Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Introduction to R01:11

Introduction to R

257
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
257
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

27
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
27
Statgraphics01:10

Statgraphics

119
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
119
Statistical Package for the Social Sciences (SPSS)01:22

Statistical Package for the Social Sciences (SPSS)

296
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
296
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

141
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
141
Introduction to GIS01:28

Introduction to GIS

60
Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
60

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Missing data in ecology: Syntheses, clarifications, and considerations.

Ecological monographs·2026
Same author

National Aquatic Resource Surveys (NARS): the foundation for long-term aquatic monitoring data across the United States.

Environmental monitoring and assessment·2025
Same author

Diverging fish biodiversity trends in cold and warm rivers and streams.

Nature·2025
Same author

Global wood fuel production estimates and implications.

Nature communications·2025
Same author

Non-Floodplain Wetlands Are Carbon-Storage Powerhouses Across the United States.

Earth's future·2025
Same author

Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system.

Transactions of the American Fisheries Society·2025

Related Experiment Video

Updated: Jun 15, 2025

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

5.8K

SSN2: The next generation of spatial stream network modeling in R.

Michael Dumelle1, Erin E Peterson2, Jay M Ver Hoef3

  • 1Pacific Ecological Systems Division, United States Environmental Protection Agency, Corvallis, OR, USA.

Journal of Open Source Software
|August 28, 2024
PubMed
Summary

The SSN2 R package offers advanced spatial statistical modeling for river networks. It succeeds the original SSN R package, incorporating modern R-spatial tools for improved functionality.

More Related Videos

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:49

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

120
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.0K

Related Experiment Videos

Last Updated: Jun 15, 2025

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

5.8K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:49

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

120
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.0K

Area of Science:

  • Spatial statistics
  • Environmental modeling
  • Geospatial analysis

Background:

  • The original SSN R package is archived due to changes in the R-spatial ecosystem.
  • Key R-spatial packages like rgdal, rgeos, and maptools have been retired.
  • The lack of active development in the sp package necessitated an update.

Purpose of the Study:

  • Introduce SSN2, a successor R package for spatial statistical modeling on stream networks.
  • Provide tools for parameter estimation and prediction within riverine systems.
  • Leverage modern R-spatial tools for enhanced geospatial analysis.

Main Methods:

  • Utilizes the sf package for modern geospatial data handling.
  • Maintains compatibility with existing SSN R package data structures.
  • Implements new modeling functions, helper functions, and enhanced fitting algorithms.

Main Results:

  • SSN2 offers simplified syntax consistent with other R generic functions.
  • Introduces new functionalities not present in the previous SSN R package.
  • Facilitates robust spatial statistical modeling on stream networks.

Conclusions:

  • SSN2 is a powerful, updated tool for spatial statistical modeling on river networks.
  • It integrates seamlessly with the current R-spatial ecosystem.
  • The package enhances capabilities for environmental and geospatial analysis.