Remote sensing of spruce budworm defoliation using EO-1 Hyperion hyperspectral data: An example in Quebec, Canada

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Abstract

Each year, the spruce budworm (SBW) causes severe, widespread damage to spruces and fir in east coast Canada. Early estimation of the defoliation can provide crucial support to mitigate the socio-economic impact on vulnerable forests. Remote sensing techniques are suitable to investigate the affected regions that usually consist of large and inaccessible forestry areas. Using satellite images, surface reflectance values at two or more wavelengths are combined to generate vegetation indices (VIs), revealing a relative abundance of features of interest. Forest health analysis based on VIs is considered as one of the primary information sources for monitoring vegetation conditions. Especially the spectral resolution of Hyperion hyperspectral satellite imagery used in this study allows for a detailed examination of the red to near-infrared portion of the spectrum to identify areas of stressed vegetation. Several narrow-band vegetation indices are used to indicate the overall amount and quality of photosynthetic material and moisture content in vegetation. By integrating the information from VIs that focus on different aspects of overall health and vigour in forested areas, the study aims at detecting defoliated condition in a forested region in the Province of Quebec, Canada. In June and August of 2014 two Hyperion images were acquired by NASA's EO-1 satellite for this study. Changes in vegetation health and vigour are observed and quantitatively compared using the multi-temporal remote sensing images. The experimental results suggest that the VI- based forest health analysis is effective in estimating SBW defoliation in the study area.

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CITATION STYLE

APA

Huang, Z., & Zhang, Y. (2016). Remote sensing of spruce budworm defoliation using EO-1 Hyperion hyperspectral data: An example in Quebec, Canada. In IOP Conference Series: Earth and Environmental Science (Vol. 34). Institute of Physics Publishing. https://doi.org/10.1088/1755-1315/34/1/012017

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