Michael C. Wimberly

Geographic Data Science with R (eBook, ePUB)

Visualizing and Analyzing Environmental Change

• Format: ePub

Produktbeschreibung

There is a lack of books on the broader topic of scientific workflows for geospatial data processing and analysis. This book aims to fill this gap by providing a series of tutorials aimed at teaching good practices for using geospatial data to address problems in environmental geography.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 310
• Erscheinungstermin: 8. Mai 2023
• Englisch
• ISBN-13: 9781000868753
• Artikelnr.: 67455220

Autorenporträt

Dr. Michael Wimberly is a Professor in the Department of Geography and Environmental Sustainability at the University of Oklahoma. He previously served on the faculties of the University of Georgia and South Dakota State University. He holds a Ph.D. from Oregon State University, an M.S. from the University of Washington, and a B.A. from the University of Virginia. Dr. Wimberly has taught graduate and undergraduate courses in Geographic Information Science (GIS), Spatial Statistics, and Landscape Ecology. He has worked with the R language and software environment throughout his academic career after being introduced to its predecessors, S and S+, in graduate school. His research combines ecological models with data from Earth-observing satellites to address scientific questions and create practical applications in the fields of public health and natural resource management. Areas of study include the effects of land use and climate on vector-borne disease transmission, wildfire and vegetation dynamics in temperate and tropical forest ecosystems, and the causes and consequences of agricultural expansion into native forests and grasslands.

Inhaltsangabe

1. Introduction to R 2. Graphics with ggplot2 3. Processing Tabular Data 4.
Dates in R 5. Vector Geospatial Data 6. Raster Geospatial Data - Continuous
7. Raster Geospatial Data - Discrete 8. Coordinate Reference Systems 9.
Combining Vector Data with Continuous Raster Data 10. Combining Vector Data
with Discrete Raster Data 11. Application - Wildfire Severity Analysis 12.
Species Distribution Modeling Appendix