Georgianna Strode

Georgianna Strode is an Application Developer for Florida State University


2013 Recipient of FSU's Disaster and Community Risk Fellowship for work on creating high-resolution dasymetric population maps.

DIGITECH, Excellence Award


Land Use or Land Cover? Visualizing Florida's Complex Landscape

The concepts of ‘land use’ and ‘land cover’ are used to convey information about a landscape. Although they are vastly different concepts, the terms have become intermingled in GIScience, resulting in a simplified one-to-one relationship that can be visualized using univariate mapping techniques.

This research posits that the relationships between land use and land cover are complex and are best represented bivariately. This geovisualization consists of three parts: 1. A bivariate map using color and symbolization to represent and differentiate the two data sources. 2. A two-dimensional statistical legend informs the data combinations and data distributions. 3. Visual analytics using Sankey (flow) diagrams show the relationships and frequencies of categorical data interactions.


Getting Started using Florida's U.S. National Grid Spatial Data Model

The US National Grid (UNSG) is a standardized geographic framework used for emergency response and rescue for its ability to pinpoint a location when landmarks are not available. Adopted by FEMA and many other government agencies, the USNG is quickly growing in use as a locational reference system.

The inherent nature of the USNG makes it well suited to double as a GIS spatial data model. The database structure can store data at multiple scales, support GIS functionality, and allow easy data transfer. The standardization allows state and local governments using this data model to easily transfer data, even at different scales.

This presentation introduces the USNG and shows how to download sample data and get started using it in your organization. Sample data includes basic population, land use, and land cover at the 1-km grid cell scale. Demonstrations will clarify how this data can be intermixed and customized to suit the needs of individual organizations.