Indicator cokriging-based subpixel mapping without prior spatial structure information

Qunming Wang, Peter M. Atkinson, Wen Zhong Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

42 Citations (Scopus)

Abstract

Indicator cokriging (ICK) has been shown to be an effective subpixel mapping (SPM) algorithm. It is noniterative and involves few parameters. The original ICK-based SPM method, however, requires the semivariogram of land cover classes from prior information, usually in the form of fine spatial resolution training images. In reality, training images are not always available, or laborious work is needed to acquire them. This paper aims to seek spatial structure information for ICK when such prior land cover information is not obtainable. Specifically, the fine spatial resolution semivariogram of each class is estimated by the deconvolution process, taking the coarse spatial resolution semivariogram extracted fromthe class proportion image as input. The obtained fine spatial resolution semivariogram is then used to estimate class occurrence probability at each subpixel with the ICK method. Experiments demonstrated the feasibility of the proposed ICK with the deconvolution approach. It obtains comparable SPM accuracy to ICK that requires semivariogram estimated from fine spatial resolution training images. The proposed method extends ICK to cases where the prior spatial structure information is unavailable.
Original languageEnglish
Article number2321834
Pages (from-to)309-323
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume53
Issue number1
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • Indicator cokriging (ICK)
  • Land cover mapping
  • Semivariogram
  • Subpixel mapping (SPM)
  • Super-resolution mapping

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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