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Geographic Information Systems Data Pathfinder

Visual representation of data layers or themes in a GIS.

Visual representation of data layers or themes in a GIS. Credit: Government Accountability Office, 2012

Geographic Information Systems (GIS) are used in nearly all fields that need to understand the spatial patterns and relationships between different types of data, from land-use planning to emergency response to resource management. GIS include 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.

Remote sensing data and imagery from Earth observations can be visualized within a GIS to provide more context about any area under study. The need is growing for NASA Earth science data to be in GIS-ready formats for easy integration and analysis in the primary tools employed by user communities. Numerous geospatial web services and tools are available through NASA's Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs) to access GIS-ready data. This data pathfinder provides direct links to those web services and tools for accessing and using NASA Earth science data.

If you don't see a dataset you need or need to locate other types of data in GIS-ready formats, contact us.

Working with Multidimensional Data in a GIS

Working with Multidimensional Data in a GIS

Overview

Multi-dimensional raster data which occurs over space (two dimensional), time, and/or height and depth (another dimension).

Multi-dimensional raster data which occurs over space (two dimensional), time, and/or height and depth (another dimension). Credit: NASA

GIS data contains spatial coordinates to represent where features are located. This is typically done using X and Y coordinates (or latitude and longitude). Multidimensional data can include additional dimensions such as depth and/or time. 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). These scientific data formats share common structures for storing multiple variables, with each variable being a multidimensional array.

In recent years, GIS software has increased support for scientific data formats in their platforms. In addition to correctly ingesting and reading these files, primary software platforms have developed new tools to aid in common workflows, management, analysis and distribution of multidimensional data.

In tools such as QGIS and ArcGIS, support for raster data is provided using a mosaic dataset. A mosaic dataset is a data model that acts as a shell to input a collection of multiple raster files, which include different file types, and is viewed as a single image. A multidimensional mosaic dataset stores information about the dimensions and variables as fields in the mosaic dataset footprint table. The underlying raster data does not have to be connecting or overlapping but can be isolated or intermittent datasets. In some GIS software platforms, a single mosaic dataset can then be used to query, process, analyze, and serve data.

Related Tutorials:

Working with Multidimensional Data in a GIS (ArcGIS Specific)

There are two ways to make a mosaic dataset that is multidimensional-aware. One option is to create a mosaic dataset by adding rasters using HDF, netCDF, or GRIB raster file types which will import dimensional data and variable information into the mosaic dataset. The other option is to build a multidimensional information table in order to generate required multidimensional fields, metadata, and structure to make the dataset interoperable. In order to do this you will need to have a field in your mosaic dataset footprint table that identifies the variable in each raster and there needs to be either a time or height field to define one or more dimensions.

If you need assistance in working with multidimensional data in GIS-ready formats, contact us.

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Using NASA Data in a GIS

Using NASA Data in a GIS

Adding a Raster Layer | Adding a Vector Layer | Adding a Web Map Service

There are several GIS programs available to users. Because QGIS is a free open source program, all of the examples below are screenshots from it, yet other programs have very similar options for adding layers.

Adding a Raster Layer to a GIS

  1. Under Layer/Add Layer, select Add Raster Layer.
    Adding a raster layer in QGIS
  2. Select the file and click add.
    You may need to modify the projection or symbology, both of which are in the layer properties. Layer properties can be accessed by double-clicking on the layer or by selecting Layer/Layer properties. "Layer Properties" is the window title within QGIS and "Properties" in ArcGIS Pro.
    Modifying symbology on raster layer in QGIS
  3. At this point, you can visualize your data.
    Raster layer visualized in QGIS

Adding a Vector Layer to a GIS

  1. Under Layer/Add Layer, select Add Vector Layer.
    Adding a vector layer in QGIS
  2. Select the file and click add. Note: you can add the entire zip file and then select specific layers to add.
    Selecting vector layers to add in QGIS
  3. At this point, you can visualize your data.
    Visualizing vector data in QGIS

Adding a Web Service to a GIS

Some of the DAACs provide geospatial services, specifically web map services (WMS), web coverage services (WCS), and web feature services (WFS), providing access to a variety of GIS-ready datasets. Many of the URLs needed for data access are specific to the DAAC, and in some cases specific to the dataset. See Use Cases for Web Services to see examples for each service.

