rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Learning R for Geospatial Analysis
  name:
    name part: Dorman, Michael
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2014
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (364 pages)
  abstract: Leverage the power of R to elegantly manage crucial geospatial analysis tasks In Detail R is a simple, effective, and comprehensive programming language and environment that is gaining ever-increasing popularity among data analysts. This book provides you with the necessary skills to successfully carry out complete geospatial data analyses, from data import to presentation of results. Learning R for Geospatial Analysis is composed of step-by-step tutorials, starting with the language basics before proceeding to cover the main GIS operations and data types. Visualization of spatial data is vital either during the various analysis steps and/or as the final product, and this book shows you how to get the most out of R's visualization capabilities. The book culminates with examples of cutting-edge applications utilizing R's strengths as a statistical and graphical tool. What You Will Learn Make inferences from tables by joining, reshaping, and aggregating Familiarize yourself with the R geospatial data analysis ecosystem Prepare reproducible, publication-quality plots and maps Efficiently process numeric data, characters, and dates Reshape tabular data into the necessary form for the specific task at hand Write R scripts to automate the handling of raster and vector spatial layers Process elevation rasters and time series visualizations of satellite images Perform GIS operations such as overlays and spatial queries between layers Spatially interpolate meteorological data to produce climate maps
  note: Dorman, Michael.
  note: Electronic resource.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
  note: Mode of access: World Wide Web.
  identifier: 9781783984367
  identifier: 9781783984374
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 291214
    record change date: 20260128184904.5
    record identifier: in00004251325