34 North Data Visualization Special Session

34 North is holding a special session to display their photo-realistic computer model to represent the historic Delta ecosystem circa 1850. 34 North used its’ experience in GIS, map development and ecosystem modeling to create this data visualization. The purpose of this effort was to build an accurate computer model that will serve as a tool to increase our understanding of the historic Delta landscape circa 1850. The ecosystem model outputs will provide visual experiences using animations, perspective maps and storytelling techniques that describes the vast amount of detail in the Sacramento-San Joaquin Delta Historical Ecology Investigation (Whipple et al. 2012). This model and its visualizations can help guide future restoration efforts by increasing our understanding of the historic Delta landscape.

Using art and artistic principles to help communicate scientific concepts can enhance both scientific communication and artistic messages. The special session will explore how the line between art and science can be blended so that the two can come together to increase awareness of estuarine ecology.

The development of this model will be used to enhance the understanding of the historical ecology, hydrology and future restoration of the Sacramento Delta.  This project is aimed to reconstruct the ecology of the Delta as it once was allowing stakeholders to visualize how habitats were distributed and how ecological functions were maintained within the native California landscape.  Visualizing how streams, wetlands, lakes, and woodlands were organized along physical gradients will help scientists, engineers, and managers develop new strategies for more integrated and functional landscape management and restoration practices.


About 34 North:34 North has been a part of the effort to provide a solution for data sharing between entities to keep data as current and near real time as possible to enable adaptive management actions. Near real time data collected on the platform will inform decisions about the future of this region. Through the timely sharing of data, it will be possible to link and compare data collected in the different studies, avoid duplication of data, allow for near real time data analysis and provide updates outside of the normal quarterly report format.