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NASA NTRS2021

The Large Footprint of Small-scale Artisanal Gold Mining in Ghana

Gold mining has played a significant role in Ghana's economy for centuries. Regulation of this industry has varied over time and while industrial mining is prevalent in the country, the expansion of artisanal mining, or Galamsey has escalated in recent years. Many of these artisanal mines are not only harmful to human health due to the use of Mercury (Hg) in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal goldmines in Ghana from 2005 to 2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007 to 2017. A combination of machine learning and change detection algorithms were used to calculate different land cover conversions and the timing of conversion annually. Within the study area of southwestern Ghana, our results indicate that approximately 47,000 ha (⨦2218 ha) of vegetation were converted to mining at an average rate of ~2600 ha yr−1. The results indicate that a high percentage(~50%) of this mining occurred between 2014 and 2017. Around 700 ha of this mining occurred within protected areas as mapped by the World Database of Protected Areas. In addition to deforestation, increased artisanal mining activity in recent years has the potential to affect human health, access to drinking water resources and food security. This work expands upon limited research into the spatial footprint of Galamseyin Ghana, complements mapping efforts by local geographers, and will support efforts by the government of Ghana to monitor deforestation caused by artisanal mining.

Abigail Barenblitt↗

NASA NTRS2022

Laser Patterning Assisted Devitrification and Domain Engineering of Amorphous and Nanocrystalline Alloys

We have investigated laser-patterning and devitrification as a novel method to realize emergent properties in modified regions at the ribbon surface consisting of periodic localized laser spots thermally treated under rapid heating and cooling conditions. Fe-based amorphous ribbons were annealed for systematically varied laser power. Extremely high heating and cooling rates on the order of 10(exp 8)-10(exp 10)K/s have been estimated by finite element analysis simulations. Observations suggest surface melting followed by rapid solidification fast enough to quench and form an amorphous structure upon cooling. Diffusion of heat occurs from the laser irradiated surface region so that a finite volume of material surrounding this region rises in temperature above the crystallization temperature relevant for conventional isothermal annealing experiments. The underlying mechanism of laser annealing and consequences of heat transients involved are discussed in terms of impacts upon micro/nanostructure, residual stresses, and magnetic domain structure surrounding the laser irradiated region. The study illustrates the potential to exploit spatially optimized phase transformations in a scalable manufacturing process of amorphous and nanocrystalline alloys to locally access otherwise inaccessible extreme heating and cooling rates.

Amorphous ribbons↗

NASA NTRS2017

Investigating Access Performance of Long Time Series with Restructured Big Model Data

Data sets generated by models are substantially increasing in volume, due to increases in spatial and temporal resolution, and the number of output variables. Many users wish to download subsetted data in preferred data formats and structures, as it is getting increasingly difficult to handle the original full-size data files. For example, application research users such as those involved with wind or solar energy, or extreme weather events are likely only interested in daily or hourly model data at a single point (or for a small area) for a long time period, and prefer to have the data downloaded in a single file. With native model file structures, such as hourly data from NASA Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2), it may take over 10 hours for the extraction of parameters-of-interest at a single point for 30 years. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is exploring methods to address this particular user need. One approach is to create value-added data by reconstructing the data files. Taking MERRA-2 data as an example, we have tested converting hourly data from one-day-per-file into different data cubes, such as one-month, or one-year. Performance is compared for reading local data files and accessing data through interoperable services, such as OPeNDAP. Results show that, compared to the original file structure, the new data cubes offer much better performance for accessing long time series. We have noticed that performance is associated with the cube size and structure, the compression method, and how the data are accessed. An optimized data cube structure will not only improve data access, but also may enable better online analysis services

reanalysis↗

NASA NTRS1991

Architecture of a large object-oriented database for remotely sensed data

Attention is given to the proposed Intelligent Information Fusion System (IIFS) within the framework of the Intelligent Data Management project at NASA-Goddard. IIFS is to use connectionist architectures to extract high-level attributes from incoming sensor images, and then send those characterizations and their associated ephemeris and ancillary image data to a large object-oriented database which will serve as the master catalog of sensor data. Important issues facing this project include the choice of rapid-access data structures (RADSs) for cataloging images by their high-level characterization, the implementation of efficient spatial data structures for cataloging images by their scene location, the automated population of such a database from a continuous stream of incoming ephemeris and ancillary data, and the translation and optimization of natural-language database queries so that RADSs are employed when appropriate.

Dorfman, Erik↗

NASA NTRS2017

Obtaining and Using Planetary Spatial Data into the Future: The Role of the Mapping and Planetary Spatial Infrastructure Team (MAPSIT)

Planetary spatial data, which include any remote sensing data or derived products with sufficient positional information such that they can be projected onto a planetary body, continue to rapidly increase in volume and complexity. These data are the hard-earned fruits of decades of planetary exploration, and are the end result of mission planning and execution. Maintaining these data using accessible formats and standards for all scientists has been necessary for the success of past, present, and future planetary missions. The Mapping and Planetary Spatial Infrastructure Team (MAPSIT) is a group of planetary community members tasked by NASA Headquarters to work with the planetary science community to identify and prioritize their planetary spatial data needs to help determine the best pathways for new data acquisition, usable product derivation, and tools/capability development that supports NASA's planetary science missions.

