This dataverse contains data inputs and products from two complimentary analyses: a spatial analysis and a machine learning approach. Both analyses were geared towards understanding relative importance of ecological factors within the Mission River Floodplain. These datasets are broken down as follows:

Digitized Trees:

    Digitized Downed/Standing Trees in the Mission River Floodplain

Spatial Analysis

    Environmental Variables Used in Spatial Analysis

    Counts of Downed Trees for Levels of Environmental Variables: Results of Spatial Analysis

ML Approach:

    Environmental Variables Used in Maxent Machine Learning Approach

    MaxentVariableselection Inputs/Outputs

    Maxent Models (digitized downed trees with structure):

        Model output with six variables and regularization multiplier of 1.0

        Model output with six variables and regularization multiplier of 2.0

        Model output with six variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 1.0

        Model output with three variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 7.0

    Maxent Models (all digitized downed trees):

        Model output with six variables and regularization multiplier of 1.0

        Model output with six variables and regularization multiplier of 2.0

        Model output with six variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 1.0

        Model output with three variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 6.0

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191 to 200 of 223 Results
Inundation_Probability.zip
Jun 8, 2020 - Environmental Variables Used in Maxent Machine Learning Approach
ZIP Archive - 5.9 MB - MD5: c12f5ef9c22b4f20bf912851ae24dbcb
Calculated inundation probability within the Mission River Floodplain. Inundation probability was based on mean daily discharge record (1939-2016) using inundation extents from Castillo et.al. (under review) as indexes. All indices (as raster maps of inundation extent) are sorted...
Soil_Type_Class.zip
Jun 8, 2020 - Environmental Variables Used in Maxent Machine Learning Approach
ZIP Archive - 783.0 KB - MD5: 1200a0ae831ca4b35ff44947f67dcfd7
Raster maps representing soil type is derived from polygon geometries that represent patches from the Ecological Modeling Systems of Texas (Elliott et.al. 2014). Each patch is assigned a soil type classification are based on the EcoName fields within this dataset, respectively. O...
Vegetation_Community_Class.zip
Jun 8, 2020 - Environmental Variables Used in Maxent Machine Learning Approach
ZIP Archive - 1.6 MB - MD5: 1e6f76fdf7012966cc702c301b3e04eb
Raster map representing vegetation community is derived from polygon geometries that represent patches from the Ecological Modeling Systems of Texas (Elliott et.al. 2014). Each patch is assigned a vegetation community classification is based on the CommonName fields within this d...
Digitized Downed/Standing Trees in the Mission River Floodplain
Jun 8, 2020
FLUD Research Group, 2020, "Digitized Downed/Standing Trees in the Mission River Floodplain", https://doi.org/10.18738/T8/UUAQT7, Texas Data Repository, V1
Downed trees (N=9505) were digitized by members of the FLUD Research group (faculty and student researchers). Student researchers consist of graduate and undergraduate students. Undergraduate student researchers worked at the supervision and expertise of faulty and graduate stude...
all_Lidar_trees_wGeometry_0p000.zip
Jun 8, 2020 - Digitized Downed/Standing Trees in the Mission River Floodplain
Shapefile as ZIP Archive - 1.7 MB - MD5: e116143f6548830b7b391267c1d7987f
All digitized downed trees. This data is processed to inform both Environmental Analyses and Hydrodynamic Modelling of Roughness Scenarios
all_Lidar_trees_wGeometry_0p150_ecolpnt_ecolrascsv.csv.zip
Jun 8, 2020 - Digitized Downed/Standing Trees in the Mission River Floodplain
Shapefile as ZIP Archive - 78.5 KB - MD5: 4a4a8719fb8a8caa9f99fc030e2a0b84
The ecologically significant point of each downed tree with structure, which is coincident with the root wad and snapped to the nearest pixel location of the model topography raster map (resolution = 1.0). These locations are input into all Environmental Analyses.
all_Lidar_trees_wGeometry_0p150.zip
Jun 8, 2020 - Digitized Downed/Standing Trees in the Mission River Floodplain
Shapefile as ZIP Archive - 994.2 KB - MD5: e2758cfd5462be8d9a64a0e3ffd95d88
Downed trees with structure (N=4571) that are used to inform Environmental Analyses. These tree geometries contain the normalized difference in root wad and tree crown (ratio) as well as direction that the tree fell (in Cartesian Degrees) (DIRN field). All operations within envir...
tree_location_merge.zip
Jun 8, 2020 - Digitized Downed/Standing Trees in the Mission River Floodplain
Shapefile as ZIP Archive - 8.9 MB - MD5: 0b0766c57e2f52f364db1785cf6a8349
Standing trees within the Mission River Floodplain.
Counts of Downed Trees for Levels of Environmental Variables: Results of Spatial Analysis
Jun 8, 2020
FLUD Research Group, 2020, "Counts of Downed Trees for Levels of Environmental Variables: Results of Spatial Analysis", https://doi.org/10.18738/T8/YHNJAP, Texas Data Repository, V1
The following archives consists of polygon shapefiles that contain single and combinations of two environmental variables. Within each of these shapefiles are stratified levels of values, where each level contains counts of ecologically significant points that are associated with...
ESP_0p150_EDFRelev.zip
Jun 8, 2020 - Counts of Downed Trees for Levels of Environmental Variables: Results of Spatial Analysis
Shapefile as ZIP Archive - 11.2 MB - MD5: 611f7cd7aaf2f539a5f8327a70a48d64
Polygon shapefile that contains counts of downed trees within each stratified level (range) that is a result of the combination of euclidean distance from river and elevation within the model evaluation domain.
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