QGIS:

  1. Under Layer/Add Layer, select Add WMS/WMTS Layer.
  2. Click "New" to add a new end point using the specific URL then click "Connect" to access the services available.

ArcGIS Pro:

  1. Insert > Connections > New WMS Server to then add a new end point using the specific URL.
  2. Click "OK" to connect and access the services available.

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Use Cases for Web Services

Use Cases for Web Services

Web Feature Service | Web Coverage Service | Web Map Service

Web Feature Service from NASA's Socioeconomic Data and Applications Center (SEDAC)

Storm surge from hurricanes pose threats to human health and wildlife. In areas where Superfund sites may be inundated, the concern that toxins will be dispersed is great. However, the level of concern varies widely depending on the specific contaminants and their concentrations. The Environmental Protection Agency (EPA), therefore, must assess where superfunds exist and the vulnerability of those sites, as well as risk to surrounding communities, when a large storm surge is expected. Use case adapted from CNBC news article and EPA Hurricane Harvey Report.

Concerned about the approaching hurricane expected to hit the panhandle of Florida, you want to look at Superfund sites in the area and the population density surrounding those areas to assess potential effects. Through SEDAC's WFS, you can directly access the data within a GIS.

To add a WFS:

  1. Proceed to Layer and "Add a WFS Layer."
  2. Provide a name and insert this URL: https://sedac.ciesin.columbia.edu/geoserver/ows?version=1.1.0
    Adding a WFS in QGIS
  3. Click OK and then Connect.
  4. Features can now be added to the map viewer.

In this example, the following SEDAC layers were added:

  • Agency for Toxic Substances and Disease Registry (ATSDR) Hazardous Waste Sites
  • Gridded Population of the World, Version 4, Population Density

SEDAC superfund sites mapped with population density

Web Coverage Service from NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC)

According to the Global Annual Temperature Rankings Outlook from NOAA, this year (2020) is on track to be one of the warmest on record.

Concerned about a changing climate, you want to access climatological data, and generate an anomaly map for the month of January, 2020. Through ORNL DAAC's WCS, you can directly access, within a GIS, Daymet data (a collection of gridded estimates of daily weather parameters generated by interpolation and extrapolation from daily meteorological observations) to run raster-based functions to generate a 28-year time averaged map and then an anomaly map for 2020.

To add a WCS:

  1. Proceed to Layer and "Add a WCS Layer."
  2. Provide a name and insert this URL: https://webmap.ornl.gov/ogcbroker/wcs?
    Adding a WCS in QGIS
  3. Click OK and then Connect.
  4. Coverages can now be added to the map viewer.

In this example, the following ORNL DAAC layers were added:

  • Daymet: Monthly Climate Summaries on a 1-km Grid for North America (January months from 1990-2018)

ORNL Daymet data visualized in QGIS

Web Coverage Service – SEDAC

Approximately half the nation's original wetland habitats have been lost over the past 200 years. In part, this has been a result of natural evolutionary processes, but human activities, such as dredging wetlands for canals or draining and filling for agriculture, grazing, or development, share a large part of the responsibility for marsh habitat alteration and destruction. Louisiana's wetlands today represent about 40 percent of the wetlands of the continental United States, but about 80 percent of the losses (from Louisiana Coastal Wetlands: A Resource at Risk).

Concerned about a changing climate, you want to conduct an analysis of coastal wetlands loss from sea level rise using estimates of wetland losses as a basis for identifying potential adaptation measures. Through SEDAC's WCS, you can directly access, within a GIS, elevation data, population density, and an urban extents grid.

To add a WCS:

  1. Proceed to Layer and "Add a WCS Layer."
  2. Provide a name and insert this URL: https://sedac.ciesin.columbia.edu/geoserver/wcs?
    Adding a web coverage service (WCS) in QGIS
  3. Click OK and then Connect.
  4. Coverages can now be added to the map viewer.

In this example, the following SEDAC layers were added:

  • Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Population Density Grid for the year 2000
  • GRUMPv1 Urban Extents
  • Global Shuttle Radar Topography Mission (SRTM) Elevation above Sea-level at 1 km resolution

SEDAC population density mapped with urban extent and elevation within QGIS

Web Map Service – Global Imagery Browse Services (GIBS)

In a recent research article from the journal Global Ecology and Biogeography, titled The Global Fire-Productivity Relationship, it is noted that on a global scale, fire activity changes along the productivity/aridity gradient. This relation should be driven by differing relative roles of the main fire drivers (weather and fuel) along the productivity gradient. In moist regions around the globe, fire activity is believed to be driven by drought frequency, whereas in dry regions, fire is thought to be limited by the amount of fuel available.