Radebaugh, J.↗

NASA NTRS2016

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long-standing "Digital Divide" in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time-varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long-time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed "data rods," are pre-generated or generated on-the-fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on "data curtains." The on-the-fly generation of data rods uses "data cubes," NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.

data rods↗

NASA NTRS1994

Optimizing tertiary storage organization and access for spatio-temporal datasets

We address in this paper data management techniques for efficiently retrieving requested subsets of large datasets stored on mass storage devices. This problem represents a major bottleneck that can negate the benefits of fast networks, because the time to access a subset from a large dataset stored on a mass storage system is much greater that the time to transmit that subset over a network. This paper focuses on very large spatial and temporal datasets generated by simulation programs in the area of climate modeling, but the techniques developed can be applied to other applications that deal with large multidimensional datasets. The main requirement we have addressed is the efficient access of subsets of information contained within much larger datasets, for the purpose of analysis and interactive visualization. We have developed data partitioning techniques that partition datasets into 'clusters' based on analysis of data access patterns and storage device characteristics. The goal is to minimize the number of clusters read from mass storage systems when subsets are requested. We emphasize in this paper proposed enhancements to current storage server protocols to permit control over physical placement of data on storage devices. We also discuss in some detail the aspects of the interface between the application programs and the mass storage system, as well as a workbench to help scientists to design the best reorganization of a dataset for anticipated access patterns.

Chen, Ling Tony↗

NASA NTRS1989

Development of an intelligent interface for adding spatial objects to a knowledge-based geographic information system

Earth Scientists lack adequate tools for quantifying complex relationships between existing data layers and studying and modeling the dynamic interactions of these data layers. There is a need for an earth systems tool to manipulate multi-layered, heterogeneous data sets that are spatially indexed, such as sensor imagery and maps, easily and intelligently in a single system. The system can access and manipulate data from multiple sensor sources, maps, and from a learned object hierarchy using an advanced knowledge-based geographical information system. A prototype Knowledge-Based Geographic Information System (KBGIS) was recently constructed. Many of the system internals are well developed, but the system lacks an adequate user interface. A methodology is described for developing an intelligent user interface and extending KBGIS to interconnect with existing NASA systems, such as imagery from the Land Analysis System (LAS), atmospheric data in Common Data Format (CDF), and visualization of complex data with the National Space Science Data Center Graphics System. This would allow NASA to quickly explore the utility of such a system, given the ability to transfer data in and out of KBGIS easily. The use and maintenance of the object hierarchies as polymorphic data types brings, to data management, a while new set of problems and issues, few of which have been explored above the prototype level.

Campbell, William J.↗

NASA NTRS1992

Free-space laser communication technologies IV; Proceedings of the 4th Conference, Los Angeles, CA, Jan. 23, 24, 1992

Papers included in this volume are grouped under topics of receivers; laser transmitters; components; system analysis, performance, and applications; and beam control (pointing, acquisition, and tracking). Papers are presented on an experimental determination of power penalty contributions in an optical Costas-type phase-locked loop receiver, a resonant laser receiver for free-space laser communications, a simple low-loss technique for frequency-locking lasers, direct phase modulation of laser diodes, and a silex beacon. Particular attention is given to experimental results on an optical array antenna for nonmechanical beam steering, a potassium Faraday anomalous dispersion optical filter, a 100-Mbps resonant cavity phase modulator for coherent optical communications, a numerical simulation of a 325-Mbit/s QPPM optical communication system, design options for an optical multiple-access data relay terminal, CCD-based optical tracking loop design trades, and an analysis of a spatial-tracking subsystem for optical communications.

Begley, David L.↗

NASA NTRS2000

Elemental, Isotopic, and Organic Analysis on Mars with Laser TOF-MS

The in-depth landed exploration of Mars will require increasingly sophisticated robotic analytical tools for both in situ composition science [1] and reconnaissance for sample return [2]. Beyond dust, rock surfaces, and topsoil, samples must be accessed within rocks and ice, well below surface soil, and possibly in elevated deposit layers. A range of spatial scales will be studied, and for the most information-rich microscopic analyses, samples must be acquired, prepared, and positioned with high precision. In some cases samples must also be brought into a vacuum chamber. After expending such resources, it will be important to apply techniques that provide a wide range of information about the samples. Microscopy, mineralogy, and molecular/organic, elemental, and isotopic analyses are all needed, at a minimum, to begin to address the in situ goals at Mars. These techniques must work as an efficient suite to provide layers of data, each layer helping to determine if further analysis on a given sample is desired. In the spirit of broad-band and efficient data collection, we are developing miniature laser time-of-flight mass spectrometers (TOF-MS) for elemental, isotopic, and molecular/organic microanalysis of unprepared solid samples. Laser TOF-MS uses a pulsed laser to volatilize and ionize material from a small region on the sample. The laser energy and focus can be adjusted for atomic and molecular content, sampling area, and depth. Ions travel through the instrument and are detected at a sequence of times proportional to the square root of their mass-to- charge ratios. Thus, each laser pulse produces a complete mass spectrum (in less than 50 microseconds). These instruments can now be significantly miniaturized (potentially to the size of a soda can) without a loss in performance. This effort is reviewed here with an emphasis on applications to Mars exploration.

