vegetation are determined on the basis of aerial photoradiometer data from Mali. The relationship between the vegetation component NDVI and plant cover is found to be better than between the NDVI of the entire landscape and plant cover. It is concluded that the usefulness of this modeling approach depends on the existence of clearly distinguishable landscape components.

Hanan, N. P.↗

Fusion of Multiple Low-Resolution NASA Airborne Snow Observatory (ASO) Lidar Data for Forest Vegetation Structure Characterization

Airborne lidar provides timely updated maps for monitoring forest change at high resolution but it has been little used for that purpose due to the scarcity of long-term time-series over a common area. The NASA Jet Propulsion Laboratory Airborne Snow Observatory (ASO) is a landscape-level monitoring system that provides ongoing multi-year remote sensing measurements over mountainous ecosystems to primary quantify snow volume and dynamics. It collects low-resolution lidar data (~1.5 pt/m2) with a nominal weekly frequency up to 12 times a year with measurements that span 2013-2017 over 12 mountain watersheds across the western US that currently face ecological threads. In this work, we present a method to automatically register ASO weekly low-resolution lidar point clouds in order to calculate spatially consistent datasets (~12 pt/m2) adapted to fine scale forestry studies. We test the method using 12 lidar datasets acquired over the Tuolumne River Basin (Sierra Nevada, California) in the spring and summer of 2014. On average, the ASO lidar system provides accurate measurements in terms of geolocation (0.38m and 0.12m for the horizontal and vertical dimension, respectively) but some datasets are biased up to 1.38m and 0.53m, respectively. Our registration method successfully corrected for systematic bias improving the 3D geometry of forest point clouds.

Painter, Thomas H.↗

Urban area delineation and detection of change along the urban-rural boundary as derived from LANDSAT digital data

LANDSAT digital multispectral scanner data, in conjunction with supporting ground truth, were investigated to determine their utility in delineation of urban-rural boundaries. The digital data for the metropolitan areas of Washington, D. C.; Austin, Texas; and Seattle, Washingtion; were processed using an interactive image processing system. Processing focused on identification of major land cover types typical of the zone of transition from urban to rural landscape, and definition of their spectral signatures. Census tract boundaries were input into the interactive image processing system along with the LANDSAT single and overlayed multiple date MSS data. Results of this investigation indicate that satellite collected information has a practical application to the problem of urban area delineation and to change detection.

Christenson, J. W.↗

Landsat Science: 40 Years of Innovation and Opportunity

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Cook, Bruce D.↗

An investigation of vegetation and other Earth resource/feature parameters using LANDSAT and other remote sensing data. 1: LANDSAT. 2: Remote sensing of volcanic emissions

A fanning technique based on a simplistic physical model provided a classification algorithm for mixture landscapes. Results of applications to LANDSAT inventory of 1.5 million acres of forest land in Northern Maine are presented. Signatures for potential deer year habitat in New Hampshire were developed. Volcanic activity was monitored in Nicaragua, El Salvador, and Guatemala along with the Mt. St. Helens eruption. Emphasis in the monitoring was placed on the remote sensing of SO2 concentrations in the plumes of the volcanoes.

Birnie, R. W.↗

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

Jagge, Amy↗

The Crop Evaluation Research for Environmental Strategies (CERES) Remote Sensing 2008 Project Activities

