Land-use mapping in a mixed urban-agricultural arid landscape using object-based image analysis: A case study from Maricopa, Arizona

Christopher S. Galletti, Soe Myint

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Land-use mapping is critical for global change research. In Central Arizona, U.S.A., the spatial distribution of land use is important for sustainable land management decisions. The objective of this study was to create a land-use map that serves as a model for the city of Maricopa, an expanding urban region in the Sun Corridor of Arizona. We use object-based image analysis to map six land-use types from ASTER imagery, and then compare this with two per-pixel classifications. Our results show that a single segmentation, combined with intermediary classifications and merging, morphing, and growing image-objects, can lead to an accurate land-use map that is capable of utilizing both spatial and spectral information. We also employ a moving-window diversity assessment to help with analysis and improve post-classification modifications.

Original languageEnglish (US)
Pages (from-to)6089-6110
Number of pages22
JournalRemote Sensing
Volume6
Issue number7
DOIs
StatePublished - 2014

Keywords

  • ASTER
  • Agriculture
  • Arid
  • Dryland
  • Object-based image analysis (OBIA)
  • Segmentation
  • Urban
  • land use

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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