Concerned about a changing climate, you want to test these ideas by comparing global fire activity. Within a GIS using GIBS's WMS, you can directly access MODIS land surface reflectance (bands 7-2-1, useful for distinguishing burn scars from naturally low vegetation or bare soil), fire and thermal anomalies, and normalized difference vegetation index, among many other relevant layers.

To add a WMS:

  1. Proceed to Layer and "Add a WMS Layer."
  2. Provide a name and insert this URL: https://gibs.earthdata.nasa.gov/wms/epsg4326/best/wms.cgi
    Adding a web map service (WMS) in QGIS
  3. Click OK and then Connect.
  4. Maps can now be added to the map viewer.

In this example, the following GIBS layers were added:

  • Thermal Anomalies and Fires (All (day/night) from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra platform)
  • 8-day Vegetation Index from Terra's MODIS instrument
  • Land Surface Reflectance (bands 7, 2, 1) from Terra's MODIS instrument

GIBS WMS layers of fire/thermal anomalies, NDVI and land surface reflectance mapped in a GIS

Some of the DAACs provide geospatial services, specifically WMS and WCS, providing access to a variety of GIS-ready datasets. They can be found on the geospatial services page.

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Tools and Platforms to Discover NASA Data

Tools and Platforms to Discover NASA Data

NASA ArcGIS Online (AGOL)

NASA ArcGIS Online data portal provides access to web maps and story maps focused on NASA data.NASA ArcGIS Online (AGOL) provides the capability to create and share NASA Earth science data with the public and interagency partners by bringing data to end users in an easy to use, cloud-based web platform.

Worldview

NASA's Worldview visualization application provides the capability to interactively browse over 900 global, full-resolution satellite imagery layers and then download the underlying data. Many of the available imagery layers are updated within three hours of observation, essentially showing the entire Earth as it looks "right now." This supports time-critical application areas such as wildfire management, air quality measurements, and flood monitoring. Imagery in Worldview is provided by GIBS. Worldview now includes nine geostationary imagery layers from Geostationary Operational Environmental Satellite (GOES)-East, GOES-West and Himawari-8 available at ten-minute increments for the last 30 days. These layers include Red Visible, which can be used for analyzing daytime clouds, fog, insolation, and winds; Clean Infrared, which provides cloud top temperature and information about precipitation; and Air Mass RGB, which enables the visualization of the differentiation between air mass types (e.g., dry air, moist air, etc.). These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world.

Worldview data visualization of the nighttime lights in Puerto Rico pre- and post- Hurricane Maria, which made landfall on September 20, 2017. The post-hurricane image on the left shows widespread outages around San Juan, including key hospital and transportation infrastructure.​

Worldview data visualization of the nighttime lights in Puerto Rico pre- and post- Hurricane Maria, which made landfall on September 20, 2017. The post-hurricane image on the left shows widespread outages around San Juan, including key hospital and transportation infrastructure.

Earthdata Search is a tool for data discovery of Earth Observation data collections from NASA's EOSDIS, as well as U.S. and international agencies across the Earth science disciplines. Users (including those without specific knowledge of the data) can search for and read about data collections, search for data files by date and spatial area, preview browse images, and download or submit requests for data files, with customization for select data collections.

In the project area, for some datasets, you can customize your granule. You can reformat the data and output as HDF, NetCDF, ASCII, KML, or a GeoTIFF. You can also choose from a variety of projection options. Lastly, you can subset the data, obtaining only the bands that are needed.

DAAC Tools

Many of the DAACs also provide Interactive Tools for GIS Data from which data can be visualized, subsetted, and downloaded in different file formats that are GIS analysis-ready.

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Other Resources

Other Resources

Atmospheric Science Data Center (ASDC) AGOL Data Portal

ASDC AGOL Data Portal features web maps of data from:

  • Measurement of Pollution in the Troposphere (MOPITT) instrument, designed to enhance our knowledge of the lower atmosphere and to observe how it interacts with the land and ocean biospheres.
  • Multi-angle Imaging Spectroradiometer (MISR), designed to show the change in reflection at different view angles, which affords the means to distinguish different types of atmospheric particles (aerosols), cloud forms, and land surface covers.
  • Climatology of solar radiation from 1983-2005.

