Computerized classification of Mediterranean vegetation using panchromatic aerial photographs

Yohay Carmel*, Ronen Kadmon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Historical aerial photographs are an important source for data on medium- to long-term (10 - 50 yr) vegetation changes. Older photographs are panchromatic, and manual interpretation has traditionally been used to derive vegetation data from such photographs. We present a method for computerized analysis of panchromatic aerial photographs, which enables one to create high resolution, accurate vegetation maps. Our approach is exemplified using two aerial photographs (from 1964 and 1992) of a test area on Mt. Meron, Israel. Spatial resolution (pixel size) of the geo-rectified photos was 0.30 m and spatial accuracy (RMS error) ca. 1 m. An illumination adjustment prior to classification was found to be essential in reducing misclassification error rates. Two classification approaches were employed: a standard maximum-likelihood supervised classifier, and a modification of a supervised classification, which takes into account spectral properties of individual pixels as well as their neighborhood characteristics. Accuracy of the maximum likelihood classification was 81 % in the 1992 image and 54 % in the 1964 image. The neighbor classifier increased accuracy to 89 % and 82 % respectively. The overall results suggest that computerized analysis of sequences of panchromatic aerial photographs may serve as a valuable tool for the quantification of medium-term vegetation changes.

Original languageAmerican English
Pages (from-to)445-454
Number of pages10
JournalJournal of Vegetation Science
Volume9
Issue number3
DOIs
StatePublished - Jun 1998

Keywords

  • GIS
  • Image analysis
  • Neighbor classifier
  • Remote sensing
  • Vegetation dynamics

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