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Find Environmental Impacts Data

Bridge traffic disappeared during the quarantine.

Bridge traffic disappeared during the quarantine. Credit: Planet Labs Inc.

To counter the onset and rapid spread of COVID-19, quarantine and social distancing measures were implemented around the world. Air traffic nearly ceased; non-essential businesses closed; the number of people on the road was much lower than normal. Due to this drastic alteration in human behavior, changes in the environment occurred.

NASA and other federal agencies, as well as European organizations, have released a number of funding opportunities and challenges to determine which observed environmental changes are related to these alterations in human behavior. NASA has numerous Earth science datasets that are used to monitor environmental impacts such as air quality, water quality, biological and land cover changes, and more. Note: this is not an exhaustive list. This list will also be modified as new information becomes available.

Air Quality

Air Quality

Map showing nitrogen dioxide density data for China in early 2020.

TROPOMI data shows nitrogen dioxide density in China in early 2020. Image from NASA's Earth Observatory.

See our Health and Air Quality Data Pathfinder for more information on aerosol optical depth, trace gas data, and pollutant transport data.

Aerosol Optical Depth/Thickness | Nitrogen Dioxide | Carbon Monoxide | Ozone

Aerosol Optical Depth/Thickness

Aerosol Optical Depth (AOD) is a column-integrated value of aerosols in the atmosphere obtained by measuring the scattering and absorption of solar energy from the top of the atmosphere to the surface. The non-aerosol signal of surface reflectance needs to be separated from the aerosol signal to accurately obtain an aerosol optical depth. This is challenging because the satellite instrument cannot penetrate cloud cover and highly reflective surfaces, such as ice or snow, producing misrepresentations of the data. To address these challenges, scientists have developed algorithms for the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data to help with these effects, dark target and deep blue. For more information on these algorithms see: Dark Target Algorithm and Deep Blue Algorithm. In the latest dataset collection, these two have been merged, using the highest quality for each. While it does provide the easiest use of global coverage, there are some risks (see the websites above for more information).

The joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) instrument collects AOD data at a much finer spatial resolution. VIIRS uses the Deep Blue (DB) algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading for daytime cloud-free, snow-free scenes. With all of the VIIRS data, downloading a file will provide the data with just the land algorithm, just the ocean algorithm, and the merged algorithm. As with all remote sensing data, make sure you are choosing the best product for your area.

Research-quality data products can be accessed via Earthdata Search. Data are in HDF or NetCDF format and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through the Giovanni online interactive tool. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

  • OMI AOD in Giovanni
    The Ozone Monitoring Instrument (OMI) aboard the Aura satellite has a coarser spatial resolution than MODIS and VIIRS but provides data at individual wavelengths from the ultraviolet (UV) to the visible. Within Giovanni, you can plot daily data at these individual wavelengths. This is important because pollutants have different spectral signatures; for example, a wavelength range around 400 nm can be used to detect elevated layers of absorbing aerosols such as biomass burning and desert dust plumes. The two AOD products provided through Giovanni use two different algorithms—OMI Multi-wavelength (OMAERO) and OMI UV (OMAERUV). OMI Multi-wavelength (OMAERO) is based on the multi-wavelength algorithm and uses up to 20 wavelength bands between 331 nm and 500 nm. This algorithm uses reflectance for a wide variety of microphysical aerosol models representative of desert dust, biomass burning, volcanic, and weakly absorbing aerosol types. OMI UV (OMAERUV) uses the near-UV algorithm, which is capable of retrieving aerosol properties over a wider variety of land surfaces than is possible using measurements only in the visible or near-infrared, because the reflectance of all terrestrial surfaces (not covered with snow) is small in the UV.
  • MODIS AOD in Giovanni
    Provides data products with both algorithms as well as the combined algorithm at daily and monthly intervals.

