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Annual high-resolution estimates of Land Use and Cover from the Mawas research area, Indonesia

Submitted by ORNL DAAC Staff on 2021-05-21
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Land cover maps at 30 m resolution across Mawas, Central Kalimantan, Indonesia in 1994 (left) and 2004 (right).

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Annual land use/cover (LUC) maps at 30 m resolution across Mawas, Central Kalimantan, Indonesia.

Midwestern USA 2018 crop growing season Land Cover-Specific SIF

Submitted by ORNL DAAC Staff on 2021-04-19
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Examples of spatial patterns of reconstructed SIF at 4 km resolution. Only pixels with a fraction of the specific vegetation type larger than 0.1 are shown. For Total SIF, only pixels with a fraction of corn, soybean, grass/pasture, and forest larger than 0.8 are displayed.

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Estimated solar-induced chlorophyll fluorescence (SIF) of specific vegetation types and total SIF available at 4-km resolution.
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Annual Estimates of Global Riverine Nitrous Oxide Emissions

Submitted by ORNL DAAC Staff on 2021-03-24
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Riverine N2O emission estimates from headwater streams (a, c, and e) and high-order rivers (b, d, and f) for the 1900s, 1960s, and 2000s. The right panel shows the latitudinal distribution of riverine N2O emissions with the uncertainty range as the standard deviation (shaded areas).

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Modeled estimates of annual NO2 emissions for two sets of global rivers and streams covering years 1900-2016 available.

Tidal Wetlands Productivity for Conterminous US Based on Blue Carbon

Submitted by ORNL DAAC Staff on 2020-10-05
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Example of average daily gross primary production (GPP) per m2 at 250 m resolution shown for wetlands in the North and South Ten Thousand Islands in the Florida Everglades. Mapped values are an average of all 16-day periods from 2000-2019. Source: Feagin et al., 2020.

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Tidal wetland gross primary production estimates across the Conterminous US derived with the spatially-explicit Blue Carbon model.

Improved LiDAR-derived Biomass for Sonoma County, CA

Submitted by ORNL DAAC Staff on 2020-07-06
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Estimated aboveground biomass (Mg/ha) for Sonoma County at 30 m spatial resolution with the 5th-95th percentile range and the standard deviation (SD) of per-pixel biomass estimates shown in the top left and bottom left, respectively.

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A new dataset used a parametric modeling approach to estimate biomass from airborne LiDAR data and field measurements.

NASA Data Helps Researcher Understand Coastal Mangrove Forests

Submitted by ORNL DAAC Staff on 2020-06-25
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Dr. David Lagomasino uses satellite, airborne, drone, and ground measurements to identify areas of coastal resilience and vulnerability.

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Dr. David Lagomasino uses NASA data to study how the Earth's landscape responds to changes caused by natural events and rapid urban expansion.