High-Resolution Vegetation Traits and Fluxes during NASA's SHIFT campaign, for Dangermond Preserve, California, 2022

OverviewThis dataset provides high-resolution (30 m) remote sensing and modeling data collected as part of the SHIFT (Surface Biology and Geology High-Frequency Time Series) campaign conducted in 2022 at the Dangermond Preserve, California. The data, sourced from AVIRIS-NG (Airborne Visible/Infrared Imaging Spectrometer-Next Generation), TROPOMI (TROPOspheric Monitoring Instrument) SIF, and outputs from the Climate Modeling Alliance (CliMA) Land model, offers valuable insights into vegetation traits, plant functional types, ecosystem dynamics, and biogeochemical cycling.Data FilesCliMA Land Outputshift_fluxes_day_00_clima_fit_reg_jmax.nc to shift_fluxes_day_12_clima_fit_reg_jmax.nc: Contains ecosystem fluxes for each day, covering parameters like gross primary production (GPP) and sun-induced fluorescence (SIF) across multiple wavelengths.pft_shift_fluxes_day_00_clima_fit_reg_jmax.nc to pft_shift_fluxes_day_12_clima_fit_reg_jmax.nc: Similar to the above, but focused on specific plant functional types (PFTs).Vegetation Traitsmean_masked_chl_aviris_dangermond_clima_fit.nc: Average chlorophyll content traits over various timeframes.mean_masked_lma_aviris_dangermond_clima_fit.nc: Average Leaf Mass per Area (LMA) traits over multiple observations.mean_masked_lwc_aviris_dangermond_clima_fit.nc: Average leaf water content (LWC) traits over different periods.lma_aviris_dangermond_clima_fit_time_00.nc to lma_aviris_dangermond_clima_fit_time_12.nc: LMA data across specific time points.chl_aviris_dangermond_clima_fit_time_00.nc to chl_aviris_dangermond_clima_fit_time_12.nc: Chlorophyll content across specific time points.lwc_aviris_dangermond_clima_fit_time_00.nc to lwc_aviris_dangermond_clima_fit_time_12.nc: Leaf water content data over time.lai_aviris_dangermond_time_00.nc to lai_aviris_dangermond_time_12.nc: Leaf Area Index (LAI) data for various time frames.Plant Functional TypesDangermond_Vegetation_WHRTYPE.nc: Spatial distribution of plant functional types within the Dangermond Preserve at 30 m resolution.TROPOMI DataTROPOMI_SIF740nm-v1.001deg_regrid_Dangermond_tll_clipped_458_492.nc: Regridded sun-induced fluorescence data at 740 nm.TROPOMI_SIF740nm-v1.005deg_regrid_Dangermond_tll_clipped.nc: Updated regridded sun-induced fluorescence data at 740 nm.AVIRIS Dataaviris_dangermond.nc: Spectral reflectance data from the AVIRIS-NG instrument, detailing spectral information across 399 wavelengths.Clumping IndexCA18_Dangermond_norm_gediMetrics_25meters.csv: CSV file containing clumping index metrics at 25 meters resolution.CA18_Dangermond_norm_gediMetrics_25meters.tif: GeoTIFF file of clumping index metrics at 25 meters resolution.CA18_Dangermond_norm_gediMetrics_3meters.tif: GeoTIFF file of clumping index metrics at 3 meters resolution.GEDI_CI_map_ci_nan.nc: NetCDF file of clumping index map with NaNs for missing data.ci_map.nc: Clumping index map file.ci_map_reprojected_clipped.nc: Reprojected and clipped clumping index map file.PLSR DataPLSR_dangermond_traits.nc: PLSR model output related to various vegetation traits. Accessed from: https://avng.jpl.nasa.gov/pub/SHIFT/gridded/mosaic_traits_20240219/Usage GuidelinesThis dataset is ideal for researchers focusing on vegetation dynamics, ecological forecasting, and biogeochemical cycling. It supports environmental analysis and modeling.CitationWhen using this dataset, please cite it as follows:"High-Resolution Vegetation Traits and Fluxes during NASA's SHIFT campaign, for Dangermond Preserve, California, 2022, provided by Braghiere R. K./Caltech-NASA-JPL, Caltech Data Library, 2024."Contact InformationFor additional information or assistance with the dataset, please contact Braghiere R. K./Caltech-NASA-JPL.ReferencesBrodrick, P., R. Pavlick, M. Bernas, J.W. Chapman, R. Eckert, M. Helmlinger, M. Hess-Flores, L.M. Rios, F.D. Schneider, M.M. Smyth, M. Eastwood, R.O. Green, D.R. Thompson, K.D. Chadwick, & D.S. Schimel. (2023). SHIFT: AVIRIS-NG L2A Unrectified Reflectance. ORNL DAAC. https://doi.org/https://doi.org/10.3334/ORNLDAAC/2183Chadwick, K. D., Davis, F., Miner, K. R., Pavlick, R., Reynolds, M., Townsend, P. A., Brodrick, P. G., Ade, C., Allen, J., Anderegg, L., Angel, Y., Boving, I., Byrd, K. B., Campbell, P., Carberry, L., Cavanaugh, K. C., Cavanaugh, K. C., Easterday, K., Eckert, R., … Schimel, D. (2024). Unlocking Ecological Insights from Subseasonal Visible-to-Shortwave Infrared Imaging Spectroscopy: The SHIFT Campaign. Ecosphere.Queally, N., Davis, F. W., Chadwick, K. D., Ade, C., Anderegg, L., Angel, Y., Baker, B., Boving, I., Braghiere, R. K., Brodrick, P., Campbell, P., Cryer, J., Cushman, K. C., Dao, P. D., Dibartolo, A., Eckert, R., Grant, K., Heberlein, B., Johnson, M., … Schimel, D. S. (2024). SHIFT: Vegetation Plot Characterization, Santa Barbara County, CA, 2022. ORNL Distributed Active Archive Center. https://doi.org/10.3334/ORNLDAAC/2295Nature Conservancy (2022). Lidar Survey of Dangermond Preserve, CA. OpenTopography. https://doi.org/10.5069/G9T43R8K