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: Automating the Analysis of Spatial Grids
    sub title: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications
  name:
    name part: Lakshmanan, Valliappa.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: ne
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 320 p. 136 illus. in color. online resource.
  abstract: The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery.
  table of contents: Automated Analysis of Spatial Grids: Motivation and Challenges -- -Geographic Information Systems -- -GIS Operations -- -Need for Automation -- -Spatial Grids -- -Challenges in Automated Analysis -- -Spatial Data Mining Algorithms -- Geospatial grids -- -Representation -- -Linearity of data values -- -Instrument geometry -- -Gridding point observations -- -Rasterization -- -Example Applications -- Data Structures for Spatial Grids -- -Array -- -Pixels -- -Level set -- -Topographical surface -- -Markov chain -- -Matrix -- -Parametric approximation -- -Relational structure -- -Applications -- Global and Local Image Statistics -- -Types of statistics -- -Distances -- -Distance transform -- -Probability Functions -- -Local measures -- -Example Applications -- Neighborhood and Window Operations -- -Preprocessing -- -Window operations -- -Median filter -- -Morphological operations -- -Skeletonization -- -Frequency Domain Convolution -- -Example Applications -- Identifying Objects -- -Object identification -- -Region growing -- -Region properties -- -Hysteresis -- -Active contours -- -Watershed Transform -- -Enhanced watershed -- -Contiguity-enhanced Clustering -- -Choosing an object-identification technique -- -Example Applications -- Change and Motion Estimation -- -Estimating change -- -Optical Flow -- -Object-tracking -- -Choosing a change or motion estimation technique -- -Example Applications -- Data Mining Attributes from Spatial Grids -- -Data Mining -- -A Fuzzy Logic Application -- -Supervised learning models -- -Clustering -- -Example Applications.
  note: by Valliappa Lakshmanan.
  subject:
    topic: Earth sciences
  subject:
    topic: Geotechnical engineering
  subject:
    topic: Data mining
  subject:
    topic: Geographical information systems
  subject:
    topic: Earth Sciences
  subject:
    topic: Geotechnical Engineering & Applied Earth Sciences
  subject:
    topic: Geographical Information Systems/Cartography
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Earth Sciences, general
  classification: TA703-705.4
  classification: 624.151
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Geotechnologies and the Environment ; 6
  identifier: 9789400740754
  identifier: http://dx.doi.org/10.1007/978-94-007-4075-4
  record info:
    record creation date: 120613
    record change date: 20151031121054.0
    record identifier: 978-94-007-4075-4