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NASA NTRS1977

Earth resources-regional transfer activity contracts review

A regional transfer activity contracts review held by the Earth Resources Office was summarized. Contracts in the earth resources field primarily directed toward applications of satellite data and technology in solution of state and regional problems were reviewed. A summary of the progress of each contract was given in order to share experiences of researchers across a seven state region. The region included Missouri, Kentucky, Tennessee, Mississippi, Alabama, Georgia, and North Carolina. Research in several earth science disciplines included forestry, limnology, water resources, land use, geology, and mathematical modeling. The use of computers for establishment of information retrieval systems was also emphasized.

Bensko, J., Jr.↗

NASA NTRS2005

Understanding What's Critical in Protecting Our Society: Can Satellite Observations Help?

There are many vital issues which are impacting our daily lives and will continue to haunt us as long as we live on this planet of ours. These issues range from food supply availability, drought, coastal zone erosion, volcanoes, hurricanes, terrorism, global warming, earthquakes, water resources, air quality, public health, and agriculture production. Such societal needs are directly linked to our geometric population growth, and abundance of automobiles, industrial emissions, industrial waste and extensive fishing of our oceans and elimination of our ecology. The questions which require serious thoughts, research, coordination, and resources to understand, plan and strike a sensible balance in our daily lives and the above issues are tough to deal with. However, with the advent of remote sensing technologies, tremendous progress has been made in applying space-based and airborne data and products in solving real societal problems. Several of these problems, such as coastal zone erosion, air quality, severe weather, water availability and quality, public health, fires, land slides and others are intricately related; and in the long run can have serious consequences if not properly addressed by scientists, regulatory bodies and policy makers. Although it is a much involved and tangled web to unravel, nevertheless we have an excellent start in understanding some of the phenomena and hopefully can mitigate some of the severe effects by advancing our scientific knowledge. This paper briefly discusses the applications of remote sensing data from Terra, Aqua, and other NASA satellites how to deal with such complex problems; it provides an excellent start.

Habib, Shahid↗

NASA NTRS2017

Satellite-Based Drought Reporting on the Navajo Nation

The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

Satellite-based↗

NASA NTRS2012

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Gail Skofronick-Jackson↗

NASA NTRS1975

Mobile data buoy system

The Mobile Data Buoy System was conceived to serve the users requirement for obtaining water quality parameters from two separate watershed systems. In view of the cost constraints of the ERTS program it was obvious that the network of 10 sampling stations required could not be of the fixed installation type; therefore, it was decided to go to a system of battery powered buoys of a size that could be used in one watershed system for a period of time and then moved to another by use of a relatively small 6.7 m (22 foot) boat. The basic idea of the water quality measurement program was to establish the water quality pattern of change from the headwaters of the watersheds to and through the Mobile Bay. This would allow the investigator to develop a good picture of the state's major water resources and the pressures from pollution that are being imposed. At this point in deployment of this mobile system of buoys, it is too early to put a quantitative value on the system, however it appears less expensive than known fixed installations as to first cost. It has a basic advantage in that it can be moved, at very little expense, to alternate sites where it is desired to obtain water quality data. It is to be noted this buoy system which covers a 80 Km (50 mile) stretch of the Black Warrior River and then skips down 483 Km (300 miles) to Mobile Bay for the next measurements would not be feasible unless there is a satellite to collect and relay the data.

Morton, R. A.↗

NASA NTRS1975

Collection of relevant results obtained with the ERTS-1 satellite images by the Institute for Space Research (INPE), volume 2

The author has identified the following significant results. Soil resource studies in Brazil have concluded that: areas with agricultural activities appear surrounding urban centers; some areas are suffering a strong erosion action; there exist two drainage systems near Paraguai River and Parana River; and this region possesses great variety of soil types. It is possible to count the number of lakes and sluices as well as their superficial area using a channel 7 photographic enlargement. The great concentration of water bodies along the Jacui River determines the large rice crops. Data concerning regions around Teresina City, Presidente Prudente, Piracicaba City, Dourados, and Tres Marias Dam revealed several characteristics concerning the soil and water resources. Two basic maps were made of the natural vegetation distribution over central eastern Brazil from data ERTS-1 data. One map shows the drainage system, the road system, and cities; while the second shows the natural vegetation. It was possible to identify old reforestation, new reforestation, natural forest in flat lands, and natural forest in rolling lands from the ERTS images. Different pasture plant species could be identified by multispectral remote sensing. Data obtained along different wavelength bands provide essential data for the range manager to evaluate his range and to establish a suitable policy. Hydrographic mapping was done using the ERTS images.

