11 to 20 of 34 Results
Jun 9, 2020 - Roughness Scenarios
FLUD Research Group, 2020, "Flow Inundation Extents: Baseline Roughness Scenario", https://doi.org/10.18738/T8/KBN60V, Texas Data Repository, V1
Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output... |
Jun 9, 2020 - Roughness Scenarios
FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +5% Roughness Scenario", https://doi.org/10.18738/T8/Z2CPJ1, Texas Data Repository, V1
Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output... |
Jun 9, 2020 - Roughness Scenarios
FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +10% Roughness Scenario", https://doi.org/10.18738/T8/YCKBGY, Texas Data Repository, V1
Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output... |
Jun 9, 2020 - Roughness Scenarios
FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +25% Roughness Scenario", https://doi.org/10.18738/T8/MZQ3O8, Texas Data Repository, V1
Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output... |
Jun 9, 2020 - Roughness Scenarios
FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +50% Roughness Scenario", https://doi.org/10.18738/T8/AQL6EC, Texas Data Repository, V1
Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output... |
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/GK5DBZ, Texas Data Repository, V1
This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia... |
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/EQUZO5, Texas Data Repository, V1
This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia... |
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 6.0", https://doi.org/10.18738/T8/WHS3BR, Texas Data Repository, V1
This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia... |
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/4TVY7S, Texas Data Repository, V1
This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes all environmental variables (... |
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 2.0", https://doi.org/10.18738/T8/VMKLOK, Texas Data Repository, V1
This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes all environmental variables (... |