Kelp forests are critical nearshore habitats, and understanding their spatiotemporal distribution across Washington State is essential for effective stewardship and management. Current floating kelp maps in Washington consist of a patchwork of multiple datasets in various formats, including remotely sensed classified imagery from fixed-wing aerial and drone surveys, as well as lines and polygons from kayak- and boat-based surveys. This diversity makes comparison and spatiotemporal change analysis challenging at the statewide level. To address this, the Nearshore Habitat Program at the Washington State Department of Natural Resources developed a linear extent model for floating kelp distribution. This model summarizes annual kelp presence along 1-km coastal line segments using the best available and most up-to-date survey data. The linear extent model builds on legacy data structures to ensure compatibility with other marine vegetation geospatial datasets. It employs multiple ETL pipelines to synthesize a variety of data streams into a single, synoptic map of kelp forests in Washington State. This new dataset is already being utilized by marine vegetation researchers and managers. This presentation will cover the technical aspects of developing this statewide spatial dataset, including the use of Python scripting for data processing and automation, methods for harmonizing spatial data from disparate sources, and strategies for sharing geospatial datasets with users of varying technical expertise.
