Spatial statistical techniques for aggregating point objects extracted from high spatial resolution remotely sensed imagery

Trisalyn Nelson, K. Olaf Niemann, Michael A. Wulder

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Using a local maximum filter, individual trees were extracted from a 1 m spatial resolution IKONOS image and represented as points. The spatial pattern of individual trees was determined to represent forest age (a surrogate for forest structure). Point attributes, based on the spatial pattern of trees, were generated via nearest neighbour statistics and used as the basis for aggregating points into forest structure units. The forest structure units allowed for the mapping of a forested area into one of three age categories: young (1-20 years), intermediate (21-120 years), and mature (>120 years). This research indicates a new approach to image processing, where objects generated from the processing of image data (rather than pixels or spectral values) are subjected to spatial statistical analysis to estimate an attribute relating an aspect of forest structure.

Original languageEnglish (US)
Pages (from-to)423-433
Number of pages11
JournalJournal of Geographical Systems
Volume4
Issue number4
DOIs
StatePublished - Dec 2002

Keywords

  • Aggregation
  • Feature extraction
  • Generalisation
  • Nearest neighbour statistics

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes

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