Individual tree recognition from multiple high spatial resolution image sources

M. Wulder, Trisalyn Nelson, K. O. Niemann, D. Seemann, D. G. Goodenough, A. Dyk, A. S. Bhogal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The availability of high resolution (1 m or better) imagery from space opens up the possibility of automatic detection of coniferous trees. Our test site is located within the Greater Victoria Watershed (GVWD) on Vancouver Island, British Columbia, Canada. In previous research we have examined various filters for detecting trees over an area with mature and immature Douglas fir trees. We have obtained a 1-m spatial resolution digital orthophoto generated from aerial photography, MEIS 1-m multispectral imagery, and IKONOS panchromatic 1-m imagery over our test site. Within the test site, there are ground plots in which the location of each tree has been determined. These detailed plots are used to assess the accuracy of the methods used for tree detection for each of the high resolution image types. The characteristics of each tree are documented allowing for an assessment of the conditions leading to the identification, or lack of identification, of each tree. The comparison of three differing data sources, each with 1-m spatial resolution, indicates favorable results for the IKONOS satellite data. The highest proportion of the trees from the field stem plot data were identified with the IKONOS satellite panchromatic imagery. While the IKONOS results have a higher rate of false positives than the airborne multispectral data, a preference for the satellite data is due to characteristics such as ease of collection, large image extent, repeatability, and radiometric consistency over a larger area.

Original languageEnglish (US)
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
Pages771-773
Number of pages3
Volume2
StatePublished - 2001
Externally publishedYes
Event2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - Sydney, NSW, Australia
Duration: Jul 9 2001Jul 13 2001

Other

Other2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
CountryAustralia
CitySydney, NSW
Period7/9/017/13/01

Fingerprint

Image resolution
spatial resolution
Satellites
IKONOS
Aerial photography
Satellite imagery
Optical resolving power
Watersheds
imagery
Availability
satellite data
orthophoto
aerial photography
open space
image resolution
coniferous tree
stem
watershed
filter
test

ASJC Scopus subject areas

  • Software
  • Geology

Cite this

Wulder, M., Nelson, T., Niemann, K. O., Seemann, D., Goodenough, D. G., Dyk, A., & Bhogal, A. S. (2001). Individual tree recognition from multiple high spatial resolution image sources. In International Geoscience and Remote Sensing Symposium (IGARSS) (Vol. 2, pp. 771-773)

Individual tree recognition from multiple high spatial resolution image sources. / Wulder, M.; Nelson, Trisalyn; Niemann, K. O.; Seemann, D.; Goodenough, D. G.; Dyk, A.; Bhogal, A. S.

International Geoscience and Remote Sensing Symposium (IGARSS). Vol. 2 2001. p. 771-773.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wulder, M, Nelson, T, Niemann, KO, Seemann, D, Goodenough, DG, Dyk, A & Bhogal, AS 2001, Individual tree recognition from multiple high spatial resolution image sources. in International Geoscience and Remote Sensing Symposium (IGARSS). vol. 2, pp. 771-773, 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001), Sydney, NSW, Australia, 7/9/01.
Wulder M, Nelson T, Niemann KO, Seemann D, Goodenough DG, Dyk A et al. Individual tree recognition from multiple high spatial resolution image sources. In International Geoscience and Remote Sensing Symposium (IGARSS). Vol. 2. 2001. p. 771-773
Wulder, M. ; Nelson, Trisalyn ; Niemann, K. O. ; Seemann, D. ; Goodenough, D. G. ; Dyk, A. ; Bhogal, A. S. / Individual tree recognition from multiple high spatial resolution image sources. International Geoscience and Remote Sensing Symposium (IGARSS). Vol. 2 2001. pp. 771-773
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