Big Data

Combining resources from NASA, NEON, and other large-scale ecological studies.

Sustainable Science

Long-term studies are drivers of scientific innovation. Combining the resources of NASA with those of the National Ecological Observatory Network and other open source data sets and citizen science projects, we can better predict the impacts of climate change on our country and world.

Our Data Sources and Inputs

Remote Sensing
Climate Projections

From NEX-GDDP: NASA Earth Exchange Global Daily Downscaled Climate Projections: Global downscaled climate scenarios for 21 General Circulation Models (GCMs) from CMIP5. Emission scenarios include options for representative concentration pathways (RCPs) 4.5 and 8.5 from 2006-2099, as well as historical retrospective model runs from 1950-2006. Precipitation and temperature products are available.

Environmental
Global Climate

From TERRACLIMATE, we derive montly averages for: actual evapotranspiration (mm), climatic water deficit (mm), Palmer Drought Severity Index, reference evapotranspiration, precipitation (mm), runoff (mm), soil moisture (mm), downward surface shortwave radiation (W/sq. m), snow water equivalent (mm), minimum and maximum temperature (C), vapor pressure (kPA), vapor pressure deficit (kPa), and wind speed (m/s).

Remote Sensing
Hyperspectral Indices

Environmental
Land Cover

Our Land Cover products, derived from the National Land Cover Database include percent tree cover, percent impervious cover, and the land cover type at a point.

Environmental
Local Climate

From the Gridded Surface Meteorological Dataset (GRIDMET), we derive for daily, weekly, monthly, seasonal, and yearly timestamps: average maximum and minimum temperature (K), total precipitation (mm), total evapotranspiration (grams/mm), and average vapor pressure deficit (kPa).

Remote Sensing
MODIS ET and PET

From NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) we can obtain the average daily evapotranspiration and potential evapotranspiration at broad spatial and high temporal resolution.

Remote Sensing
MODIS LAI and FPAR

From NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) we can obtain the Fraction of Absorbed Photosynthetically Active Radiation (fPAR) and Leaf Area Index (LAI) and a broad spatial and high temporal resolution.

Remote Sensing
MODIS Land Surface Temperature

From NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) we can obtain the land surface temperature at 10:30 (TERRA), 13:30 (Aqua), 22:30 (TERRA), and 01:30 (Aqua) local time at broad spatial, high temporal resolution.

Remote Sensing
MODIS Phenology

From NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) we can obtain spatially explicit days since Jan 1, 2000 that correspond to: vegetation green-up, vegetation maturity, vegetation senescence, and vegetation dormancy.

Remote Sensing
MODIS Vegetation Indices

From NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) we can obtain a Normalized Difference Vegetation Index (NDVI) and an Enhanced Vegetation Index (EVI) and broad spatial and high temporal resolution.

Remote Sensing
Precipitation

From NASA's TRMM 3B43 models we can obtain monthly precipitation rate (mm/hr) estimates across the globe at a point, or within a region.

Remote Sensing
Productivity

From NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) we can obtain annual gross primary productivity, annual net primary productivity, and the cloud contamination which may affect annual productivity at brad spatial and high temporal resolution.

Environmental
Soil Metrics

From the world soil database, our inputs include: organic carbon content, pH, cation exchange capacity, sand content, silt content, volume of coarse fragments, clay content, bulk density, and soil depth. Sub-order classification across the US and World is also available.

Remote Sensing
Soil Moisture

From the SMOS mission, we derive spatially explicit surface soil moisture (mm), subsurface soil moisture (mm), and soil moisture profile.

Remote Sensing
Topography

Topography data is derived from the NASA Shuttle Radar Topography Mission (SRTM). Metrics include elevation (meters), slope (radians), and aspect (radians).

Remote Sensing
Vegetation Indices

From LANDSAT, we derive spatially explicit vegetation indices, specifically: Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Burn Ratio (NBR).

Remote Sensing
Vegetation Structure

Vegetation Structure

Want to use your own data?

Combine our data through our tutorials and products with your won biodiversity data to produce maps and distributions of your study systems - leveraging your research with the power of NASA, NEON, and the National Science Foundation.
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Our Partners

PBGJAM is a collaborative project with financial and logistical support from the following partners