Near real-time (NRT) data can be accessed via Worldview:

  • MODIS Aqua/Terra Combined Algorithm AOD
    The merged Dark Target/Deep Blue Aerosol Optical Depth layer provides a more global, synoptic view of aerosol optical depth over land and ocean. It is available from 2000 to present.
  • VIIRS Level 2 Deep Blue Aerosol Product
    The product uses the Deep Blue algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading. The product is designed to facilitate continuity in the aerosol record. Deep Blue uses measurements from multiple Earth-observing satellites to determine the concentration of atmospheric aerosols along with the properties of these aerosols.
  • OMI AOD Multi-wavelength and UV
    The multi-wavelength layer and the UV absorbing layer displays the degree to which airborne particles (aerosols) prevent the transmission of light through the process of absorption (attenuation), and the UV extinction layer indicates the level at which particles in the air (aerosols) prevent light (extinction of light) from traveling through the atmosphere. Toggling between these three can provide more distinction on the types of aerosols present.

Nitrogen Dioxide

Nitrogen Dioxide (NO2) is a pollutant, the primary sources being the burning of fossil fuels, automobiles, and industry.

Once in the air, it can aggravate respiratory conditions in humans, especially those with asthma, leading to an increase of symptoms, hospital admissions, and emergency visits. Long-term exposure can lead to the development of asthma and potentially increase susceptibility to respiratory infections. NO2 reacts with other chemicals in the atmosphere, forming particulate matter and ozone, producing haze and even acid rain, and contributing to nitrogen pollution in coastal waters. NASA Goddard Space Flight Center's Air Quality site provides more information on NO2, as well as trend maps and pre-made images of NO2 over cities and power plants.

Research-quality data products can be accessed via Earthdata Search:

  • OMI NO2 data from Earthdata Search
    OMI provides daily gridded and non-gridded products at 13x24 km resolution; data are in HDF5 format and can be opened using Panoply. A tutorial on using OMI NO2 data is available as a PDF and a webinar on Analyzing NO2 data within Java and Excel is available from NASA's Earthdata YouTube channel.
  • TROPOspheric Monitoring Instrument tropospheric vertical column of nitrogen dioxide data opened in NASA tool, Panoply

    TROPOspheric Monitoring Instrument tropospheric vertical column of nitrogen dioxide data opened in NASA tool, Panoply. The red circle indicates a change needed in the scaling factor, due to the very small numbers.

    TROPOMI NO2 from Earthdata Search
    The TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P, is a European Space Agency (ESA) Mission, The ESA TROPOMI NO2 provides additional information on this Level 2 data product. It is important to note that, because of the very small numbers in tropospheric vertical column of NO2, you will need to change the scaling factor in Panoply (see image from June 2018 to right). Data are NetCDF and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

NRT data can be accessed via Worldview:

NASA also has a global nitrogen dioxide monitoring site that provides imagery of daily NO2 from OMI.

Carbon Monoxide

Carbon Monoxide (CO) is a harmful pollutant that is released when something is burned, such as in the combustion of fossil fuels, the primary source, or biomass burning. Outdoor levels are rarely high enough to cause issues; when they do reach dangerous levels, however, they can be of concern to people with certain types of heart disease.

Research-quality data products can be accessed via Earthdata Search:

  • AIRS CO data from Earthdata Search
    Atmospheric Infrared Sounder (AIRS) measures abundances of trace components in the atmosphere including carbon monoxide. Data are available daily (AIRS3STD), over 8 days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of CO in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere). Data are in HDF format, and can be opened using Panoply.
  • MOPITT CO data from Earthdata Search
    Measurements of Pollution in the Troposphere (MOPITT) measures the amount of CO present in the total vertical column of the lower atmosphere (troposphere) and is measured in mole per square centimeter (mol/cm2). Data are available daily or monthly. Data are acquired using the thermal and near-infrared channels. Data are in HDF5 format, and can be opened using Panoply.
  • TROPOMI CO data from Earthdata Search
    ESA TROPOMI CO provides additional information on this Level 2 data product. As with the nitrogen oxide data above, you will need to adjust the scaling factor. Data are in NetCDF format and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Near real-time (NRT) data can be accessed via Worldview:

