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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/