Geographic Data Science with R - Wimberly, Michael C. (The University of Oklahoma, USA)
114,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
payback
57 °P sammeln
  • Gebundenes Buch

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.

Andere Kunden interessierten sich auch für
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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.