4.4 Article

Dieback classification modelling using high-resolution digital multispectral imagery and in situ assessments of crown condition

Journal

REMOTE SENSING LETTERS
Volume 3, Issue 6, Pages 541-550

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/01431161.2011.639400

Keywords

-

Funding

  1. Murdoch University
  2. Centre of Excellence for Climate Change Woodland and Forest Health
  3. iVEC
  4. SpecTerra Services Pty Ltd

Ask authors/readers for more resources

Quantifying dieback in forests is useful for land managers and decision makers seeking to explain spatial disturbances and understand the cyclic nature of forest health. Crown condition is assessed as reference to dieback in terms of the density, transparency, extent and in-crown distribution of foliage. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 Eucalyptus gomphocephala crowns were assessed both in situ (2008) and using two acquisitions (2008 and 2010) of airborne imagery. Each tree was assessed using four crown-condition indices: Crown Density, Foliage Transparency, the Crown Dieback Ratio and Epicormic Index combined into a single index called the Total Crown Health Index (TCHI). The airborne imagery is like value calibrated then classified and modelled using in situ canopy condition assessments resulting in a quantification of crown-condition change over time. Comparison of Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI) and a novel Red-Edge Extrema Index (REEI) suggests that the latter is more suited to classification applications of this type.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available