Demendonca, F.↗

NASA NTRS1977

An operational earth resources satellite system - The Landsat follow-on program

The Landsats 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The Landsat follow-on study addressed the economics, technological performance, and design of a system in transition from R&D to operations. Economic benefits were identified; and a complete system from sensors to the utilization in forecasting crop production, oil and mineral exploration, water resources management was designed. Benefits-to-costs ratio in present-worth dollars is at least 4:1.

Stroud, W. G.↗

NASA NTRS1978

Improved LANDSAT to give better view of earth resources

The launch data of LANDSAT 3 is announced. The improved capability of the spacecrafts' remote sensors (the return beam vidicon and the multispectral scanner) and application of LANDSAT data to the study of energy supplies, food production, and global large-scale environmental monitoring are discussed along with the piggyback amateur radio communication satellite-OSCAR-D, the plasma Interaction Experiment, and the data collection system onboard LANDSAT 3. An assessment of the utility of LANDSAT multispectral data is given based on the research results to data from studies of LANDSAT 1 and 2 data. Areas studied include agriculture, rangelands, forestry, water resources, environmental and marine resources, environmental and marine resources, cartography, land use, demography, and geological surveys and mineral/petroleum exploration.

Source record↗

NASA NTRS1977

An operational earth resources satellite system: The LANDSAT follow-on program

The LANDSATS 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The LANDSAT Follow-on Study addressed the economics, technological performance, and design of a system in transition from R and D to operations. Economic benefits were identified; and a complete system from sensors to the ultilization in forecasting crop production, oil and mineral exploration, and water resources management was designed.

Stroud, W. G.↗

NASA NTRS2011

Goddard DEVELOP Students: Using NASA Remote Sensing Technology to Study the Chesapeake Bay Watershed

The DEVELOP National Program is an Earth Science research internship, operating under NASA s Applied Sciences Program. Each spring, summer, and fall, DEVELOP interns form teams to investigate Earth Science related issues. Since the Fall of 2003, Goddard Space Flight Center (GSFC) has been home to one of 10 national DEVELOP teams. In past terms, students completed a variety of projects related to the Applied Sciences Applications of National Priority, such as Public Health, Natural Disasters, Water Resources, and Ecological Forecasting. These projects have focused on areas all over the world, including the United States, Africa, and Asia. Recently, Goddard DEVELOP students have turned their attention to a local environment, the Chesapeake Bay Watershed. The Chesapeake Bay Watershed is a complex and diverse ecosystem, spanning approximately 64,000 square miles. The watershed encompasses parts of six states: Delaware, Maryland, New York, Pennsylvania, Virginia, and West Virginia, as well as the District of Columbia. The Bay itself is the biggest estuary in the United States, with over 100,000 tributaries feeding into it. The ratio of fresh water to salt water varies throughout the Bay, allowing for a variety of habitats. The Bay s wetlands, marshes, forests, reefs, and rivers support more than 3,600 plant and animal species, including birds, mammals, reptiles, amphibians, fish, and crabs. The Bay is also commercially significant. It is ranked third in the nation in fishery catch, and supplies approximately 500 million pounds of seafood annually. In addition to its abundant flora and fauna, the Chesapeake Bay watershed is home to approximately 16.6 million people, who live and work throughout the watershed, and who use its diverse resources for recreational purposes. Over the past several decades, the population throughout the watershed has increased rapidly, resulting in land use changes, and ultimately decreasing the health of the Chesapeake Bay Watershed. Over the course of 2009-2010, student teams carried out two independent research projects focused on the Chesapeake Bay Watershed. The first investigated the threat of invasive species to forests in Maryland. The second investigated the detection of winter cover crops throughout the watershed from satellite data.