In recent years, the use of Plant Incorporated Protectant (PIP) corn by American producers has been increasing dramatically. PIP corn contains genetically inserted traits that produce toxins in the plant that provide narrowly targeted protection against specific insect pests. The plant producing t oxms can offer significant reductions in the application of broad -spectrum pesticides that have ecological and human health consequences. PIP corn as a percentage of total corn acreage planted in the US is expected to continue to increase as these protective traits are "stacked" with other desirable traits by seed companies, and producers are seeing considerable increases in corn yield as a result. The introduction of corn as a bio-fuel source for ethanol has increased production by over 6 million hectares in 2007. The United States Environmental Protection Agency (USEPA), which is responsible for the registration of PIP crops under the Federal Insecticide, Fungicide and Rodenticide Act, views the use of PIP corn as positive. Broad spectrum pesticide use has declined since the PIP traits have been introduced. As the agricultural landscape sees a higher percentage of corn acres using the PIP technology, the risk of the targeted insect pest populations developing resistance to the toxins, thereby rendering the in will increase as well. This result would negate the effectiveness of the PIP corn traits and could reduce production of a US field corn crop valued at $33 billion dollars in 2006 and place US food and now energy security at risk. Concerns over insect pest resistance development to PIP traits have led the USEPA to team with NASA and the Institute for Technology Development (ITD) to develop geo-spatial technologies designed to proactively monitor the corn production landscape for insect pest infestation and possible resistance development. USEPA resistance management simulation models are combined with NASA remote sensi ng products to monitor the corn landscape for resistance development. The two agencies have entered into an agreement which could potentially lead to the development of next generation NASA sensors that will more specifically address the requirements of the USEPA's resistance development strategy and offer opportunities to study the ever changing ecosystem complexities. The USEPA/NASA/ITD team has developed a broad research project entitled CERES (Crop Evaluation Research for Environmental Strategies). CERES is a research effort leading to decision support system tools that are designed to integrate multi-resolution NASA remote sensing data products and USEPA geo -spatial models to monitor the potential for insect pest resistance development from the regional to the landscape and then to the field level.

Casas, Joseph C.↗

The Future of Oaks in the Santa Monica Mountains: A Case Study in Using Remote Sensing Data for Species Distributions Models

The Woolsey Fire began on November 8, 2018, and lasted for almost two weeks, during which it burned almost 100,000 acres of valuable landscape and habitat, including a vast area of woodland. The persistence of key woodland species provides aesthetic, monetary, and ecological value to the landscape through carbon sequestration, air temperature moderation, and erosion mitigation, among other ecosystem services. This study investigated the impact of the Woolsey Fire on native woodland species distributions and identified areas suitable for restoration within the Santa Monica Mountains National Recreation Area. The team partnered with the Resource Conservation District of the Santa Monica Mountains; National Park Service, Santa Monica Mountains National Recreation Area; California Department of Parks and Recreation, Los Angeles County Division; County of Los Angeles Fire Department, Prevention Services Bureau, Forestry Division; County of Los Angeles Department of Regional Planning; and the University of Montana. The Earth observations used include data from Landsat 8 Operational Land Imager, NASA ER-2 Jet Airborne Visible InfraRed Imaging Spectrometer, Shuttle Radar Topography Mission, and RapidEye. The team produced maps of burn severity from the Woolsey Fire, its impact on plant species distributions, and habitat suitability projections for 2050 and 2099 to assist partners in prioritizing areas for restoration. A plant community classification was successfully created using Multiple Endmember Spectral Mixture Analysis (MESMA). Overall accuracy was assessed at 90.54% by comparing the classification to validation pixels derived from ground truth information provided by our partners.

Roger Ly↗

The development of the human exploration demonstration project (HEDP), a planetary systems testbed

The Human Exploration Demonstration Project (HEDP) is an ongoing task at the National Aeronautics and Space Administration's Ames Research Center to address the advanced technology requirements necessary to implement an integrated working and living environment for a planetary surface habitat. The integrated environment will consist of life support systems, physiological monitoring of project crew, a virtual environment workstation, and centralized data acquisition and habitat systems health monitoring. There will be several robotic systems on a simulated planetary landscape external to the habitat environment to provide representative work loads for the crew. This paper describes the status of the HEDP after one year, the major facilities composing the HEDP, the project's role as an Ames Research Center testbed, and the types of demonstration scenarios that will be run to showcase the technologies.

Chevers, Edward S.↗

Functional patterns in an annual grassland during an AVIRIS overflight

This study relates Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery to ground measurements of vegetation distribution, physiology, and productivity at Stanford University's Jasper Ridge Biological Preserve. Primary efforts focused on a 9-ha region of annual grassland where we completed a detailed ground-based study in conjunction with a 15 May 1991 AVIRIS overflight. Spectral mixture analysis and the normalized difference vegetation index (NDVI) calculated from AVIRIS data were used to evaluate spatial patterns of vegetation type, productivity, and potential physiological activity. Concurrent ground sampling revealed a high degree of correlation between NDVI and estimates of canopy chemistry, structure, productivity, and CO2 flux, supporting the use of imaging spectrometry to estimate spatial and temporal trends in vegetation physiology and productivity in this relatively simple grassland ecosystem. Geostatistical analyses of both ground and AVIRIS data supported the conclusion that the AVIRIS pixel size was suitable for describing the influence of major landscape features in this grassland and that spatial detail would be lost at slightly larger pixel sizes typical of other imaging spectrometers.