  • AIRS CO data in Worldview
    AIRS Level 2 data are nominally 45 km/pixel at the equator but the data in Worldview has been resampled into a 32 km/pixel visualization. The data are in units of parts per billion by volume at the 500 hPa pressure level, approximately 5500 meters (18,000 feet) above sea level.
  • MOPITT CO data in Worldview

Ozone

Ozone (O3) can be either good or bad, depending on where it is found in the atmosphere. In the stratosphere, O3 protects humans, plants, and animals from harmful UV radiation. In the troposphere or closer to the ground level, however, O3 serves as a potent greenhouse gas and can aggravate existing health problems in humans, especially those with respiratory illnesses. O3 is not emitted directly into the atmosphere but instead forms from the chemical reaction between nitrogen oxides and volatile organic compounds, emitted primarily from cars, power plants, and other industrial facilities; reactions take place in the presence of sunlight. Because of the need for sunlight, unhealthy levels are most often reached on very sunny days and in urban environments.

Research-quality data products can be accessed via Earthdata Search. There are several options and determining which to use can be a challenge. The table in About the Data may be of use as it provides information on spatial and temporal resolution.

  • OMI O3 data from Earthdata Search
    OMI provides daily total column data; data are in HDF5 format and can be opened using Panoply.
  • AIRS O3 data from Earthdata Search
    AIRS measures abundances of trace components in the atmosphere including ozone. Data are available daily (AIRS3STD), over 8 days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of O3 in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere). Data are in HDF format and can be opened using Panoply.
  • TROPOMI O3 data from Earthdata Search
    ESA TROPOMI O3 provides additional information on this level 2 data product. Data are in NetCDF format and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

NRT data can be accessed via Worldview:

Trends on a national and regional level are available through the Environmental Protection Agency’s Air Quality Trends.

NASA’s Goddard Earth Science Data Information Services Center (GES DISC) has developed an Air Quality and Climate Anomaly Viewer, which contains information on population, AOD, NO2, and O3, as well as temperature and precipitation anomalies. They have also put out a story map on changes in the observed tropospheric NO2 column density.

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Nighttime Lights

Nighttime Lights
Satellite image shows nighttime lights near Wuhan, China on February 4. Highways appear darker than in January.
February 4, 2020
Satellite image shows nighttime lights near Wuhan, China on January 19, 2020.
January 19, 2020

Observing the Earth at night provides some insight into human behaviors, from the observation of various religious or cultural events to illegal fishing to a decrease in city traffic. The Suomi NPP VIIRS nighttime imagery layer shows the Earth’s surface and atmosphere using a sensor designed to capture low-light emission sources, under varying illumination conditions, which can aid in our understanding of how nighttime lights change due to changes in human behaviors.

Research-quality data products can be accessed via Earthdata Search, and NRT data can be accessed via Worldview:

NASA has also developed the Black Marble, a daily calibrated, corrected, and validated product suite, so nightlight data can be used effectively for scientific observations. Black Marble's standard science processing removes cloud-contaminated pixels and corrects for atmospheric, terrain, vegetation, snow, lunar, and stray light effects on the VIIRS Day/Night Band radiances. Black Marble data can be accessed at NASA's Level-1 and Atmosphere Archive and Distribution System Distributed Active Archive Center (LAADS DAAC). Black Marble imagery in Worldview is an image composite that was assembled from clear, cloud free images for 2012 and 2016.

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Water Quality

Water Quality

Chesapeake Bay and surroundings, mosaic of 5 Landsat images taken in October and November 2014.

Chesapeake Bay and surroundings, mosaic of 5 Landsat images taken in October and November 2014. Credit: USGS.

