Giles M Foody


Ontology type: schema:Person     


Person Info

NAME

Giles M

SURNAME

Foody

Publications in SciGraph latest 50 shown

  • 2016-07 Geographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information in GEOINFORMATICA
  • 2013-06 Satellites: Ambition for forest initiative in NATURE
  • 2013-04 Assessing flash flood hazard in an arid mountainous region in ARABIAN JOURNAL OF GEOSCIENCES
  • 2009 Remote sensing of terrestrial chlorophyll content in GLOBAL CLIMATOLOGY AND ECODYNAMICS
  • 2006-07 What is the difference between two maps? A remote senser’s view in JOURNAL OF GEOGRAPHICAL SYSTEMS
  • 2006 Pattern Recognition and Classification of Remotely Sensed Images by Artificial Neural Networks in ECOLOGICAL INFORMATICS
  • 2004 Sub-Pixel Methods in Remote Sensing in REMOTE SENSING IMAGE ANALYSIS: INCLUDING THE SPATIAL DOMAIN
  • 2002-06 Sharpened Mapping of Tropical Forest Biophysical Properties from Coarse Spatial Resolution Satellite Sensor Data in NEURAL COMPUTING AND APPLICATIONS
  • 2001-11 Thematic mapping from remotely sensed data with neural networks: MLP, RBF and PNN based approaches in JOURNAL OF GEOGRAPHICAL SYSTEMS
  • 2000-12 Mapping Land Cover from Remotely Sensed Data with a Softened Feedforward Neural Network Classification in JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
  • 1999-03 Fuzzy mapping of tropical land cover along an environmental gradient from remotely sensed data with an artificial neural network in JOURNAL OF GEOGRAPHICAL SYSTEMS
  • 1997-12 Fully fuzzy supervised classification of land cover from remotely sensed imagery with an artificial neural network in NEURAL COMPUTING AND APPLICATIONS
  • 1997-08 Mapping tropical forest fractional cover from coarse spatial resolution remote sensing imagery in PLANT ECOLOGY
  • 1997 Land Cover Mapping from Remotely Sensed Data with a Neural Network: Accommodating Fuzziness in NEUROCOMPUTATION IN REMOTE SENSING DATA ANALYSIS
  • 1995-12 Book reviews in GEOJOURNAL
  • 1995-09 Training pattern replication and weighted class allocation in artificial neural network classification in NEURAL COMPUTING AND APPLICATIONS
  • 1995-08 Estimation of land coverage from a land cover classification derived from remotely sensed data in GEOJOURNAL
  • 1995-05 Book reviews in GEOJOURNAL
  • 1995-04 Book reviews in GEOJOURNAL
  • 1993-04 Non-classificatory analysis and representation of heathland vegetation from remotely sensed imagery in GEOJOURNAL
  • JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "affiliation": [
          {
            "affiliation": {
              "id": "https://www.grid.ac/institutes/grid.4563.4", 
              "type": "Organization"
            }, 
            "isCurrent": true, 
            "type": "OrganizationRole"
          }, 
          {
            "id": "https://www.grid.ac/institutes/grid.5491.9", 
            "type": "Organization"
          }
        ], 
        "familyName": "Foody", 
        "givenName": "Giles M", 
        "id": "sg:person.013045461423.16", 
        "identifier": {
          "name": "orcid_id", 
          "type": "PropertyValue", 
          "value": [
            "0000-0001-6464-3054"
          ]
        }, 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013045461423.16", 
          "https://orcid.org/0000-0001-6464-3054"
        ], 
        "sdDataset": "persons", 
        "sdDatePublished": "2019-03-07T14:01", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-researchers-20181010/20181011/dim_researchers/base/researchers_1791.json", 
        "type": "Person"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/person.013045461423.16'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/person.013045461423.16'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/person.013045461423.16'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/person.013045461423.16'


     




    Preview window. Press ESC to close (or click here)


    ...