Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

Xiaoxiao Li, Soe Myint, Yujia Zhang, Chritopher Galletti, Xiaoxiang Zhang, Billie Turner

Research output: Contribution to journalArticlepeer-review

70 Scopus citations


Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

Original languageEnglish (US)
Pages (from-to)321-330
Number of pages10
JournalInternational Journal of Applied Earth Observation and Geoinformation
Issue number1
StatePublished - 2014


  • Aerial photography
  • Classification system
  • Land cover
  • Object-based image analysis
  • Phoenix
  • Urban

ASJC Scopus subject areas

  • Global and Planetary Change
  • Earth-Surface Processes
  • Computers in Earth Sciences
  • Management, Monitoring, Policy and Law


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