Processing of Geospatial Data for the Habitat Risk Software
Mitchell, Corey I.; Walter, W. David; Hollingshead, Nicholas; Schuler, Krysten
The Processing of Geospatial Data for the Habitat Risk Software allows the user to process publicly available geospatial data into the format necessary for inclusion in the Habitat Risk Software (Hanley et al. 2021; doi.org/10.7298/rcz8-nw50), which is the software that leverages Bayesian Hierarchical models (Clayton and Kaldor 1987; Banderjee et al. 2004; Gelman et al. 2004; Evans et al. 2016) with disease testing data to estimate the spatial risk of Chronic Wasting Disease in white-tailed deer (Odocoileus virginianus). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
The software is shared under a MIT License. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.eCommons files updated 2022-07-06. Clarified wording in readme file per peer review comments, updated broken code, updated packages, and updated gNATSGO dataset version and instructions.
Financial support comes from: (1) Michigan Disease Initiative - Optimizing CWD Surveillance: Regional Synthesis of Demographic, Spatial, and Transmission-Risk Factors (2019); (2) Tennessee Wildlife Resources Agency - Modeling Risk of Infection for Individually Harvested Deer & Estimating Prevalence When Sampling is Limited (2020); (3) Michigan Disease Initiative - SOP4CWD Dashboard: A Web Application for Disease Visualization and Data-Driven Decisions (2020); (2) Multistate Conservation Grant Program - Surveillance Optimization Project for Chronic Wasting Disease: Streamlining a Web Application for Disease Visualization and Data-Driven Decisions (2021).
Geospatial Data; Processing; R software