Moore, Rachel↗

NASA NTRSDate not supplied

Why Near Real-time/Low Latency is Important to Monitor the Changing World

An essential factor for remote sensing data products in impacting decision making is latency, or the time between earth observation and data are available to users. In many applications areas, latency plays an important or even decisive role where low latency earth observations help people to make timely, data-based decisions. Within the open and free NASA resources, NASA’s Land, Atmosphere Near real-time Capability for Earth Observing System (EOS) (LANCE) supports users interested in monitoring a wide variety of natural and man-made phenomena using near real-time (NRT) data products that are made available much quicker than routine processing allows. The combination of all available LANCE satellite products provides global coverage at multiple times per day, which makes it possible to meet user needs in various areas of applications including water resources, agriculture, air quality, wildland fire and many other disasters monitoring and management. As one of the prime users of LANCE, NASA’s Earth Science Applied Sciences Program promotes the use of LANCE data products to demonstrate applications in decision making and facilitates the end-user feedback to the science team to improve data products. One of the most critical applications that we expect data to be processed as close to the user as possible is wildland file response and management. User feedback indicates that LANCE NRT fire data products within 3 hours latency would meet the needs of the wildland fire community. Other examples of earth science application areas for which low latency is particularly important include detecting volcanic eruptions, early warning of disasters, tracking extreme weather events, and monitoring air quality.

Tian Yao↗

NASA NTRS2021

Tonlé Sap Food Security and Agriculture II: Evaluating Changes in Ecosystem Vitality and Freshwater Healthin the Tonlé Sap Basin using Remotely Sensed Data

The Tonlé Sap Lake and river basin in central Cambodia provide critical ecosystem services to the region, including fisheries, agricultural irrigation, hydropower, and biodiverse habitats. Deforestation, increased pumping for farming, and effects of climate change such as droughts and forest fires threaten the health of the lake and food security in the region. This project built upon the previous term through a partnership with Conservation International (CI), the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority to assess ecosystem vitality and implement CI’s Freshwater Health Index (FHI) tool, in an effort to prioritize resource expenditure and highlight areas of concern. Due to the COVID-19 pandemic and related travel restrictions, partners had not been able to readily collect in situ data for the past year, which make up the majority of FHI inputs. To help fill this data gap, we developed a methodology for using Gravity Recovery and Climate Experiment (GRACE) satellite data to calculate groundwater storage depletion, and a Python Application Programming Interface for processing and formatting remotely-sensed data for the Soil and Water Assessment Tool (SWAT) model. We then used SWAT to model nutrient flows and of phosphorous, nitrogen and suspended sediments amounts in the basin from October 2000 to December 2020. These outputs served as inputs for the FHI and provided policy makers with robust monitoring information to aid decision-making in the area and safeguard the lake’s vital fisheries and biodiversity.

Justine Spore↗

NASA NTRS1977

Economic Analysis in the Pacific Northwest Land Resources Project: Theoretical Considerations and Preliminary Results

The Pacific Northwest Land Resources Inventory Demonstration Project i s an a ttempt to combine a whole spectrum of heterogeneous geographic, institutional and applications elements in a synergistic approach to the evaluation of remote sensing techniques. This diversity is the prime motivating factor behind a theoretical investigation of alternative economic analysis procedures. For a multitude of reasons--simplicity, ease of understanding, financial constraints and credibility, among others--cost-effectiveness emerges as the most practical tool for conducting such evaluation determinatIons in the Pacific Northwest. Preliminary findings in two water resource application areas suggest, in conformity with most published studies, that Lands at-aided data collection methods enjoy substantial cost advantages over alternative techniques. The pntential for sensitivity analysis based on cost/accuracy tradeoffs is considered on a theoretical plane in the absence of current accuracy figures concerning the Landsat-aided approach.

