New Page
EOSDIS (Earth Observing System Data and Information System) is a NASA
initiative that provides access to a vast array of Earth science data collected by
satellites. It supports the collection, processing, archiving, and distribution of Earth
observation data to enable research and application in various fields such as climate,
weather, natural disasters, and ecosystems.
Worldview, a tool within EOSDIS, allows users to visualize this data
interactively, enabling easy exploration of satellite imagery and environmental data in
near-real time.
EOSDIS Worldview uses the Global Imagery Browse Services (GIBS) to rapidly
retrieve its imagery for an interactive browsing experience. While EOSDIS
Worldview uses Open Layers as its mapping library.
This open source code app from NASA's ESDIS provides the capability to
interactively browse over 1000 global, full-resolution satellite imagery layers and
then download the underlying data. Many of the imagery layers are updated daily and
are available 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. Arctic and Antarctic
views of many products are also available for a "full globe" perspective.
Geostationary imagery layers are also now available. These are provided in ten
minute increments for the last 90 days. These full disk hemispheric views allow for
almost real-time viewing of changes occurring around most of the world. Browsing
on tablet and smartphone devices is generally supported for mobile access to the
imagery.
Interesting layers
• Land Surface Temperature
Land Surface Temperature is the temperature of the land surface in Kelvin
(K). This measurement differs from air temperature measurements as it
provides the temperature of whatever is on the surface of the Earth for
example, bare sand in the desert, ice and snow covered area, a leaf covered
tree canopy and even the temperature of man-made buildings and roads. Land
Surface Temperature is useful for monitoring changes in weather and climate
patterns and used in agriculture to allow farmers to evaluate water
requirements for wheat, or determine frost damage in orange groves.
• Carbon Dioxide
The Carbon Dioxide (L3, Free Troposphere, Monthly) layer displays monthly
Carbon Dioxide in the free troposphere. It is created from the AIRX3C2M data
product which is the AIRS mid-tropospheric Carbon Dioxide (CO2) Level 3
Monthly Gridded Retrieval, from the AIRS and AMSU instruments on board of
Aqua satellite. It is monthly gridded data at 2.5x2 degreee (lon)x(lat) grid cell
size. The data is in mole fraction units (data x 10^6 =ppm in volume). This
quantity is not a total column quantity because the sensitivity function of the
AIRS mid-tropospheric CO2 retrieval system peaks over the altitude range 6
10 km. The quantity is what results when the true atmospheric CO2 profile is
weighted, level-by-level, by the AIRS sensitivity function.
• Relative Humidity
Relative humidity is the ratio of the amount of water vapor in air to the total
amount of water vapor the air can hold at specified temperature and pressure.
Warm air can hold more water vapor than cold air, so the same amount of
water vapor results in higher relative humidity in cool air than in warm air.
AIRS relative humidity is derived from AIRS temperature and water vapor and
is calculated as the fraction of retrieved humidity mixing ratio and
temperature-dependent saturation mixing ratios.
• Aboveground Biomass
The Global Ecosystem Dynamics Investigation (GEDI) Level 4B (L4B)
dataset provides estimates of aboveground biomass density (AGBD) and
associated uncertainty per 1 km x 1 km EASE-Grid 2.0 grid cells globally
within -52 and 52 degrees latitude. GEDI L4B uses a hybrid model-based
inference, accounting for uncertainty due to GEDI's sampling of the 1km grid
area and Level 4A footprint-level biomass modeling. Accurate estimation of
AGBD helps assess the carbon sequestration potential of forests and the
impacts of land-use changes on atmospheric carbon dioxide concentrations.
• Canopy Characteristics
The GEDI L3 Gridded Land Surface Metrics dataset provides Global
Ecosystem Dynamics Investigation (GEDI) Level 3 (L3) gridded mean canopy
height, standard deviation of canopy height, mean ground elevation, standard
deviation of ground elevation, and counts of laser footprints per 1 km x 1 km
grid cells globally within -52 and 52 degrees latitude.
L3 gridded products can be used to characterize important carbon and water
cycling processes, biodiversity, habitat and can also be of immense value for
climate modeling, forest management, snow and glacier monitoring, and the
generation of digital elevation models.
• Vegetation Indices
Vegetation indices are used for monitoring of vegetation conditions and can be
used to identify areas undergoing land cover changes. These data may be used
as input for modeling global biogeochemical and hydrologic processes and
global and regional climate. These data also may be used for characterizing
land surface biophysical properties and processes including primary production
and land cover conversion. Vegetation indices also provide information on the
health of vegetation and can assist farmers and resource managers monitor the
health and development of their crops and fields over the growing season.
• Flood Hazard
The Flood Hazard: Frequency and Distribution layer indicates the relative
distribution and frequency of flood hazard. Global Flood Hazard Frequency
and Distribution is a 2.5 minute grid derived from a global listing of extreme
flood events between 1985 and 2003 (poor or missing data in the early/mid
1990s) compiled by Dartmouth Flood Observatory and georeferenced to the
nearest degree. The resultant flood frequency grid was then classified into 10
classes of approximately equal number of grid cells. The greater the grid cell
value in the final data set, the higher the relative frequency of flood
occurrence.
Population Density
The purpose of the data set is to provide estimates of population count for the
years 2000, 2005, 2010, 2015, and 2020, consistent with national censuses and
population registers with respect to relative spatial distribution, but adjusted to
match United Nations country totals.
• Soil Moisture
The Soil Moisture (Normalized Polarization Difference, Day) layer displays
gridded estimates of soil moisture in the top 1 cm of soil, averaged over the
AMSR-E retrieval footprint, and is measured in grams per centimeter by
volume (g/cm) Soil moisture is estimated from AMSR-E/Aqua L2A brightness
temperature (Tb) measurements using the Normalized Polarization Difference
algorithm (NPD) approach.
• Earth at Night
Viewing the Earth at night affords us a different view of the Earth's surface.
https://nasa-gibs.github.io/gibs-api-docs/
https://github.com/nasa-gibs/worldview
Accessing via Python
https://nasa-gibs.github.io/gibs-api-docs/python-usage/