N: 53.994 S: -54.1988 E: 180 W: -180
Description
This dataset contains Global Ecosystem Dynamics Investigation (GEDI) Level 4A (L4A) predictions of the aboveground biomass density (AGBD; in Mg/ha) and estimates of the prediction standard error within each sampled geolocated laser footprint. The footprints are located within the global latitude band observed by the International Space Station (ISS), nominally 51.6 degrees N and S and reported for the period 2019-04-18 to 2020-09-02. The GEDI instrument consists of three lasers producing a total of eight beam ground transects, which instantaneously sample eight ~25 m footprints spaced approximately every 60 m along-track. The GEDI beam transects are spaced approximately 600 m apart on the Earth's surface in the cross-track direction, for an across-track width of ~4.2 km. Footprint AGBD was derived from parametric models that relate simulated GEDI Level 2A (L2A) waveform relative height (RH) metrics to field plot estimates of AGBD. Height metrics from simulated waveforms associated with field estimates of AGBD from multiple regions and plant functional types (PFT) were compiled to generate a calibration dataset for models representing the combinations of world regions and PFTs (i.e., deciduous broadleaf trees, evergreen broadleaf trees, evergreen needleleaf trees, deciduous needleleaf trees, and the combination of grasslands, shrubs, and woodlands).
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Publications Citing This Dataset
| Title | Authors | Year Sort ascending | Referenced Datasets |
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| Validating remotely sensed biomass estimates with forest inventory data in the western US |
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| Extreme droughts shrink suitable habitats and reduce fitness for large mammals in the American West |
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| GEDI and Sentinel data integration for quantifying agroforestry tree height and stocks |
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| Evaluating GEDI for quantifying forest structure across a gradient of degradation in Amazonian rainforests |
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| Multiscale analysis of global variation in tree allometric relationships: parameter sets for global vegetation models |
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| Human degradation of tropical moist forests is greater than previously estimated |
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| Vicarious calibration of GEDI biomass with Landsat age data for |
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| Characterizing the structural complexity of the Earth's forests with |
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| Connecting spaceborne lidar with NFI networks: A method for improved estimation of forest structure and biomass |
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| Explainable Machine Learning for Geospatial Data Analysis: A Data-Centric Approach |
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| Evaluating the performance of airborne and spaceborne lidar for mapping |
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| Evaluation of GEDI footprint level biomass models in Southern African Savannas using airborne LiDAR and field measurements |
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| Above Ground Carbon Biomass Estimate with Physics-Informed Deep Network |
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| Quantifying aboveground biomass dynamics from charcoal degradation in Mozambique using GEDI Lidar and Landsat |
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| Forest Biomass Mapping Using Continuous InSAR and Discrete Waveform Lidar Measurements: A TanDEM-X/GEDI Test Study |
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| Computational tools for assessing forest recovery with GEDI shots and forest change maps |
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| Integrated global assessment of the natural forest carbon potential |
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| On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake |
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| Fusing GEDI with earth observation data for large area aboveground |
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| GEDI launches a new era of biomass inference from space |
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| GEDI4R: an R package for NASA's GEDI level 4 A data downloading, processing and visualization |
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| Challenges to aboveground biomass prediction from waveform lidar |
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