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NASA'S SERVIR Gulf of Mexico Project: The Gulf of Mexico Regional Collaborative (GoMRC)

The Gulf of Mexico Regional Collaborative (GoMRC) is a NASA-funded project that has as its goal to develop an integrated, working, prototype IT infrastructure for Earth science data, knowledge and models for the five Gulf U.S. states and Mexico, and to demonstrate its ability to help decision-makers better understand critical Gulf-scale issues. Within this preview, the mission of this project is to provide cross cutting solution network and rapid prototyping capability for the Gulf of Mexico region, in order to demonstrate substantial, collaborative, multi-agency research and transitional capabilities using unique NASA data sets and models to address regional problems. SERVIR Mesoamerica is seen as an excellent existing framework that can be used to integrate observational and GIs data bases, provide a sensor web interface, visualization and interactive analysis tools, archival functions, data dissemination and product generation within a Rapid Prototyping concept to assist decision-makers in better understanding Gulf-scale environmental issues.

Quattrochi, Dale A.↗

Continental Spatio-Temporal Data Analysis with Linear Spectral Mixture Model Using FOSS

This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS) unmixing model developed in C++ programming language with OpenCV package and boost C++ libraries in the NASA Earth Exchange (NEX). Visualization of the results is supported by GRASS GIS and statistical analysis is carried in R in a Linux system environment. FCLS was first tested on computer simulated data with Gaussian noise of various signal-to-noise ratio, and Landsat data of an agricultural scenario and an urban environment using a set of global end members of substrate (soils, sediments, rocks, and non-photosynthetic vegetation), vegetation that includes green photosynthetic plants and dark objects which encompasses absorptive substrate materials, clear water, deep shadows, etc. For the agricultural scenario, a spectrally diverse collection of 11 scenes of Level 1 terrain corrected, cloud free Landsat-5 TM data of Fresno, California, USA were unmixed and the results were validated with the corresponding ground data. To study an urbanized landscape, a clear sky Landsat-5 TM data were unmixed and validated with coincident World View-2 abundance maps (of 2 m spatial resolution) for an area of San Francisco, California, USA. The results were evaluated using descriptive statistics, correlation coefficient, RMSE, probability of success, boxplot and bivariate distribution function. Finally, FCLS was used for sub-pixel land cover analysis of the monthly WELD (Wen-enabled Landsat data) repository from 2008 to 2011 of North America. The abundance maps in conjunction with DMSP-OLS nighttime lights data were used to extract the urban land cover features and analyze their spatial-temporal growth.

Landsat Satellites↗

Celestial Mapping System

Celestial Mapping System (CMS) is a software platform developed by Dr. Agrawal’s team to generate virtual 3D globes for celestial bodies. Various layers are built on top of the virtual globe to provide visualization for high-resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. In her June 14th presentation, Dr. Agrawal will showcase the user interactive software platform to virtually travel the lunar terrain, place rovers and instruments on the surface of the moon and perform measurements of various geological features including permanently shadowed regions. Her team’s future goals include building interactive 3D globes for other planetary bodies such as Venus, Mars, and Titan in the solar system.

GIS system↗

Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world.

precipitation↗

Increasing Discovery and Usability of Earth Science Satellite Data with My NASA Data

For 20 years, the My NASA Data project at NASA Langley Research Center has developed innovative approaches to increase the use of NASA’s satellite data by learners. My NASA Data offers a variety of authentic Earth Science datasets and a data visualization tool, eliminating the need for educators and/or learners to obtain specialized knowledge of GIS data formats and software to access and use authentic Earth Science data. While there is no shortage of available data, as federal government agencies such as NASA house petabytes of freely accessible Earth Science datasets, much of the data are only available for download and visualization in specialized formats and software, limiting their accessibility to educators and learners, especially those in primary and secondary school. Using the Google Earth Engine platform, the My NASA Data team has recently reinvented their data visualization tool, called the Earth System Data Explorer (ESDE). The ESDE gives users the capability to explore over 60 Earth Science satellite datasets in a multitude of formats such as maps, graphs, and data table Its new and improved user interface design was developed based on the preferences of educators, whom the My NASA Data project has over 20 years’ experience working with. Earth Science and GIS Subject Matter Experts (SMEs) structured the data in a professional and scientific manner. During Fiscal Year 2023, the My NASA Data website received over 1 million digital engagements, with over one-third being visitors to the data visualization tool. These metrics highlight the interest in a visualization tool that is simple and free to use with reliable and trusted datasets. The ESDE empowers users to readily relate and analyze NASA Earth Science data within their area of interest. The team used a user-centered design (UCD) framework to receive and incorporate feedback into the application’s design. Core requested features include the ability to create time series graphs, comparative analysis of maps, and download the data as CSV file. Responses indicate that advances in data visualization tools such as the ESDE make authentic Earth Science data more accessible. This presentation will cover how the My NASA Data project develops tools to enhance data discovery and accessibility, as well as how SME and user suggestions are incorporated.