The Water Quality Data Pathfinder has additional information on the use and processing of ocean color data, as well as the integration of ground-based data with satellite or airborne data.

Ocean color is measured based on the amount of absorption by particles (e.g., phytoplankton, sediments, colored dissolved organic matter [CDOM]) and in turn, the amount of water-leaving radiance. Having a quantitative measure of these parameters is useful in understanding how water bodies, such as the ocean, are evolving, as well as determining the quality of the water for consumption by living organisms. The primary means of measuring ocean color from space is through Landsat, the Terra and Aqua satellites, Suomi NPP, and ESA’s suite of Sentinel missions. Each of these satellites has sensors acquiring data at different spatial, temporal, spectral, and radiometric resolutions (for detailed information on these, read What is Remote Sensing?).

In addition to ocean color, sea surface temperature (SST) is a valuable parameter as warmer waters can contribute to the growth of algal blooms. However, in the ocean cold upwelling waters usually bring nutrients from the seafloor fueling marine phytoplankton blooms. In the MODIS and VIIRS data, there is also an inherent optical properties (IOP) file, which provides an estimate of reflectance by CDOM. Specifically, the adg_443_giop is the absorption coefficient of non-algal material plus CDOM. For more information on the algorithm used to generate this product and others, view the Ocean Biology DAAC (OB.DAAC) algorithm descriptions.

Research-quality data products can be accessed via Earthdata Search or through NASA partner websites:

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

  • Level 3 data products from OB.DAAC
    Data products include chlorophyll-a concentration, SST, reflectance, and other related measurements from MODIS and VIIRS at 4 km and 9 km resolution. These data products are provided in five temporal resolutions: daily, 8-day, monthly, seasonally, and annually.
  • Aqua MODIS Chlorophyll-a Concentration data from Giovanni
    Data products from MODIS on the Aqua satellite at 4 km resolution provided at both 8-day and monthly temporal resolutions.
  • Aqua MODIS SST data from Giovanni
    Data products from MODIS on the Aqua satellite at 4 km resolution provided at both 8-day and monthly temporal resolutions.

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Biological Diversity

Biological Diversity

The Biological Diversity and Ecological Forecasting Data Pathfinder has additional information on vegetation characteristics, species distribution modeling, and spectroscopy.

Surface Reflectance

ASTER deforestation

Extensive deforestation and fragmentation are visible in this satellite image, acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on August 24, 2000, of the state of Rondonia, Brazil, along the Jiparaná River. Tropical rainforest appears bright red, while pale red and brown areas represent cleared land. Black and gray areas have probably been recently burned. The Jiparaná River appears blue. (Image courtesy of NASA and the U.S./Japan ASTER Science Team)

Surface reflectance is useful for monitoring changes within the landscape. Moderate resolution instruments that are primarily used for this measurement include MODIS and VIIRS. MODIS reflectance products are available at 250 m, 500 m, 1000 m, and 5600 m spatial resolution. VIIRS reflectance products are available at 500 m and 1000 m spatial resolution. MODIS data are acquired every one to two days, whereas the wider swath width of VIIRS allows for daily global coverage.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), another high-resolution instrument, acquires visible and near-infrared (VNIR) reflectance data at 15 m resolution and short-wave infrared (SWIR) reflectance data at 30 m resolution (through 2009). Note that ASTER is a tasked sensor, meaning that it only acquires data when it is directed to do so over specific targets, making its temporal resolution variable depending on your target region of interest. ASTER Surface Reflectance products are processed on-demand and so must be requested with additional parameters. Note that there is a limit to 2000 granules per order.

Research-quality surface reflectance data products can be accessed directly via Earthdata Search; MODIS, VIIRS, and ASTER are available as HDF files, but are also customizable to GeoTIFF:

NASA's Land Processes DAAC (LP DAAC) also provides a tool called the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS). AppEEARS offers a simple and efficient way to access, transform, and visualize geospatial data from a variety of federal data archives. MODIS and VIIRS surface reflectance data are available in AppEEARS, as well as the USGS Landsat Analysis Ready Data (ARD) surface reflectance product.

NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC) also provides tools for on-demand subsetting of MODIS and VIIRS land data. In particular, the Subsets API allows users to retrieve custom subsets, analytics, and visualization of MODIS and VIIRS data products.

For higher resolution, the Landsat 7 Enhanced Thematic Mapper (ETM+) sensor and the Landsat 8 Operational Land Imager (OLI) instrument acquire data at 30 m spatial resolution in VNIR every 16 days (or less as you move away from the equator). Landsat 8 was developed as a collaboration between NASA and the USGS. The USGS now leads satellite operations and data archiving at the Earth Resources Observation and Science (EROS) center.

Landsat data can be discovered using Earthdata Search, however, you will need a USGS Earth Explorer login to download the data.

Data can be visualized in Worldview:

  • MODIS True Color in Worldview
    Note that Worldview does have a corrected reflectance product but it is not a standard, research-quality product. The purpose of this algorithm is to provide natural-looking images by removing gross atmospheric effects, such as Rayleigh scattering, from MODIS visible bands 1-7.

Vegetation Greenness

Screenshot of Normalized Difference Vegatation Index of King Fire area of burn.

False-color image of Normalized Difference Vegetation Index (NDVI) data of King Fire area, September 2013 (left) and Nov 2014. (ORNL DAAC)

Vegetation indices measure the amount of green vegetation over a given area and can be used to assess vegetation health. A commonly-used vegetation index is the Normalized Difference Vegetation Index (NDVI), which uses the difference between near-infrared (NIR) and red reflectance divided by their sum. NDVI values range from -1 to 1. Low values of NDVI generally correspond to barren areas of rock, sand, exposed soils, or snow, while higher NDVI values indicate greener vegetation, including forests, croplands, and wetlands. The enhanced vegetation index (EVI) is another widely used vegetation index that minimizes canopy-soil variations and improves sensitivity over dense vegetation conditions.

Vegetation products from the MODIS instrument and the VIIRS instrument satellite can be accessed in various ways:

Research-quality surface reflectance data products can be accessed directly via Earthdata Search or LP DAAC's Data Pool; datasets are available in HDF format but are, in some cases, customizable to GeoTIFF.

LP DAAC's  AppEEARS offers a simple and effective way to extract, transform, visualize, and download MODIS and VIIRS vegetation-related data products. AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest, and output data can be downloaded in csv (point), GeoTIFF (area) or NetCDF-4 (area) format. ORNL DAAC subsetting tools provide a means to simply and efficiently access and visualize MODIS and VIIRS vegetation-related data products as well.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal coverages, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Data can be visualized in Worldview:

  • MODIS NDVI in Worldview
    This dataset has a spatial resolution of 250 m and a temporal resolution of eight days. 16-day and monthly data are also available within Worldview.
  • MODIS EVI in Worldview
    This dataset is monthly at 1 km spatial resolution. Rolling 8-day and 16-day data are also available within Worldview.

Land Surface Temperature

Research-quality land surface temperature data products can be accessed directly from Earthdata Search. MODIS and ASTER data are available as HDF. VIIRS and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) data are available as HDF5:

To quickly extract a subset of ECOSTRESS, MODIS, or VIIRS data for your region of interest, use LP DAAC's AppEEARS tool or the ORNL DAAC subsetting tools.

Landsat data can be discovered using Earthdata Search, however, you will need a USGS Earth Explorer login to download the data.

Data can be visualized in Worldview:

Evapotranspiration

The combination of evaporation from the land surface and transpiration from plants is evapotranspiration, abbreviated ET. This parameter approximates the consumptive use of a landscape’s plants.