Gamon, John A.↗

Converting Topographic Maps into Digital Form to Aid in Archeological Research in the Peten, Guatemala

The purpose of my project was to convert a topographical map into digital form so that the data can be manipulated and easily accessed in the field. With the data in this particular format, Dr. Sever and his colleagues can highlight the specific features of the landscape that they require for their research of the ancient Mayan civilization. Digital elevation models (DEMs) can also be created from the digitized contour features adding another dimension to their research.

Aldrich, Serena R.↗

The Impact of Rise of the Andes and Amazon Landscape Evolution on Diversification of Lowland terra-firme Forest Birds

Since the 19th Century, the unmatched biological diversity of Amazonia has stimulated a diverse set of hypotheses accounting for patterns of species diversity and distribution in mega-diverse tropical environments. Unfortunately, the evidence supporting particular hypotheses to date is at best described as ambiguous, and no generalizations have emerged yet, mostly due to the lack of comprehensive comparative phylogeographic studies with thorough trans-Amazonian sampling of lineages. Here we report on spatial and temporal patterns of diversification estimated from mitochondrial gene trees for 31 lineages of birds associated with upland terra-firme forest, the dominant habitat in modern lowland Amazonia. The results confirm the pervasive role of Amazonian rivers as primary barriers separating sister lineages of birds, and a protracted spatio-temporal pattern of diversification, with a gradual reduction of earlier (1st and 2nd) and older (> 2 mya) splits associated with each lineage in an eastward direction. (The easternmost tributaries of the Amazon, the Xingu and Tocantins Rivers, are not associated with any splits older than > 2 mya). For the suboscine passerines, maximum-likelihood estimates of rates of diversification point to an overall constant rate over the past 5 my (up to a significant downturn at 300,000 y ago). This "younging-eastward" pattern may have an abiotic explanation related to landscape evolution. Triggered by a new pulse of Andean uplift, it has been proposed that modern Amazon basin landscapes may have evolved successively eastward, away from the mountain chain, starting approximately 10 mya. This process was likely based on the deposition of vast fluvial sediment masses, known as megafans, that may have extended progressively and in series eastward from Andean sources. This process plausibly explains the progressive extinction of original Pebas wetland of western-central Amazonia by the present fluvial landsurfaces of a more terra-firme type. The youngest landsurfaces thus lie furthest from the mountains. In this scenario major drainages were also reoriented in wholesale fashion away from a northerly orientation generally towards the east and an Atlantic Ocean outlet. The advance of megafans is best seen by the location of axial rivers such as the Orinoco and Mamore which lie against the cratonic margins furthest from the Andes, at the distal ends of major megafan ramparts. More importantly, other major river courses in western-central Amazonia will have been established at progressively younger dates with distance eastward. If this landscape-sequence scenario is accurate, it parallels the progressive younging of the passerine lineages. The bird DNA data appears to confirm strongly the pervasive role of Amazonian rivers--as primary barriers separating sister lineages of birds, and thus probably as facilitaters of bird speciation. We show for the first time that a general spatio-temporal pattern of diversification for terra-firme lineages in the Amazon is associated with rivers ("younging-eastward"), and furthermore parallels a specific scenario of regional drainage evolution.

