APPLYING MACHINE LEARNING METHODS AND TIME SERIES ANALYSIS TO CREATE A NATIONAL DYNAMIC LAND COVER DATASET FOR AUSTRALIA  


Authors / CoAuthors

Tan, P. | Lymburner, L. | Mueller, N. | Li, F. | Thankappan, M. | Lewis, A.

Abstract

The National Dynamic Land Cover Dataset (DLCD) classifies Australian land cover into 34 categories, which conform to 2007 International Standards Organisation (ISO) Land Cover Standard (19144-2). The DLCD has been developed by Geoscience Australia and the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES), aiming to provide nationally consistent land cover information to federal and state governments and general public. This paper describes the modeling procedure to generate the DLCD, including machine learning methodologies and time series analysis techniques involved in the process.

Product Type

nonGeographicDataset

eCat Id

76272

Contact for the resource

  Custodian

EGD  

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Commonwealth of Australia (Geoscience Australia)  
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia

Keywords

  • External PublicationConference Paper
Australian and New Zealand Standard Research Classification (ANZSRC)
  • Earth Sciences
  • Published_Internal

Publication Date

2013-01-01T00:00:00

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Australian Government Security ClassificationSystem    

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Creative Commons Attribution 4.0 International Licence    

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Use - license

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geoscientificInformation

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