Exploring small footprint lidar intensity data in a forested environment

Jaden Langford, Olaf Niemann, Gordon W. Frazer, Michael A. Wulder, Trisalyn Nelson

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

8 Scopus citations

Abstract

Lidar intensity, a quantity analogous to backscatter, has yet to be fully exploited as an information source in the characterization of forests. Intensity images appear noisy due to complex laser interactions in a forested environment; however, we expect that these data are inherently spatially structured. We found that (1) the scale and variability of global estimates of spatial autocorrelation derived from raw intensity data were markedly different between stands of different age, and (2) the magnitude of local estimates of spatial autocorrelation varied with canopy height. We believe that these height and age-related differences in intensity are due to both structural and compositional features unique to each stand.

Original languageEnglish (US)
Title of host publication2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Pages2416-2419
Number of pages4
DOIs
StatePublished - Dec 1 2006
Externally publishedYes
Event2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States
Duration: Jul 31 2006Aug 4 2006

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
CountryUnited States
CityDenver, CO
Period7/31/068/4/06

Keywords

  • Forest structure
  • Lidar intensity
  • Spatial autocorrelation

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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  • Cite this

    Langford, J., Niemann, O., Frazer, G. W., Wulder, M. A., & Nelson, T. (2006). Exploring small footprint lidar intensity data in a forested environment. In 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS (pp. 2416-2419). [4241774] (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2006.626