Digital elevation models with elevation uncertainty treatment, Grand Bay Estuary, Mississippi, 2015 - 2022

This data release includes outputs that were created using Monte Carlo simulations with the aim to reduce elevation overestimation in coastal wetlands at Grand Bay, MS. We evaluated the performance of coastal wetland elevation refinement by using bare earth digital elevation models (DEMs) and DEMs created from the last return from the light detection and ranging (lidar) point cloud, hereafter referred to as the minimum bin DEM. We additionally created DEMs for a range of resolutions – 3 m, 5 m, and 10 m. The elevation source data were from 2015 and 2022. Using high-accuracy elevation data collected from 2013 to 2025 in the Mississippi Sound, we assessed initial error of the DEMs. For each DEM, we used Monte Carlo simulation with 1,000 iterations to create new DEM realizations. Next, we summarized the 1,000 DEM realizations by calculating the 5th – 95th percentiles (that is, median and every 5th percentile) of elevation by pixel across all iterations. This data release includes all percentiles from each DEM type and resolution. We used the previously mentioned in-situ elevation observations to assess the performance of the DEM error reduction. We used mean bias error (MBE) to identify a best, upper, and lower estimate for each bare earth DEM where MBE was closest to 0 cm, 5 cm, and -5 cm, respectively. These DEMs are recommended for use in wetland modeling over the full range of percentiles.

[
  "010:12"
]

[
  "geospatial"
]