The combination of evaporation from the land surface and transpiration from plants is evapotranspiration, abbreviated ET. This parameter approximates the consumptive use of a landscape’s plants. Image Credit: U.S. Geological Survey

Measurements of evapotranspiration (ET), the sum of evaporation from land surface and transpiration in vegetation, are extremely useful in monitoring and assessing water availability, drought conditions, and crop production. One of the challenges in acquiring ET data is that ET can’t be measured directly with satellite instruments as it is dependent on many other variables, such as land surface temperature, air temperature, and solar radiation. However, there are Level 4 data products (see data processing levels for more information) that incorporate daily meteorological reanalysis data with remote sensing data to arrive at estimations of ET. MODIS has such a product. Meteorological reanalysis data are assimilated products from historical atmospheric data from an extended period of time.

Research-quality MODIS Level 4 ET products are available in yearly and 8-day temporal resolutions with 500 m pixel size.

NASA's Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) aboard the International Space Station (ISS) measures the temperature of plants to better understand how they respond to the stress of insufficient water availability. ECOSTRESS was launched in June 2018 and uses a multispectral thermal infrared radiometer to measure radiance, which is converted into surface temperature and emissivity. ECOSTRESS produces Level 3 ET data products according to the Priestly-Taylor Jet Propulsion Laboratory (PT-JPL) algorithm, using the surface temperature and emissivity as inputs (among other ancillary data inputs from other sources).

Research-quality ECOSTRESS ET data products can be accessed directly via Earthdata Search or LP DAAC's Data Pool; datasets are available as HDF files but are, in some cases, customizable to GeoTIFF.

LP DAAC's AppEEARS offers a simple and effective way to extract, transform, visualize, and download MODIS and ECOSTRESS ET data products. AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest, and output data can be downloaded in csv (point), GeoTIFF (area), or NetCDF-4 (area) format.

ORNL DAAC's subsetting tools also provide a means to simply and efficiently access and visualize MODIS ET data products.

The Land Data Assimilation System (LDAS) provides model-based ET data of which there is a global collection (GLDAS) and a North American collection (NLDAS). LDAS uses measurements of precipitation, soil texture, topography, and leaf area index to model soil moisture and evapotranspiration. When calculating ET, there are biases around seasonality or local-specific effects but developers try to account for those and calibrate accordingly; estimates of ET are provided every day and integrated to get monthly, seasonal, or annual information within a 2-12% error.

GLDAS data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions and multiple temporal coverages, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

  • GLDAS ET in Giovanni
    Data are available with a temporal resolution of 3-hourly, daily, and monthly.

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Socioeconomic Data

Socioeconomic Data

A simple-to-use mapping tool at NASA’s Socioeconomic Data and Applications Center (SEDAC) shows demographic data along with regularly updated information about reported global cases of the disease caused by COVID-19.

SEDAC COVID viewer data-verified=

SEDAC also has datasets related to population density and size, urban extent, land use and land cover, poverty.

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Tools for Data Access and Visualization

Tools for Data Access and Visualization

Earthdata Search | Panoply | Giovanni | Worldview | AppEEARS | MODIS/VIIRS Subsetting Tools Suite | Spatial Data Access Tool (SDAT)| SeaDAS

Earthdata Search is a tool for data discovery of Earth Observation data collections from NASA’s Earth Observing System Data and Information System (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.

Screenshot of the Search Earthdata site.

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.

Earthdata Search customization tools diagram.

Panoply

HDF and NetCDF files can be viewed in Panoply, a cross-platform application that plots geo-referenced and other arrays. Panoply offers additional functionality, such as slicing and plotting arrays, combining arrays, and exporting plots and animations.

Giovanni

Giovanni is an online environment for the display and analysis of geophysical parameters. There are many options for analysis. The following are the more popular ones.

