Affordable Access

Publisher Website

Forecasting the susceptibility and vulnerability of balsam fir stands to insect defoliation with Landsat Thematic Mapper data

Remote Sensing of Environment
Publication Date
DOI: 10.1016/s0034-4257(96)00108-3
  • Physics


Abstract The potential of remote sensing to aid in the forecast of insect defoliation and the associated impact on forest stands was tested by examining the relationships between i) preoutbreak forest structure and growth characteristics, ii) multispectral values recorded by the Landsat Thematic Mapper (TM) sensor, and iii) subsequent patterns of defoliation and volume loss in the balsam fir ( Abies balsamea L. Mill) forests of Western Newfoundland. Forest structure and growth characteristics were measured in the field in 1992–1993 and reconstructed to represent conditions 3 years prior to an infestation of black-headed budworm, Acleris variana (Fern.), which began in 1988. Preoutbreak Landsat TM data were acquired on 8 August 1985. Spectral values were converted to approximate reflectances using PCI atmospheric correction routines and related to the field measurements. Logistic regression techniques were used to develop models for predicting forest susceptibility (probability of attack) and vulnerability (response to attack) and to assess the accuracy of the susceptibility and vulnerability forecasts. In general, susceptible stands were younger and had lower basal area and tree density, but higher leaf area index than stands that were not attacked. Vulnerable stands were older, had lower vigor and growth efficiency indices (stemwood growth per unit of leaf area), and also displayed the highest near infrared spectral values. The best predictions combined selected spectral measurements with provincial forest inventory data. These models produced classifications with accuracies of 81%, 67%, and 78% for predicting susceptibility and pre- and postoutbreak vulnerability, respectively.

There are no comments yet on this publication. Be the first to share your thoughts.