Desiray Wilson↗

Design and test of an object-oriented GIS to map plant species in the Southern Rockies

Elevational and latitudinal shifts occur in the flora of the Rocky Mountains due to long term climate change. In order to specify which species are successfully migrating with these changes, and which are not, an object-oriented, image-based geographic information system (GIS) is being created to animate evolving ecological regimes of temperature and precipitation. Research at the Earth Data Analysis Center (EDAC) is developing a landscape model that includes the spatial, spectral and temporal domains. It is designed to visualize migratory changes in the Rocky Mountain flora, and to specify future community compositions. The object-oriented database will eventually tag each of the nearly 6000 species with a unique hue, intensity, and saturation value, so their movements can be individually traced. An associated GIS includes environmental parameters that control the distribution of each species in the landscape, and satellite imagery is used to help visualize the terrain. Polygons for the GIS are delineated as landform facets that are static in ecological time. The model manages these facets as a triangular irregular net (TIN), and their analysis assesses the gradual progression of species as they migrate through the TIN. Using an appropriate climate change model, the goal will be to stop the modeling process to assess both the rate and direction of species' change and to specify the changing community composition of each landscape facet.

Morain, Stanley A.↗

Crop-CASMA - A Web GIS Tool for Cropland Soil Moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Zhengwei Yang↗

Crop-CASMA - A Web GIS Tool for Cropland soil moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA - a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Reichle, Rolf H.↗

Making NASA GES DISC Level 2 Data GIS Analysis Ready

There are many valuable data hosted by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for GIS applications in the areas of extreme weather events, climatic anomaly, and public health. However, using NASA Earth Science Data poses some challenges for GIS users. Many of these users are not experts in Earth Observation and have little knowledge about NASA's Earth science data. In the GIS community, GeoTiff is the most widely used raster format, whereas NASA's data is primarily in complex multidimensional netCDF and HDF formats. This complexity makes it difficult for GIS users, especially those who are unfamiliar with these formats. Although GIS software like ArcGIS has made progress in processing multidimensional netCDF data, certain issues still remain, particularly with level 2 data. In this study, we use TROPSpheric Monitoring instrument (TROPOMI) level 2 data as an example to demonstrate how to make such data GIS analysis ready. The process involves: 1. Creating a feature layer from the TROPOMI level 2 data. 2. Converting the feature layer to a gridded raster dataset. 3. Mosaicking gridded raster datasets into a raster dataset covering the entire desired extent. 4. Generating a symbology with a GIBS-specific style that aligns with the visual standards and requirements of GIBS. 5. Publishing image services. By performing these preprocessing and transformation steps, NASA level 2 data can be made compatible and ready for use within GIS software for various spatial analysis and visualization tasks.

Geographic Information System↗

Earth Science and Remote Sensing Data Portal Earth Science and Remote Sensing Geospatial Data Portal

The Earth Science and Remote Sensing (ESRS) Data Portal, managed by the ESRS Unit at NASA's Johnson Space Center, is a web GIS environment built on Esri's ArcGIS Enterprise platform. Its current intent is to visualize, analyze, and distribute geospatial data to our internal organization and the communities of Houston and Galveston. Applications on the ESRS Data Portal include a Regional Remote Sensing web app, story maps developed for astronaut training, and a web scene for visualizing LiDAR.

Jagge, Amy M.↗

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗

Monitoring Areal Snow Cover Using NASA Satellite Imagery

The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data can be obtained from a digital elevation model (DEM) for the area of interest.

Harshburger, Brian J.↗

Category identification of changed land-use polygons in an integrated image processing/geographic information system

A framework is proposed for analyzing ancillary data and developing procedures for incorporating ancillary data to aid interactive identification of land-use categories in land-use updates. The procedures were developed for use within an integrated image processsing/geographic information systems (GIS) that permits simultaneous display of digital image data with the vector land-use data to be updated. With such systems and procedures, automated techniques are integrated with visual-based manual interpretation to exploit the capabilities of both. The procedural framework developed was applied as part of a case study to update a portion of the land-use layer in a regional scale GIS. About 75 percent of the area in the study site that experienced a change in land use was correctly labeled into 19 categories using the combination of automated and visual interpretation procedures developed in the study.