Aleixo, Alexandre↗

The Next Landsat Satellite: The Landsat Data Continuity Mission

The Landsat program is one of the longest running satellite programs for Earth observations from space. The program was initiated by the launch of Landsat 1 in 1972. Since then a series of six more Landsat satellites were launched and at least one of those satellites has been in operations at all times to continuously collect images of the global land surface. The Department of Interior (DOI) U.S. Geological Survey (USGS) preserves data collected by all of the Landsat satellites at their Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. This 40-year data archive provides an unmatched record of the Earth's land surface that has undergone dramatic changes in recent decades due to the increasing pressure of a growing population and advancing technologies. EROS provides the ability for anyone to search the archive and order digital Landsat images over the internet for free. The Landsat data are a public resource for observing, characterizing, monitoring, trending, and predicting land use change over time providing an invaluable tool for those addressing the profound consequences of those changes to society. The most recent launch of a Landsat satellite occurred in 1999 when Landsat 7 was placed in orbit. While Landsat 7 remains in operation, the National Aeronautics and Space Administration (NASA) and the DOI/ USGS are building its successor satellite system currently called the Landsat Data Continuity Mission (LDCM). NASA has the lead for building and launching the satellite that will carry two Earth-viewing instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will take images that measure the amount of sunlight reflected by the land surface at nine wavelengths of light with three of those wavelengths beyond the range of human vision. T1RS will collect coincident images that measure light emitted by the land surface as a function of surface temperature at two longer wavelengths well beyond the range of human vision. The DOI/USGS is developing the ground system that will command and control the LDCM satellite in orbit and manage the OLI and TIRS data transmitted by the satellite. DOI/USGS will thus operate the satellite and collect, archive, and distribute the image data as part of the EROS archive. DOI/USGS has committed to renaming LDCM as Landsat 8 following launch. By either name the satellite and its sensors will extend the 40-year archive with images sufficiently consistent with data from earlier Landsat satellites to allow multi-decadal, broad-area studies of our dynamic landscapes. The next Landsat satellite and ground system are on schedule for a January, 2013 launch.

Rons, James R.↗

Evaluation of Spaceborne L-band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada

The landscape freeze/thaw (FT) state has an important impact on the surface energy balance, carbon fluxes, and hydrologic processes; the timing of spring melt is linked to active layer dynamics in permafrost areas. L-band (1.4 GHz) microwave emission could allow the monitoring of surface state dynamics due to its sensitivity to the pronounced permittivity difference between frozen and thawed soil. The aim of this paper is to evaluate the performance of both Aquarius and Soil Moisture and Ocean Salinity (SMOS) L-band passive microwave measurements using a polarization ratio-based algorithm for landscape FT monitoring. Weekly L-band satellite observations are compared with a large set of reference data at 48 sites across Canada spanning three environments: tundra, boreal forest, and prairies. The reference data include in situ measurements of soil temperature (Tsoil) and air temperature (Tair), and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover area (SCA) products. Results show generally good agreement between Lband FT detection and the surface state estimated from four reference datasets. The best apparent accuracies for all seasons are obtained using Tair as the reference. Aquarius radiometer 2 (incidence angle of 39.6) data gives the best accuracies (90.8), while for SMOS the best results (87.8 of accuracy) are obtained at higher incidence angles (55- 60). The FT algorithm identifies both freeze onset and end with a delay of about one week in tundra and two weeks in forest and prairies, when compared to Tair. The analysis shows a stronger FT signal at tundra sites due to the typically clean transitions between consistently frozen and thawed conditions (and vice versa) and the absence of surface vegetation. Results in the prairies were poorer because of the influence of vegetation growth in summer (which decreases the polarization ratio) and the high frequency of ephemeral thaw events during winter. Freeze onset and end maps created from the same algorithm applied to SMOS and Aquarius measurements characterize similar FT patterns over Canada. This study shows the potential of using L-band spaceborne observations for FT monitoring, but underlines some limitations due to ice crusts in the snowpack, liquid water content in snow cover during the spring freeze to thaw transition, and vegetation growth.

soil freeze/thaw↗

Dare Mighty Things

Winston Churchill once said, “To improve is to change; to be perfect is to change often.” JPL’s Property Accountability objective is to provide superior services related to property accountability, reutilization, and disposition. JPL must report property reutilized and disposed through either sales, donation, or scrap. Implementing the JPL designed and built Property Information Reporting System (PIRS), opened a new perspective with our data and what are we reporting to NASA. With this new depth of visibility, we self-implemented as assessment to validate the fiduciary and stewardship responsibilities of what is being reporting to NASA. JPL strives to perform at a level beyond the basic primary expectations of our NASA requirements. JPL developed the PIRS - which rolled out in 2018 - to simplify the delivery of JPL’s Personal Property and Equipment (PP&E) reporting: PIRS takes the raw data from Oracle to generate the NASA Form (NF) 1018 and Contractor Held Asset Reporting System (CHATS) Reports, and to meet the requirements established for AS9100 compliance. The data presented from PIRS is exportable and used to analyze our property records. JPL is also embarking on an effort to define the JPL of the future with “Enterprise 2.0”. Enterprise 2.0 is the driving force of JPL’s strategy to digitally transform the Laboratory from the current legacy processes and systems to a modern, integrated, information-driven highway of business transactions. This should include automation of routine processes and data-related tasks, integration of data and systems, advanced search and analytics, and improved information sharing and collaboration. As JPL’s evolving landscape of digital technologies advance to meet the future, JPL Property Accountability is making strides to surpass these expectations. For every cause there is an effect: a revealing of something that aids in the further development and transformation of JPL best business practices.

