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71 to 80 of 125 Results
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 Dataverse, 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 Dataverse, 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/8UXWKH, Texas Data Repository Dataverse, V1
This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes all environmental variables (veget...
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0", https://doi.org/10.18738/T8/GQYIX2, Texas Data Repository Dataverse, V1
This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes all environmental variables (veget...
Jun 8, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/0PQLIB, Texas Data Repository Dataverse, V1
This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes all environmental variables (veget...
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/GMU4XY, Texas Data Repository Dataverse, V1
This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/F2U3QV, Texas Data Repository Dataverse, V1
This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...
Jun 9, 2020 - Environmental Analyses
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0", https://doi.org/10.18738/T8/ILRKFQ, Texas Data Repository Dataverse, V1
This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...
Jun 9, 2020 - Roughness Scenarios
FLUD Research Group, 2020, "Mesh Resolution of HEC-RAS Models: Average Point Spacing of 7.5m-15.0m", https://doi.org/10.18738/T8/CES19C, Texas Data Repository Dataverse, V1
Shapefiles of Computational Meshes for HEC-RAS Models for that have an average point spacing of 7.5m, 10.0m, 12.5m, and 15.0m (original). Created with the export feature of RAS-Mapper for HEC-RAS v 5.0.7 (Brunner, 2016) Brunner, G.W. (2016). HEC-RAS: River Analysis System, 2D Mod...
May 13, 2020 - Lyndon B. Johnson National Grasslands Evapotranspiration Partitioning Study
Adkison, Christopher, 2020, "Monthly Vapor Pressure Deficit Calculations", https://doi.org/10.18738/T8/HLFMSY, Texas Data Repository Dataverse, V1
These spreadsheets contain data for 30-min vapor pressure deficit calculations at Lyndon B. Johnson National Grasslands in Decatur, TX, part of the National Ecological Observatory Network from May 2019-February 2020.
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