Brinckerhoff, W. B.↗

NASA NTRS2005

Geographic Information Systems and Martian Data: Compatibility and Analysis

Planning future landed Mars missions depends on accurate, informed data. This research has created and used spatially referenced instrument data from NASA missions such as the Thermal Emission Imaging System (THEMIS) on the Mars Odyssey Orbiter and the Mars Orbital Camera (MOC) on the Mars Global Surveyor (MGS) Orbiter. Creating spatially referenced data enables its use in Geographic Information Systems (GIS) such as ArcGIS. It has then been possible to integrate this spatially referenced data with global base maps and build and populate location based databases that are easy to access.

Jones, Jennifer L.↗

NASA NTRSDate not supplied

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗

NASA NTRS2008

Hail Size Distribution Mapping

A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at . 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, ). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.

Source record↗

NASA NTRS2005

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗

NASA NTRSDate not supplied

Milwaukee Urban Development: Assessing the Drivers of Urban Flood Vulnerability in Milwaukee using the Integrated Valuation of Ecosystem Services and Tradeoffs Urban Flood Risk Mitigation Model (InVEST)

Milwaukee County has experienced an increase in flooding due to climate change and urbanization. The frequency and severity of flooding vary spatially due to differences in land cover, surface permeability, and infrastructure. Marginalized communities tend to experience disproportionately high flooding and damage due to infrastructural inequalities and limited access to resources. To quantify these differences, we used the Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model to calculate and create maps of runoff retention, nominal flood depth, and economic damage to buildings in Milwaukee. Our model inputs included land cover, surface permeability, and rainfall. To inform our precipitation inputs, we used NASA’s Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) and National Weather Service (NWS) data. We assessed the relationship between flood risk and social and environmental spatial data including redlining, racial demographics, greenspace, and community resilience. The data demonstrate that flood risk is higher in historically redlined neighborhoods, majority Hispanic and Black census block groups, areas that lack parks and trees, and areas of low community resilience as measured by the Census Bureau’s Community Resilience Estimates (CRE). These findings will support our partners, Groundwork Milwaukee and Groundwork USA, in their efforts to promote the equitable distribution of resources and support environmental health in urban spaces. The end products of this project provide our partners with tools to assess urban flooding vulnerability, guide future intervention projects, quantify the effects of environmental injustice, and improve stakeholder access to data.

Madeleine Tango↗

NASA NTRS2022

Milwaukee Urban Development: Assessing the Drivers of Urban Flooding Vulnerability in Milwaukee Using NASA Earth Observations

Madeleine Tango↗

NASA NTRS1996

Was the MSSTA 2 mission successful?

The Multi-Spectral Solar Telescope Array (MSSTA) is a rocket borne solar observatory designed to address a wide range of scientific questions relating to two aspects of the structure and dynamics of the solar atmosphere: (1) The heating and dynamics of chromospheric and coronal structures including spicules, coronal loops, bright points, and planes; and the role of the fine scale structure of the chromospheric network in the transport of mass and energy between these structures, and (2) The large scale structures of the corona, including the interface of prominences and filaments with material at coronal temperatures, the transition region structure of coronal holes and plumes, and their relationship to the solar wind. In order to address these fundamental scientific problems, the observational objective of the MSSTA is to obtain a set of high resolution spectroheliograms with the following properties: (1) Sufficiently broad spectral coverage and accurate photometry to allow modeling of structures covering the full range of temperatures observed in non-flaring chromosphere/corona, 10(exp 4) K to 10(exp 7) K; (2) Sufficient spectral resolution (lambda / delta lambda approx. 30-100) in each spectroheliogram to allow isolation of the emission from lines excited over a narrow range of temperatures; (3) To address objective (a), spatial resolution sufficient to resolve structures on the sun on a scale of 100-200 km (0.1-0.3 arc seconds); to address objective (b), images of the full disk and inner corona with resolution at least 1.0 arc second, and high sensitivity images of the extended corona (to approx. 3-4 solar radii above the limb) with resolution of approx. 3 arc seconds; for both objectives (c), direct measurements of the coronal magnetic field. (4) To access the role of non-thermal phenomena in the heating and dynamics of the chromosphere/corona interface, high resolution (lambda / delta lambda greater than 1000) spectroheliograms with spatial resolution of 1-3 arc seconds.

Spencer, Dwight C.↗

NASA NTRS1973

Design relationships for holographic memories.

The maximum capacity of a block-oriented, random-access memory is determined primarily by the geometrical parameters of the lenses required to create a Fourier transform of a spatial bit pattern and to image the reconstructed bits onto a photodetector array. Furthermore, the maximum packing density is determined primarily by the same parameters. Several important relationships are developed that are useful in the preliminary design of holographic memories.

Lugt, A. V.↗