  • Time-averaged maps are a simple way to observe the variability of data values over a region of interest.
  • Map animations are a means to observe spatial patterns and detect unusual events over time.
  • Area-averaged time series are used to display the value of a data variable that has been averaged from all the data values acquired for a selected region for each time step.
  • Histogram plots are used to display the distribution of values of a data variable in a selected region and time interval.

For more detailed tutorials:

  • Giovanni How-To’s on NASA's GES DISC YouTube channel.
  • Data recipe for downloading a Giovanni map as NetCDF and converting its data to quantifiable map data in the form of latitude-longitude-data value ASCII text.

Worldview

NASA’s EOSDIS 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 NASA’s Global Imagery Browse Services (GIBS). Worldview now includes nine geostationary imagery layers from 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. Post-hurricane image 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.

AppEEARS

AppEEARS, from LP DAAC, 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.

Performing Area Extractions

After choosing to request an area extraction, you will be taken to the Extract Area Sample page where you will specify a series of parameters that are used to extract data for your area(s) of interest.

Spatial Subsetting

Define your region of interest in one of these three ways:

  • Upload a vector polygon file in shapefile format (you can upload a single file with multiple features or multipart single features). The .shp, .shx, .dbf, or .prj files must be zipped into a file folder to upload.
  • Upload a vector polygon file in GeoJSON format (can upload a single file with multiple features or multipart single features).
  • Draw a polygon on the map by clicking on the Bounding box or Polygon icons (single feature only).

Select the date range for your time period of interest.

Specify the range of dates for which you wish to extract data by entering a start and end date (MM-DD-YYYY) or by clicking on the Calendar icon and selecting dates a start and end date in the calendar.

Adding Data Layers

Enter the product short name (e.g., MOD09A1, ECO3ETPTJPL), keywords from the product long name, a spatial resolution, a temporal extent, or a temporal resolution into the search bar. A list of available products matching your query will be generated. Select the layer(s) of interest to add to the Selected layers list. Layers from multiple products can be added to a single request. Be sure to read the list of available products available through AppEEARS.

Extracting an area in AppEEARS
Selecting Output Options

Two output file formats are available:

  • GeoTIFF
  • NetCDF-4

If GeoTIFF is selected, one GeoTIFF will be created for each feature in the input vector polygon file for each layer by observation. If NetCDF-4 is selected, outputs will be grouped into .nc files by product and by feature.

If GeoTIFF is selected, you must select a projection
Interacting with Results

Once your request is completed, from the Explore Requests page, click the View icon in order to view and interact with your results. This will take you to the View Area Sample page.

The Layer Stats plot provides time series boxplots for all of the sample data for a given feature, data layer, and observation. Each input feature is renamed with a unique AppEEARS ID (AID). If your feature contains attribute table information, you can view the feature attribute table data by clicking on the Information icon to the right of the Feature dropdown. To view statistics from different features or layers, select a different AID from the Feature dropdown and/or a different layer of interest from the Layer dropdown.

Interpreting Results in AppEEARS

Be sure to check out the AppEEARS documentation to learn more about downloading the output GeoTIFF or NetCDF-4 files.

MODIS/VIIRS Subsetting Tools Suite

ORNL DAAC also has several MODIS and VIIRS Subset Tools for subsetting data.

  • With the Global Subset Tool, you can request a subset for any location on earth, provided as GeoTIFF and in text format, including interactive time-series plots and more. Users specify a site by entering the site's geographic coordinates and the area surrounding that site, from one pixel up to 201 x 201 km. From the available datasets, you can specify a date and then select from MODIS Sinusoidal Projection or Geographic Lat/Long. You will need an Earthdata login to request data.
  • With the Fixed Subsets Tool, you can download pre-processed subsets for 3000+ field and flux tower sites for validation of models and remote sensing products. The goal of the Fixed Sites Subsets Tool is to prepare summaries of selected data products for the community to characterize field sites. It includes sites from networks such as NEON, ForestGeo, PhenoCam and LTER that are of relevance to the biodiversity community.
  • With the Web Service, you can retrieve subset data (in real-time) for any location(s), time period, and area programmatically using a REST web service. Web service client and libraries are available in multiple programming languages, allowing integration of subsets into users' workflow.
Directions for subsetting data with the ORNL DAAC MODIS and VIIRS subset tool

