You are here

Tools for spatial statistical modeling on stream networks (STARS and SSN)

January, 2010

Spatial statistical models for streams provide a new set of analytical tools that can be used to improve predictions of physical, chemical, and biological characteristics on stream networks. The Spatial Tools for the Analysis of River Systems (STARS) and Spatial Stream Network (SSN) modelss are unique because they account for patterns of spatial autocorrelation among locations based on both Euclidean and in-stream distances. They also have practical applications for the design of monitoring strategies and the derivation of information from databases with non-random sample locations. Generating the spatial data needed to fit these statistical models requires practical skills in multiple disciplines including ecology, geospatial science, and statistics. The tools' home page hosted by RMRS Air, Water, and Aquatic Environments supports two sets of tools that have been developed to make the methodology more accessible to users: the STARS ArcGIS toolset and the SSN package for R statistical software. These models were developed by researchers at NOAA and Queensland University of Technology.


STARS: ArcGIS Toolset

SSN and STARS are powerful tools for spatial statistical modeling of stream temperature and other stream characteristics.
SSN and STARS are powerful tools for spatial statistical modeling of stream temperature and other stream characteristics.
The purpose of the Spatial Tools for the Analysis of River Systems (STARS) toolset is to generate and format the data needed to fit spatial statistical models in R software. The STARS toolset makes use of the Landscape Network, a data structure used to efficiently navigate throughout a stream network. Specific tools have been included to 1) pre-process the Landscape Network; 2) calculate the hydrologic distances (with flow-direction preserved), the spatial additive function used to weight converging stream segments, and the covariates for all observed and prediction locations in the stream network; and 3) export the topological, spatial, and attribute information in a format that can be efficiently stored, accessed, and analyzed in R. The site also houses GIS layers and sample data to get you started.

SSN: An R Package for Spatial Statistical Modeling on Stream Networks

The Spatial Stream Network (SSN) package was developed for R statistical software, a powerful open source statistical computing and graphics software. Once streams data have been properly formatted using the STARS toolset, the SSN package allows users to: 1) import and store their spatial data in R; 2) calculate pair-wise distances and spatial weights based on the network topology; 3) fit spatial statistical models to streams data where autocorrelation is based on three spatial relationships (Euclidean, flow-connected, and flow-unconnected); 4) estimate relationships between stream variables (spatial regression); 5) make predictions at unobserved locations (prediction sites); 6) export spatial data for use in other software programs; and 7) visualize the spatial data.


Isaak, Daniel J. ; Peterson, Erin E. ; Ver Hoef, Jay M. ; Wenger, Seth J. ; Falke, Jeffrey A. ; Torgersen, Christian E. ; Sowder, Colin ; Steel, E. Ashley ; Fortin, Marie-Josee ; Jordan, Chris E. ; Ruesch, Aaron S. ; Som, Nicholas ; Monestiez, Pascal. , 2014
Peterson, Erin E. ; Ver Hoef, Jay M. ; Isaak, Daniel J. ; Falke, Jeffrey A. ; Fortin, Marie-Josee ; Jordan, Chris E. ; McNyset, Kristina ; Monestiez, Pascal ; Ruesch, Aaron S. ; Sengupta, Aritra ; Som, Nicholas ; Steel, E. Ashley ; Theobald, David M. ; Torgersen, Christian E. ; Wenger, Seth J. , 2013
Isaak, Daniel J. ; Luce, Charles H. ; Rieman, Bruce E. ; Nagel, David E. ; Peterson, Erin E. ; Horan, Dona ; Payne (Parkes) , Sharon L. ; Chandler, Gwynne L. , 2010



Support for this work was provided by the U.S. Forest Service, the U.S. Geological Survey, and the Oregon State Office of the Bureau of Land Management. Some of this work was conducted as part of the working group entitled “Spatial Statistical Models for Stream Networks," supported by the National Center for Ecological Analysis and Synthesis, a center funded by NSF (Grant #EF-0553768), the University of California, Santa Barbara, and the State of California. This project also received financial support from the Australian CSIRO Water for a Healthy Country Flagship, and the NOAA's National Marine Fisheries Service to the Alaska Fisheries Science Center. Find additional contact information for the STARS and SNN tools here.

Project Contact: 

Principal Investigators:
Erin E. Peterson - Queensland University of Technology
Jay M. Ver Hoef - NOAA National Marine Mammal Laboratory

Sherry P. Wollrab - RMRS Boise