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SUMMARY:Spatial-Stream-Network (SSN) Model Training Workshop
DESCRIPTION:Spatial-Stream-Network (SSN) Model Training Workshop\nAGENDA\nDay 1: Overview of spatial statistical network models: theory\, software\, and applications\nDays 2 & 3: Work 1-on-1 with instructors to apply the spatial models to your datasets \nCOST $700 (students)\n$1\,000 (professionals) \nDATES Oct 14–16\, 2026 \nTIME 8:30 – 5:00 \nLOCATION Idaho Water Center\n322 E Front Street\nBoise\, Idaho \nCourse Instructors\nDr. Erin Peterson (QUT)\nDr. Mike Dumelle (EPA)\nDr. Jay Ver Hoef (NOAA)\nDr. Dan Isaak (USFS) \nFREE SOFTWARE PACKAGES\nSSNbler GIS toolset: An Introduction to ‘SSNbler’: Assembling Spatial Stream Network (`SSN`) Objects in R • SSNbler \nSSN2 package for the R statistical software: CRAN: Package SSN2 \nSpatial statistical stream-network (SSN) models are a new type of model based on covariance structures that account for flow direction\, flow volume\, and the branching structure of stream networks to provide a valid means of interpolating predictions between sample locations. SSNs are 0useful for describing spatial patterns in common stream attributes (e.g.\, water quality\, habitat conditions\, biological surveys) and often outperform traditional analytical techniques applied to stream data. SSNs also provide parameter estimates for covariate fixed effects and can be used to describe the spatial autocorrelation structure (i.e.\, non-independence) among measurements\, which has utility for designing efficient monitoring strategies and spatial surveys. \n\nShare free user-friendly software tools for SSN analysis:\n\nSSNbler package for processing spatial data sets using GIS\nand the R statistical software\nSSN2 package for analysis in the R statistical software\n\n\nIntroduction to the new R packages\, SSNbler and SSN2\, including\nnew data structures and functionality\nDemonstrate the data processing steps used to calculate the spatial\ninformation for fitting SSN models in R\nDemonstrate how SSN2 is used for:\n\nExploratory data analysis\nModeling continuous\, presence/absence\, and count data\nusing spatial linear\, mixed-effects\, and generalized models\nModel diagnostics and selection\nPrediction (geostatistical kriging)\nUncertainty estimation\nSimulation and spatial visualization techniques for stream\ndata using ggplot2\n\n\n\nREQUIREMENTS A good working knowledge of statistics and the R statistical program are useful to obtain the greatest benefit from the workshop. Participants must bring a laptop with access to the R statistical software and a GIS of your choice (Recommended: ArcGIS Pro with standard or advanced license or QGIS software). Please contact the organizers if you cannot meet these requirements. \nIf you have questions about course enrollment\, email: disaak67@gmail.com and support@spatialstreamnetworks.com
URL:https://pnamp.org/event/spatial-stream-network-ssn-model-training-workshop/
CATEGORIES:Non-PNAMP Event
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