Alexandra Martin | Alissa Patterson | Alessandra Puig-Santana | Katherine Rosencrance | Lauren Harris | Pol Carbó Mestre
The Gaviota Region Interactive Planner is an R Shiny app that allows users to visualize the degree of overlap of natural resources, environmental threats, and DEJ/EJ issues in the Santa Barbara County region. This app is designed to help users make informed decisions regarding land-use planning and natural resource conservation. This is a part of a group project for the Master of Environmental Science and Management program at the Bren School, University of California Santa Barbara. The project is being developed for The Nature Conservancy to aid in their efforts to preserve natural resources in the Gaviota region.
The application is designed to visualize and analyze spatial environmental data, with a focus on three primary axes: Natural Resources, Environmental Threats, and DEJ/EJ issues. Each axis contains multiple layers of data that define our region, highlighting areas of interest based on different metrics. Users can adjust the weight of each layer and view an aggregated representation of the data. Additionally, the app provides the ability to extract statistics for a specific area of interest selected by the user.
The three axes of the app contain the following data:
- Natural Resources: water resources, soil, biodiversity, and resilience.
- Environmental Threats: droughts, flooding, wildfires, and climate exposure.
- DEJ/EJ issues: pollution, isolation from nature, and demographics.
The natural resources axis has an additional map that allows comparing stakeholder groups' resource priorities. Users choose two groups, and the map displays the relative preferences.
Environmental data was collected from several open-source databases, including Data Basin and Santa Barbara County Conservation Blueprint Atlas, and were developed by TNC, the Conservation Biology Institute (CBI), the Federal Emergency Management Agency (FEMA), California Department of Water Resources (DWR) and the CalEnviroScreen 3.0.
Spatial data was processed using the Environmental Evaluation Modeling System (EEMS) (Sheehan and Gough 2016) allowing us to integrate metrics of different types into single spatial layers.
We welcome contributions to this repository and encourage the public to explore the app and provide feedback for future updates and improvements.
If you have any questions about this Repo, please do not hesitate to send us an email with your inquiries. Additionally, if you come across any bugs or have any recommendations for improvements, please contact us at [email protected]