Sucher, Jay M↗

Thermal signatures of urban land cover types: High-resolution thermal infrared remote sensing of urban heat island in Huntsville, AL

The main objective of this research is to apply airborne high-resolution thermal infrared imagery for urban heat island studies, using Huntsville, AL, a medium-sized American city, as the study area. The occurrence of urban heat islands represents human-induced urban/rural contrast, which is caused by deforestation and the replacement of the land surface by non-evaporating and non-porous materials such as asphalt and concrete. The result is reduced evapotranspiration and more rapid runoff of rain water. The urban landscape forms a canopy acting as a transitional zone between the atmosphere and the land surface. The composition and structure of this canopy have a significant impact on the thermal behavior of the urban environment. Research on the trends of surface temperature at rapidly growing urban sites in the United States during the last 30 to 50 years suggests that significant urban heat island effects have caused the temperatures at these sites to rise by 1 to 2 C. Urban heat islands have caused changes in urban precipitation and temperature that are at least similar to, if not greater than, those predicted to develop over the next 100 years by global change models. Satellite remote sensing, particularly NOAA AVHRR thermal data, has been used in the study of urban heat islands. Because of the low spatial resolution (1.1 km at nadir) of the AVHRR data, these studies can only examine and map the phenomenon at the macro-level. The present research provides the rare opportunity to utilize 5-meter thermal infrared data acquired from an airplane to characterize more accurately the thermal responses of different land cover types in the urban landscape as input to urban heat island studies.

Lo, Chor Pang↗

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗

Future Plans in US Flight Missions: Using Laser Remote Sensing for Climate Science Observations

Laser Remote Sensing provides critical climate science observations necessary to better measure, understand, model and predict the Earth's water, carbon and energy cycles. Laser Remote Sensing applications for studying the Earth and other planets include three dimensional mapping of surface topography, canopy height and density, atmospheric measurement of aerosols and trace gases, plume and cloud profiles, and winds measurements. Beyond the science, data from these missions will produce new data products and applications for a multitude of end users including policy makers and urban planners on local, national and global levels. NASA Missions in formulation including Ice, Cloud, and land Elevation Satellite (ICESat 2) and the Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI), and future missions such as the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS), will incorporate the next generation of LIght Detection And Ranging (lidar) instruments to measure changes in the surface elevation of the ice, quantify ecosystem carbon storage due to biomass and its change, and provide critical data on CO 2 in the atmosphere. Goddard's plans for these instruments and potential uses for the resulting data are described below. For the ICESat 2 mission, GSFC is developing a micro-pulse multi-beam lidar. This instrument will provide improved ice elevation estimates over high slope and very rough areas and result in improved lead detection for sea ice estimates. Data about the sea ice and predictions related to sea levels will continue to help inform urban planners as the changes in the polar ice accelerate. DESDynI is planned to be launched in 2017 and includes both lidar and radar instruments. GSFC is responsible for the lidar portion of the DESDynI mission and is developing a scanning laser altimeter that will measure the Earth's topography, the structure of tree canopies, biomass, and surface roughness. The DESDynI lidar will also measure and predict the response of ice masses to climate change and impact on sea level. Data from the lidar will ultimately be fused with radar data products with heretofore unseen results and applications. The 3-D structure of forests is critical to understanding the impact of land use and associated landscape changes on the habitat of life forms and consequently on their biodiversity. Lidar instruments are also under development to measure trace gases in the atmospheric such as CO2 and methane. GSFC is developing an active measurement approach to determine the CO2 column density and surface pressure for the proposed ASCENDS mission. The objective of this approach is to produce data on the amounts of anthropogenic and organic CO2 in the atmosphere with sufficient accuracy to meet the needs of target users including state, federal and international users as well as policy-related legislative, regulatory, and voluntary carbon-related management groups local to international interests. In summary, NASA will continue to rely on laser remote sensing for critical climate science observations and is committed to the development of the next generation of lidar instruments for a range of applications.

Callahan, Lisa W.↗