Morse, D. R. A.↗

NASA NTRS2016

Design of an Excavation Robot: Regolith Advanced Surface Systems Operations Robot (RASSOR) 2.0

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. Acquiring the water resources on Mars will require mining significant quantities of regolith and this is not possible with the state-of-the-art low mass excavation systems. Low gravity environments (Mars = 3/8 G) and launch mass restrictions limit the traction and the resulting reaction force of the vehicle, making current terrestrial techniques impractical. This project addressed this challenge by developing a completely new technology that can mine large quantities of regolith on Mars. Recent measurements by the “Curiosity” rover on Mars have found that the regolith contains ~ 2% water by weight globally, ~4% in Jezero Crater (Human Architecture Team’s reference landing site), and much more at the poles(Leshin et al, 2013). RASSOR 2.0 is a planetary excavator, which has a mass of 66 kg, with a 0.38 kg vehicle mass per kilogram, per hour of excavation rate and power usage of 4 W per kg of regolith excavation rate. A single RASSOR 2.0 can excavate a minimum of 2.7 metric tons of regolith per day.This is accomplished by using counteracting excavation forces on two opposing digging implements called bucket drums and an autonomous mining control system. This work has addressed several major research areas outlined in the NASA Technology Area (TA) 04 Robotics & Autonomous Systems and TA 07 Human Destination Systems roadmaps. This project started at Technology Readiness Level (TRL) 4 as a low fidelity “proof of concept” prototype which has successfully demonstrated basic regolith simulant excavation functionality in a lab-scale gravity off load test. The foundational technology described here was awarded US patent number: US 9027265 for a “Zero horizontal reaction force excavator” on May 12, 2015.

RASSOR↗

NASA NTRS2022

Critical Soil Moisture Thresholds of Plant Water Stress in Terrestrial Ecosystems

Plant water stress occurs at the point when soil moisture (SM) limits transpiration, defining a critical SM threshold (θ crit ). Knowledge of the spatial distribution of θ crit is crucial for future projections of climate and water resources. Here, we use global eddy covariance observations to quantify θcrit and evaporative fraction (EF) regimes. Three canonical variables describe how EF is controlled by SM: the maximum EF (EF max ), θ crit , and slope (S) between EF and SM. We find systematic differences of these three variables across biomes. Variation in θ crit , S, and EFmax is mostly explained by soil texture, vapor pressure deficit, and precipitation, respectively, as well as vegetation structure. Dryland ecosystems tend to operate at low θ crit and show adaptation to water deficits. The negative relationship between θ crit and S indicates that dryland ecosystems minimize θcrit through mechanisms of sustained SM extraction and transport by xylem. Our results further suggest an optimal adaptation of local EF-SM response that maximizes growing-season evapotranspiration and photosynthesis.

Zheng Fu↗

NASA NTRS2011

Global Assimilation of Multi-Sensor Snow Observations for Improved Characterization of Snow Processes

Snow conditions on the land surface are recognized to be key components of the global hydrological cycle as they play a critical role in the determination of local and regional climate. In many mid-latitude and high-latitude regions, the seasonal water storage and associated spring snowmelt dominate the local hydrology. The contribution to the runoff and moisture conditions from snow is vital in supporting agriculture and in determining water resources management practices. Consequently, accurate characterization of snow properties becomes important for both end-use applications and weather and climate research. Recently a joint effort between the u.S. Air Force and NASA has enabled a blended, multi-sensor snow product known as the AFWA NASA Snow Algorithm (ANSA). This global snow dataset has been generated by utilizing the Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) datasets. ANSA product includes estimates of snow cover extent, snow water equivalent (SWE) and SWE-derived snow depth fields. The MODIS-based products enable snow cover mappings under cloud-free conditions whereas the passive microwave data from AMSR-E provides measurements under cloudy conditions. These remotely-sensed snow observations are further augmented with the information from ground-based snow measurements through data fusion techniques. The resulting ANSA products are employed in the NASA Land Information System (LIS) data assimilation framework, which provides a comprehensive environment for integrating community land surface models, ground and satellite-based observations, and ensemble-based data assimilation tools. LIS incorporates the multisensor ANSA snow retrievals with the land surface model estimates to generate spatially and temporally continuous estimates of snow states, through data assimilation. A suite of experiments to assimilate ANSA snow cover, SWE and snow depth estimates with different land surface models in LIS are conducted and the resulting estimates of snow conditions are evaluated against a number of in-situ observational datasets, over several regions of the world. These evaluations are used to compare and contrast the advantages and disadvantages of these multi-sensor snow observations.