Spatial Data Access Tool (SDAT)

ORNL DAAC’s SDAT is an Open Geospatial Consortium standards-based web application to visualize and download spatial data in various user-selected spatial/temporal extents, file formats, and projections. Several data sets including land cover, biophysical properties, elevation, and selected ORNL DAAC archived data are available through SDAT. KMZ files are also provided for data visualization in Google Earth.

Within SDAT, select a dataset of interest. Upon selection, the map service will open displaying the various measurements, with the associated granule, and a visualization of the selected granule.

Canopy Height, Kalimantan Forests, Indonesia, 2014 from the Oak Ridge National Laboratory Distributed Active Archive Center Spatial Data Access Tool.

Canopy Height, Kalimantan Forests, Indonesia, 2014 from the Oak Ridge National Laboratory Distributed Active Archive Center Spatial Data Access Tool.

You can then select your spatial extent, projection, and output format for downloading.

Canopy Height, Kalimantan Forests, Indonesia, 2014 from the Oak Ridge National Laboratory Distributed Active Archive Center Spatial Data Access Tool with various output options.

Canopy Height, Kalimantan Forests, Indonesia, 2014 from the Oak Ridge National Laboratory Distributed Active Archive Center Spatial Data Access Tool with various output options.

SeaDAS

SeaDAS is a comprehensive software package for the processing, display, analysis, and quality control of ocean color data. While the primary focus of SeaDAS is ocean color data, it is applicable to many satellite-based earth science data analyses.

SeaDAS is a comprehensive software package for the processing, display, analysis, and quality control of ocean color data. This image shows ocean color, sea surface temperature and non-algal material plus colored dissolved organic matter.

SeaDAS is a comprehensive software package for the processing, display, analysis, and quality control of ocean color data. This image shows ocean color, sea surface temperature and non-algal material plus colored dissolved organic matter.

SeaDAS processing components (OCSSW)

SeaDAS processing components (OCSSW)

Within SeaDAS, you can visualize data, and re-project, crop and create land, water and coastline masks. You can perform mathematical and statistical operations, such as band math (band additions and subtractions, band ratios), plot histograms, scatter plots and correlation plots, and you can incorporate in-situ data.

If you only have reflectance values, you can use the band ratio and algorithm coefficients within SeaDAS to derive chlorophyll-a. If using Landsat data, you need to convert Level 1 to Level 2 data. To do this, make sure your data processors within SeaDAS are updated.

In-situ data can be incorporated as well; this is critical for data validation. To integrate in-situ data, whether from SeaBASS or from another source, the data must be in a specific format. The file must be tab-delimited with fields of data, time, station (with the stations defined in the file), lat, lon, depth. Date and time are relevant as well. They need to be defined as YYYYMMDD and time as HH:MM:SS. If not defined properly, the file must be reworked to make it readable.

Once the tab-delimited file is complete, you can select Vector/Import and then select your data source. Remember in order to validate your remotely sensed data, you only want to look at the in-situ data at the surface (depth of 0).

SeaDAS allows for the integration of in-situ data in order to validate satellite measurements.

SeaDAS allows for the integration of in-situ data in order to validate satellite measurements.

For more detailed tutorials:

  • SeaDAS Video tutorials and demos—OB.DAAC recommends viewing the first few in the order they are shown. The core videos are listed first, followed by multi-tool case studies; everything below that appears in chronological order by release date.
  • SeaDAS FAQs—Frequently asked questions from SeaDAS users.

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Published May 12, 2020

Page Last Updated: Oct 15, 2020 at 4:34 PM EDT