A key component of NASA's Earth Observing System is its field experiments, for intensive observation of particular phenomena such as hurricanes, or for ground validation of satellite observations. These field experiments collect many datasets from a wide variety of satellite, airborne, and ground-based instruments, on different spatial and temporal scales, often in unique formats. Such diverse environmental observations are important for physical process studies, disaster assessment and response, as well as for the validation of environmental satellite observations and atmospheric models, which can improve weather forecasts and representations of Earth’s past and future climate.
A commercial cloud service approved for use by NASA’s Office of the Chief Information Officer. For an introduction to AWS read NASA IT Talk, Jan-March 2018, v. 8, no. 1, NASA in the Cloud.
The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) was developed by NASA's LP DAAC and offers a simple and efficient way to access and transform geospatial data from a variety of federal data archives. AppEEARS enables users to subset geospatial datasets using spatial, temporal, and band/layer parameters. Two types of sample requests are available: point samples for geographic coordinates and area samples for spatial areas via vector polygons.
An application programming interface (API) is a set of defined rules that explain how computers or applications communicate with one another. APIs sit between an application and the web server and act as an intermediary layer that processes data transfer between systems.
Calibration and validation (often shortened to cal/val) are processes for ensuring the validity of remotely sensed data. Measurements acquired locally are compared with data from remote sensing satellites.
The web-based Catalog of Archived Suborbital Earth Science Investigations (CASEI) was developed by NASA’s Airborne Data Management Group (ADMG). CASEI facilitates quick access to detailed information about NASA’s airborne and field investigations along with links to associated data products.
Cloud computing is the ability to access and work with data virtually in a cloud-based environment. Analyses and data manipulations can be accomplished directly with data in the cloud with only the analysis results needing to be downloaded.
A Cloud Optimized GeoTIFF (COG) is a GeoTIFF that contains internal organization, which enables it to be efficiently delivered and processed on the cloud.
Commercial data refers to data created and provided by commercial entities rather than government agencies. NASA’s Commercial Smallsat Data Acquisition (CSDA) program identifies, evaluates, and acquires remote sensing imagery and data from commercial sources that support NASA’s Earth science research and application activities.
The Common Metadata Repository (CMR) is the definitive management system for EOSDIS Earth science metadata. As a single, shared, scalable metadata repository, CMR merges all current capabilities and metadata from the existing NASA Earth science metadata systems.
Cumulus is an ESDIS Project effort to prototype and test how EOSDIS data collections can be archived collectively and disseminated in the commercial cloud. A primary feature of Cumulus is a cloud-based framework for data ingest, archive, distribution, and management, which are the primary activities of the discipline-specific EOSDIS Distributed Active Archive Centers (DAACs).
Tools and resources which assist in the retrieval, manipulation, and display of Earth science data.
A data collection is an assemblage of data grouped according to a standardized hierarchy or organizing system.
The organization and integration of Earth science observation data collected from sensors in orbit, from airborne sources, or in-situ. It can involve collection, processing, archiving and publication of data so that the value of the data is maintained over time, and the data remains available for reuse and preservation.
Standardized ways that Earth science information is encoded for storage in a computer file. Different data formats describe the structure and compression of data, metadata requirements and the scope of the variables included to meet the varying needs of the data users.
Daymet provides long-term, continuous, gridded estimates of daily weather and climatology variables from ground-based observations through statistical modeling techniques. The Daymet data products provide driver data for biogeochemical terrestrial modeling and have myriad applications in many Earth science, natural resource, biodiversity, and agricultural research areas. Daymet weather variables include daily minimum and maximum temperature, precipitation, vapor pressure, shortwave radiation, snow water equivalent, and day length over continental North America and Hawaii and Puerto Rico.
Deep learning uses huge neural networks with many layers of processing units, taking advantage of advances in computing power and improved training techniques to learn complex patterns in large amounts of data. Common applications include image and speech recognition.
In the Earthdata Forum, subject matter experts from several NASA Distributed Active Archive Centers (DAAC) discuss general questions, research needs, and data applications. Users can query how to access, view, and interpret data.
Earthdata Search provides easy-to-use access to EOSDIS services for Earth science data discovery, filtering, visualization, and access. It also serves as a platform to feature planned EOSDIS services as they become available.
The Fire Information for Resource Management System (FIRMS) distributes Near Real-Time (NRT) active fire data within 3 hours of satellite observation from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites, and the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard S-NPP and NOAA 20 (formally known as JPSS-1).
GIS is a collection of computer-based tools for organizing information from a variety of data sources to map and examine changes on Earth. It is designed to capture, store, manage, analyze, and visualize all types of geographical data. GIS allows for the integration and collective analysis of geospatial data from multiple sources, including satellite imagery, GPS recordings, and textual attributes associated with a particular space.
GIS is used in nearly all fields that need to understand the spatial patterns and relationships between different datasets, from land-use planning to emergency response to resource management.
Our vision is to identify and deliver high value Earth Science data in formats compliant and compatible with GIS standards; to ensure data are interactive, interoperable, accessible, and GIS-enabled through primary GIS platforms; and to provide the maximum impact to research, education, and public user communities requiring visualization and spatial analysis.
GIS includes many components:
- visualizations through interactive maps,
- data based on the location of features or variables represented,
- spatial analytic functions that focus on identifying trends and patterns across space and time, and
- applications that enable tools and services in user-friendly interfaces.
