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STARS: An ArcGIS Toolset Used to Calculate the Spatial Information Needed to Fit Spatial Statistical Models to Stream Network Data

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  • Peterson, Erin
  • Ver Hoef, Jay

Abstract

This paper describes the STARS ArcGIS geoprocessing toolset, which is used to calcu- late the spatial information needed to fit spatial statistical models to stream network data using the SSN package. The STARS toolset is designed for use with a landscape network (LSN), which is a topological data model produced by the FLoWS ArcGIS geoprocessing toolset. An overview of the FLoWS LSN structure and a few particularly useful tools is also provided so that users will have a clear understanding of the underlying data struc- ture that the STARS toolset depends on. This document may be used as an introduction to new users. The methods used to calculate the spatial information and format the final .ssn object are also explicitly described so that users may create their own .ssn object using other data models and software.

Suggested Citation

  • Peterson, Erin & Ver Hoef, Jay, 2014. "STARS: An ArcGIS Toolset Used to Calculate the Spatial Information Needed to Fit Spatial Statistical Models to Stream Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i02).
    • Handle: RePEc:jss:jstsof:v:056:i02
    DOI: http://hdl.handle.net/10.18637/jss.v056.i02
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    References listed on IDEAS

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    1. Ver Hoef, Jay & Peterson, Erin & Clifford, David & Shah, Rohan, 2014. "SSN: An R Package for Spatial Statistical Modeling on Stream Networks," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i03).
    2. Ver Hoef, Jay M. & Peterson, Erin E., 2010. "A Moving Average Approach for Spatial Statistical Models of Stream Networks," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 6-18.
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    Citations

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    Cited by:

    1. Yirigui Yirigui & Sang-Woo Lee & A. Pouyan Nejadhashemi & Matthew R. Herman & Jong-Won Lee, 2019. "Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    2. Ying Man & Fangwen Zhou & Baoshan Cui, 2023. "Process–Based Identification of Key Tidal Creeks Influenced by Reclamation Activities," Sustainability, MDPI, vol. 15(10), pages 1-11, May.
    3. Lisa Holsinger & Robert Keane & Daniel Isaak & Lisa Eby & Michael Young, 2014. "Relative effects of climate change and wildfires on stream temperatures: a simulation modeling approach in a Rocky Mountain watershed," Climatic Change, Springer, vol. 124(1), pages 191-206, May.
    4. Ver Hoef, Jay & Peterson, Erin & Clifford, David & Shah, Rohan, 2014. "SSN: An R Package for Spatial Statistical Modeling on Stream Networks," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i03).
    5. Jhorland Ayala‐García & Sandy Dall'Erba, 2022. "The impact of preemptive investment on natural disasters," Papers in Regional Science, Wiley Blackwell, vol. 101(5), pages 1087-1103, October.
    6. Eric W Fox & Jay M Ver Hoef & Anthony R Olsen, 2020. "Comparing spatial regression to random forests for large environmental data sets," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-22, March.
    7. Jhorland Ayala-García & Sandy Dall’Erba, 2021. "The impact of preemptive investment on natural disasters," Documentos de trabajo sobre Economía Regional y Urbana 301, Banco de la Republica de Colombia.
    8. Santos-Fernandez, Edgar & Ver Hoef, Jay M. & Peterson, Erin E. & McGree, James & Isaak, Daniel J. & Mengersen, Kerrie, 2022. "Bayesian spatio-temporal models for stream networks," Computational Statistics & Data Analysis, Elsevier, vol. 170(C).
    9. Stefano Salata & Taygun Uzelli, 2024. "The Uncertain Certainty of a Nightmare: What If Another Destructive Earthquake Strikes Izmir (Türkiye)?," Sustainability, MDPI, vol. 16(2), pages 1-26, January.
    10. Tsung-Ta David Hsu & Danlin Yu & Meiyin Wu, 2023. "Predicting Fecal Indicator Bacteria Using Spatial Stream Network Models in A Mixed-Land-Use Suburban Watershed in New Jersey, USA," IJERPH, MDPI, vol. 20(6), pages 1-17, March.
    11. Pebesma, Edzer & Bivand, Roger & Ribeiro, Paulo Justiniano, 2015. "Software for Spatial Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i01).

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