Kumar, Sujay↗

NASA NTRS2011

Software Architecture to Support the Evolution of the ISRU RESOLVE Engineering Breadboard Unit 2 (EBU2)

The In-Situ Resource Utilization (ISRU) Regolith & Environmental Science and Oxygen & Lunar Volatiles Extraction (RESOLVE) software provides operation of the physical plant from a remote location with a high-level interface that can access and control the data from external software applications of other subsystems. This software allows autonomous control over the entire system with manual computer control of individual system/process components. It gives non-programmer operators the capability to easily modify the high-level autonomous sequencing while the software is in operation, as well as the ability to modify the low-level, file-based sequences prior to the system operation. Local automated control in a distributed system is also enabled where component control is maintained during the loss of network connectivity with the remote workstation. This innovation also minimizes network traffic. The software architecture commands and controls the latest generation of RESOLVE processes used to obtain, process, and quantify lunar regolith. The system is grouped into six sub-processes: Drill, Crush, Reactor, Lunar Water Resource Demonstration (LWRD), Regolith Volatiles Characterization (RVC) (see example), and Regolith Oxygen Extraction (ROE). Some processes are independent, some are dependent on other processes, and some are independent but run concurrently with other processes. The first goal is to analyze the volatiles emanating from lunar regolith, such as water, carbon monoxide, carbon dioxide, ammonia, hydrogen, and others. This is done by heating the soil and analyzing and capturing the volatilized product. The second goal is to produce water by reducing the soil at high temperatures with hydrogen. This is done by raising the reactor temperature in the range of 800 to 900 C, causing the reaction to progress by adding hydrogen, and then capturing the water product in a desiccant bed. The software needs to run the entire unit and all sub-processes; however, throughout testing, many variables and parameters need to be changed as more is learned about the system operation. The Master Events Controller (MEC) is run on a standard laptop PC using Windows XP. This PC runs in parallel to another laptop that monitors the GC, and a third PC that monitors the drilling/ crushing operation. These three PCs interface to the process through a CompactRIO, OPC Servers, and modems.

Moss, Thomas↗

NASA NTRS2015

Effects of Resolution and Spectral Nudging in Simulation the Effects of Wintertime Atmospheric River Landfalls in the Western US

Landfalling atmospheric rivers (ARs) play a crucial role in the climate of the US Pacific coast region as they are frequently related with heavy precipitation and flash flooding events. Thus, the capability of climate models to accurately simulate AR landfalls and their key hydrologic effects is an important practical concern for WUS, from flood forecasting to future water resources projections. In order to examine the effects of model configuration, including the resolution and spectral nudging, in simulating the climatology of key weather events in the conterminous US, a NASA team has performed a hindcast experiment using the GEOS5 global and the NU-WRF regional models for Nov 1999 - Oct 2010. This study examines the skill of these hindcasts, with different models and their configurations, in simulating key footprints of landfalling ARs in the WUS region. Using an AR-landfall chronology based on the vertically-integrated water vapor flux calculated from the MERRA2 reanalysis, we have analyzed the observed and simulated precipitation and temperature anomalies associated with wintertime AR landfalls along the US Pacific coast. Model skill is measured using metrics including regional means, a skill score based on correlations and mean-square errors, and Taylor diagrams in four WUS Bukovsky regions. Results show that the AR-related anomalies of precipitation is more reliable than of surface temperatures. Model skill also varies according to regions. The AR temperature anomalies are well simulated in most of the WUS region except PNW. For precipitation, simulations with finer spatial resolution tend to generate larger spatial variability and agree better with the PRISM data in most regions. Such a resolution dependence of spatial variability is not found for temperatures; e.g., the MERRA2 reanalysis often outperforms, with similar spatial variability and higher pattern correlations with the PRISM data, finer-resolution NU-WRF runs in simulating temperature variations within subregions. Results from this study will be summarized to assist future (regional) climate experiments for climate change impact assessments and developing adaptationmitigation strategies, the key elements of the National Climate Assessment.

Simulation↗