Geospatial data are collected in a variety of ways. It is remotely sensed from instruments aboard airplanes and satellites, created from imagery, or captured in the field.
GIS data contain spatial coordinates to represent where features are located. This is typically done using latitude (y) and longitude (x) coordinates. Multidimensional data can include additional dimensions such as depth, elevation and/or time (z).
StoreNASA's Earth Observing System Data and Information System (EOSDIS) archives and distributes 41.86 petabytes (PB) of Earth observation data. This scientific data are often complex and rich with valuable information across multiple dimensions beyond time and space.
Multidimensional data and its associated metadata are stored in scientific data formats optimized for these data types. The most common specialized formats are Network Common Data Form (netCDF), Hierarchical Data Format (HDF), and Gridded Binary (GRIB). Some of the more common cloud-ready formats include Cloud Optimized GeoTIFF (COG), Meta Raster Format (MRF) and Cloud Raster Format (CRF). These scientific data formats share common structures for storing multiple variables, with each variable being a multidimensional array.
GIS tools rely on information stored in data files to determine the correct method of visualization. Often, this relies on the Coordinate Systems (the values used to define a position within a spatial reference to represent location when capturing the data), as well as the Projections (how the values are located and displayed on a map).
At NASA, our scientific data work well in GIS tools if it follows standards such as the Hierarchical Data Format - Earth Observing System (HDF-EOS) and conventions such as Climate Forecast (CF). These help to ensure the data is formatted in a way for tools to read and write. However, not all of the complex, scientific data can be easily read or understood by libraries such as the Geospatial Data Abstraction Library (GDAL), which tells software what information to parse from data files and how to display them properly.
Using GIS tools, users can perform a multitude of spatial analyses to determine patterns or trends across space. GIS analysis is used to detect change, extract features, identify relationships, interpolate data, calculate statistics, determine viewsheds, and find optimal routes. GIS tools also help researchers employ machine learning and deep learning models to enhance our use of big data and make more accurate predictions.
GIS tools do more than make maps. Although cartography is the foundation for GIS technology, modern technology allows GIS practitioners to create and publish web mapping services, develop powerful user-intuitive applications, create interactive dashboards, and tell effective stories with data alongside narration and media. These methods allow content to be distributed to broad audiences in ways that are easy to digest, explore, utilize as well as integrate with content of their own. Expanding beyond traditional maps allows NASA to increase awareness and exposure within new communities and aids in the understanding and use of science data.
NASA data are freely and openly available to researchers and the public at large. Earthdata Search provides the means for discovery, filtering, visualization, and access across all of NASA’s Earth science data holdings. This includes more than 33,000 Earth observation data collections. It allows you to search by any topic, collection, or place name.
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NOTE: NASA data are available in a number of various scientific formats, however, not all data are GIS-ready, and not all files can be easily ingested into GIS systems without error or complications. Visit the Earthdata Forum to interact with NASA subject matter experts who can answer any questions that may arise. |
Interactively browse and download full-resolution, global satellite imagery from over 900 data products with Worldview. Showing the entire Earth as it looks "right now"—or at least as it has looked within the past few hours—Worldview supports time-critical application areas such as wildfire management, air quality measurements, and weather forecasting. Geostationary imagery layers are also now available. These are provided in ten minute increments for the last 30 days. These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world. Worldview is supported by NASA’s Global Imagery Browse Services (GIBS).
GIBS provides access global, full-resolution imagery from over 900 satellite imagery products via a variety of standards-based set of web services, such as Web Map Tile Services (WMTS), Tiled Web Map Service (TWMS), Web Map Services (WMS), and Keyhole Markup Language (KML).
NASA also utilizes Esri’s ArcGIS Online—a collaborative web GIS that allows users to use, create, and share data, layers, maps, applications, and analytic products. NASA’s publicly available content includes web services, dashboards, notebooks and story maps.
Selected authoritative content is also registered to Esri’s Living Atlas of the World, which now features imagery layers provided by EOSDIS.
There are a number of GIS tools from which data can be visualized, subsetted, and downloaded in different file formats that are GIS analysis-ready. There are also several Geospatial services (specifically, web map services [WMS], web feature services [WFS], and web coverage services [WCS]) providing access to a variety of GIS-ready datasets.
A GIS Pathfinder was developed to provide a guided walkthrough of NASA data in GIS tools. This resource provides links to the tools from which data can be visualized, subset, and downloaded in different file formats, as well as a brief tutorial on using the tool to access NASA geospatial web services.
NASA's Earthdata data discovery and data access webinars span the Earth science disciplines and are designed to help users learn about NASA EOSDIS data, services and tools and show users how to work with these resources.
Already on Your Way?If you are using NASA earth observation data, you may need some help navigating the complexities. NASA's EOSDIS has Tutorials/How-To Guides and Data Recipes to help you navigate the complexities of data processing and transformation to GIS use. If you are interested in receiving expert advice, check out the Earthdata Forum. Within the “Search by Tags” box, under “Services/Usage” select “GIS Tools” from the dropdown. Here, subject matter experts from several of NASA's Distributed Active Archive Centers (DAAC) can discuss general questions, research needs and data applications. Users can query how to access, view and interpret the data.
GeoTIFF, an Open Geospatial Consortium (OGC) Implementation Standard, is based on the TIFF format and is used as an interchange format for georeferenced raster imagery. While GeoTIFF has widespread use, it is not suitable for storing complex multi-dimensional data structures nor for storing vector data with many attributes or topology information.