- Agricultural-Biological Sciences
- Arts & Humanities
- Biochemistry, Genetics, Molecular Biology
- Business Management Accounting
- Chemical Engineering
- Chemistry
- Computer Science
- Decision Sciences
- Earth & Planetary Sciences
- Economics, Econometrics, Finance
- Energy
- Engineering
- Environmental Science
- Immunology & Microbiology
- Materials Science
- Mathematics
- Medicine
- Neuroscience
- Nursing
- Pharmacology. Toxicology. Pharmaceutics.
- Physics and Astronomy
- Psychology
- Social Sciences
- Veterinary
- Dentistry
- Health Professions
- Sports Science
- Military & Naval Sciences
- Multidisciplinary
- Call for Papers
Spatial Statistics
Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies without methodological development are not acceptable for publication.
Spatial statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of dependence structures, and drawing of valid inference from a limited set of spatio-temporal data. Application fields include
The physical domains, e.g. agriculture, geology, soil science, hydrology, ecology, mining, oceanography, forestry, air quality, remote sensing
The social/economic domains, e.g. spatial econometrics, epidemiology and disease mapping.