Estimating tree crown size from multiresolution remotely sensed imagery

  • Song C
  • Woodcock C
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Abstract

The spatial arrangement of the brightness values of remotely sensed imagery bears important information for forest canopy structures. This paper presents the theory and a simple analytical model to estimate tree crown size using sills of semi-variograms from images at two spatial resolutions. The theoretical basis for the model is that the spatial patterns of multiresolution imagery are diagnostic of tree size. The sills of variograms from images containing larger trees decrease more slowly than those for images containing smaller trees as the image spatial resolution decreases. Tests with generated images, integrated simulation of stand development and its spatial patterns, and Ikonos images show that the model can provide realistic estimates of tree crown size. Errors of the estimated crown size strongly depend on the spatial resolutions of the images. The best combination of spatial resolutions is at the ratio of pixel size to the object size around unity.

Author-supplied keywords

  • AUTO-CORRELATION
  • CANOPY REFLECTANCE MODEL
  • CLASSIFICATION
  • DIGITAL IMAGES
  • FOREST
  • LANDSAT
  • MANIFESTATION
  • OPTICAL IMAGERY
  • REGULARIZATION
  • SPATIAL-RESOLUTION
  • SUCCESSION

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Authors

  • C Song

  • C E Woodcock

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