Westmoreland, Sally↗

VISUALIZING INTERANNUAL TO DECADAL COASTAL VARIABILITY NEAR VULNERABLE NASA INFRASTRUCTURE UTILIZING VIDEOS PRODUCED FROM REMOTELY SENSED DATA AT CAPE CANAVERAL, FL AND WALLOPS ISLAND, VA

Coastlines represent an interesting convolution of intense anthropogenic development superimposed onto morphologies that are among the most dynamic on the planet. Two of NASA’s critical facilities are particularly vulnerable to coastal change, Kennedy Space Center, Cape Canaveral, FL and Wallops Flight Facility, Wallops Island, VA. With continuing global sea level rise and increasing storminess coastal vulnerabilities at these facilities will only be exacerbated. These launch centers a subject to multiple coastal hazards including, flooding, episodic coastal erosion, saltwater intrusion, and coastal morphological changes. Although rapid change is readily observed during large storms or hurricanes, long term annual to decadal coastal change is much harder to visualize and conceptualize. The authors use videos developed from remotely sensed data to enhance conceptualization of coastal processes for planning and management stakeholders at these NASA facilities. Near or better than decadal coastal imagery has been available through high altitude photogrammetry efforts since the 1930’s. A significant amount of additional imagery was acquired through other federal, state, and local government agencies such as the USGS, NOAA, State DOT, and local Assessors Offices providing annual and inter annual images at spatial resolutions of 10cm – 1m. With the advent of GIS systems these images could be rectified and then layered to better understand change through time using a multitude of visual base shoreline proxies. With the increased awareness and use of video editing software the rectified images can be used to create videos. These videos can then be used to conceptualize a multitude of coastal processes including: performance of coastal restoration efforts, rapid change in sedimentation rates due to storms or other geomorphic processes, loss of protective barrier islands as sea level rises and lower sedimentation rates occur. The videos are also useful as a tool for verification and comparison to coastal models and provide an easy to understand educational resource for stakeholder engagement at these NASA centers, and other vulnerable coastal populations.

Richard A. MacKenzie III↗

Serving NASA GES DISC Multi-Spatiotemporal Earth Science Data to the GIS community

NASA Earth Science (ES) data is essential to a wide range of GIS research and applications. However, for many GIS users, searching, accessing, using and analyzing NASA ES data can be of a great challenge- ranging from the sheer data volumes, types of science parameters, and to the complexity of data encoding formats. As one of the twelve NASA Science Mission Directorate (SMD) Data Centers, Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes petabytes of ES parameters covering atmosphere, land, and ocean fields. Most data are multidimensional and multi-spatiotemporal in nature and are encoded in different science data formats (e.g, HDF, HDF-EOS, netCDF, GRIB, binary), which usually contain multiple variables and different metadata information. By far, GES DISC has been developing a number of services and online tools to help GIS users to easily explore our data products. In this presentation, we will describe our ArcGIS-based data accessing and visualization services and portals, which allow users directly exploring the multi-spatiotemporal ES data in ArcGIS clients without having to pre-download/import the data. The ArcGIS services are also compliant with the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and Web Map Service (WMS) protocols and can be accessed by any other WCS/WMS clients to get customized GES DISC EO data on-the-fly from such services.

Wei, Jennifer↗

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗

Emergency Response Virtual Environment for Safe Schools

An intelligent emergency response virtual environment (ERVE) that provides emergency first responders, response planners, and managers with situational awareness as well as training and support for safe schools is presented. ERVE incorporates an intelligent agent facility for guiding and assisting the user in the context of the emergency response operations. Response information folders capture key information about the school. The system enables interactive 3D visualization of schools and academic campuses, including the terrain and the buildings' exteriors and interiors in an easy to use Web..based interface. ERVE incorporates live camera and sensors feeds and can be integrated with other simulations such as chemical plume simulation. The system is integrated with a Geographical Information System (GIS) to enable situational awareness of emergency events and assessment of their effect on schools in a geographic area. ERVE can also be integrated with emergency text messaging notification systems. Using ERVE, it is now possible to address safe schools' emergency management needs with a scaleable, seamlessly integrated and fully interactive intelligent and visually compelling solution.

Wasfy, Ayman↗