Spatial Statistics Methods and Modeling

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".

Deadline for manuscript submissions: 20 March 2025 | Viewed by 71

Special Issue Editor


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Guest Editor
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands
Interests: spatial (bio) statistics; spatial epidemiology; air quality mapping; spatial biostatistics
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Special Issue Information

Dear Colleagues,

With the advent of Global Positioning System (GPS) technology and Geographic Information Science (GIS), spatial data are increasingly becoming easy to collect, store, and analyze. Spatial data may be observations of the locations of event occurrences (point processes), observations of aggregated quantities over a set of contiguous areas (lattice processes), or observations of quantities over a set of locations (geostatistical processes). Today, spatial data have rapidly become abundant in precision public health and disease modeling, environmental science monitoring, precision agriculture, and diverse other domains. The modeling of these spatial data processes presents unique perspectives about how inferences about the phenomenon under study can be drawn. This Special Issue aims to bring to studies that apply, innovate, or extend existing spatial modeling methods in public health, environmental science, agriculture, etc. We shall consider manuscripts that present innovative solutions to application and methodological challenges to solve real societal problems.

Dr. Frank Badu Osei
Guest Editor

Manuscript Submission Information

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Keywords

  • spatial statistics
  • spatial modeling
  • geostatistics
  • Markov random field
  • Gaussian Markov random field
  • conditional autoregressive
  • point processes
  • log Gaussian Cox process

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Published Papers

This special issue is now open for submission.
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