Tree cover discrimination in panchromatic aerial imagery of pinyon-juniper woodlands

Jesse Jacob Anderson, Neil S Cobb

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Responding to an increasing interest in studying vegetation changes over time, we review current methods of processing black and white digital aerial photographs in order to classify tree cover in pinyon-juniper woodlands. Besides applying commonly used clustering and supervised maximum-likelihood methods, we have developed a new classifier, nearest edge thresholding, which is unsupervised and based on the principals of edge detection and density slicing. Comparison of the three methods' abilities to predict field values at plot scales of 100 m2 to 900 m2 shows this new method is better or comparable to others at all scales, can be easily applied to digital imagery, and has high correspondence with ground-truthed field values of tree cover.

Original languageEnglish (US)
Pages (from-to)1063-1068
Number of pages6
JournalPhotogrammetric Engineering and Remote Sensing
Volume70
Issue number9
StatePublished - Sep 2004

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Edge detection
Maximum likelihood
woodland
Classifiers
imagery
Antennas
Processing
aerial photograph
method
vegetation

ASJC Scopus subject areas

  • Earth and Planetary Sciences (miscellaneous)
  • Computers in Earth Sciences

Cite this

Tree cover discrimination in panchromatic aerial imagery of pinyon-juniper woodlands. / Anderson, Jesse Jacob; Cobb, Neil S.

In: Photogrammetric Engineering and Remote Sensing, Vol. 70, No. 9, 09.2004, p. 1063-1068.

Research output: Contribution to journalArticle

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