DAAC Story Maps

Dizzy the Disdrometer: An interactive story map from NASA's Global Hydrology Resource Center DAAC (GHRC DAAC) to learn about the disdrometer instrument, the Global Precipitation Monitoring (GPM) Ground Validation (GV) project, and where to find the data used during the field campaigns.

Mapping Deforestation: A new "Data in Action" ArcGIS Story Map, at NASA's Land Processes DAAC (LP DAAC), maps deforestation in Cambodia using NASA MODIS Land Cover and Vegetation Continuous Fields datasets to highlight land cover changes.

Screenshot of an image captured by Sentinel-1B of Hurricane Dorian off the north coasts of Puerto Rico and the Dominican Republic, taken on August 29, 2019. The image was processed using GAMMA software and contains modified Copernicus Sentinel data 2019, processed by ESA.

Screenshot of an image captured by Sentinel-1B of Hurricane Dorian off the north coasts of Puerto Rico and the Dominican Republic, taken on August 29, 2019. The image was processed using GAMMA software and contains modified Copernicus Sentinel data 2019, processed by ESA. Credit: Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC) 

Hurricane Dorian (2019) in Sentinel-1 SAR Imagery: NASA's Alaska Satellite Facility DAAC (ASF DAAC) has created a timeline showing images captured by the Sentinel-1 satellites of Hurricane Dorian as it moved through the Caribbean and up the east coast of the U.S.

Changes in the Observed Tropospheric NO2 Column Density shows the changes in the observed Tropospheric NO2 column density over China before and after lockdown due to COVID-19.

Ice-Albedo Feedback in the Arctic provides information on sea ice extent in the Arctic and the drivers of change. The story map also highlights the impact of increasing absorbed solar radiation and its impact within the ice-albedo feedback loop.

Introduction to MAIA and TEMPO introduces us to these two new missions, the Multi-Angle Imager for Aerosols (MAIA) and Tropospheric Emissions Monitoring Pollution (TEMPO), launching in 2022, that will study air quality and its impact on human health at unprecedented temporal and spatial scales.

Applied Sciences Disaster Portal

The Disasters Applications area promotes the use of Earth observations to improve prediction of, preparation for, response to, and recovery from natural and technological disasters. Disaster applications and applied research on natural hazards support emergency preparedness leaders in developing mitigation approaches, such as early warning systems, and providing information and maps to disaster response and recovery teams.

My NASA Data

My NASA Data Earth System Data Explorer helps learners visualize complex Earth System datasets over space and time.My NASA Data provides a means of visualizing global datasets through its Earth System Data Explorer. My NASA Data provides global monthly visualizations of parameters, such as aerosol optical depth, surface air temperature, surface air temperature anomalies, wind speed, biome classification, chlorophyll, leaf area index, normalized difference vegetation index, concentration of CO2 in the troposphere, total column ozone, and air column concentration of CO, SO2, and NO2.

By choosing a dataset, the web-based tool provides information about the source of the data and the units, as well as a visualization of the monthly data (note that there are a few daily datasets). Within the Earth System Data Explorer, you can compare multiple datasets, create line plots, create animations, and perform computational requests (like computing the average values over time).

Once you have the dataset of interest, it can be exported to a variety of desktop applications, including Ferrett, GrADS, and MatLab. The data also can be saved as an ASCII, CSV, NetCDF, and arcGRID file. arcGRID and NetCDF files can be opened as a raster layer in GIS programs. CSV files can be opened as a "delimited text" file. To open properly, you will need to specify that it is comma-separated, the number of header lines to discard, and the appropriate fields for latitude and longitude.

My NASA Data also has a series of story maps designed for educational use:

NASA Center for Climate Simulation

NASA Center for Climate Simulation (NCCS) Spatial Analytics Platform supports NASA scientists and partners by providing a centralized and highly available geospatial platform that:

  • is tightly integrated with NCCS’s high performance computing capabilities;
  • accelerates collaborative analytics through the use of advanced visualization and custom applications; and
  • can process vast amounts of data without significant performance degradation. NCCS has various ArcGIS web apps as well as story maps.

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Published July 10, 2020

Page Last Updated: Jul 13, 2020 at 11:30 AM EDT