Articles | Book Reviews | Special Volumes |
A Mouse Model For Studying Fire Spread Rates Using Experimental Micro-fires Vol. 9, Issue 6, May 2020 Submitted 2018-11-01, Accepted 2020-05-14 | John R. J. Thompson, Xi J. Wang, W. John Braun |
Frailty Models for the Control Time of Wildland Fires in the Former Intensive Fire Management Zone of Ontario, Canada Vol. 9, Issue 5, Sep 2019 Submitted 2019-05-01, Accepted 2019-09-15 | Amy A. Morin, Alisha Albert-Green, Douglas G. Woolford, David L. Martell |
Statistical Surveillance Thresholds for Enhanced Situational Awareness of Spring Wildland Fire Activity in Alberta, Canada Vol. 9, Issue 4, Sep 2019 Submitted 2018-10-31, Accepted 2019-09-15 | Cordy Tymstra, Douglas G. Woolford, Mike D. Flannigan |
Spatial Semi-parametric Spectral Density Estimation for Multivariate Extremes, with Application to Fire Threat Vol. 9, Issue 3, Sep 2019 Submitted 2018-10-31, Accepted 2019-09-15 | Mauricio Nascimento, Benjamin A. Shaby |
Area Interaction Point Processes for Bivariate Point Patterns in a Bayesian Context Vol. 9, Issue 2, Sep 2019 Submitted 2017-08-17, Accepted 2019-09-15 | Glenna F. Nightingale, Janine Bärbel Illian, Ruth King, Peter Nightingale |
Visualizing Multivariate Time Series of Aerial Fire Fighting Data Vol. 9, Issue 1, Sep 2019 Submitted 2018-11-14, Accepted 2019-09-15 | Devan G. Becker, W. John Braun, Charmaine B. Dean, Douglas G. Woolford |
Modeling of Dengue Fever Death Counts Using Hidden Markov Model Vol. 8, Issue 9, Sep 2018 Submitted 2018-04-18, Accepted 2018-09-07 | Joshni George, Seemon Thomas |
Practical Geostatistics Case Studies 2009 Vol. 1, Book Review 1, Feb 2010 Submitted 2009-12-12, Accepted 2009-12-12 | Reviewed by David Zes |
Volume 9: Statistical Analysis of Wildfire Data |
Volume 8: Novel or Unusual Ideas in Environmental Statistics |
Volume 4: TIES2012 |
As of 2018, the Journal of Environmental Statistics no longer accepts ordinary submissions; we only accept submissions targeted for specific special issues. The Journal of Environmental Statistics' purpose is to contribute to the development of statistical techniques aimed at addressing questions related to environmental data. In particular, we encourage papers devoted to the development of computational methods and models for spatial and spatial-temporal data, especially point process and geostatistical data. Of special interest also is the incorporation of geographic information systems software. Important areas of application include environmental disturbances such as earthquakes, wildfires, hurricanes, and volcanic eruptions, as well as problems relating to air pollution, climate change, water quality, mining, oceanography, geology, and meteorology. Emphasis is on applied statistics and it is expected that published papers will be of practical use for researchers working in the environmental sciences.
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