Detecting wind disturbance severity and canopy heterogeneity in boreal forest by coupling high-spatial resolution satellite imagery and field data

Published Date

15 February 2010, Vol.114(2):299–308, doi:10.1016/j.rse.2009.09.005

Title 

Detecting wind disturbance severity and canopy heterogeneity in boreal forest by coupling high-spatial resolution satellite imagery and field data

• Author 

• Roy. L. Rich ^b,,
• Lee Frelich ^a
• Peter B. Reich ^a
• Marvin E. Bauer ^a

• aDepartment of Forest Resources University of Minnesota, United States
• bEnvironmental Science Institute, The University of Texas at Austin, 1 University Station C9000, Austin TX, 78712, United States

Received 23 May 2006. Revised 3 September 2009. Accepted 13 September 2009. Available online 17 November 2009.

Abstract 

Wind disturbance events can impact spatially heterogeneous patterns in vegetation structure and disturbance severity in forested landscapes. Characterizing these patterns in forested ecosystems with remote sensing data has been a persistent challenge as variation in severity may be heterogeneous at fine spatial scales. Yet the degree and pattern of disturbance severity are an important influence on successional dynamics. This study explored how spectral and textural characteristics of high-spatial resolution IKONOS imagery reflected patterns of disturbance severity across a windstorm damaged, 121-km² area of the Boundary Waters Canoe Area Wilderness (BWCAW) in northeastern Minnesota, USA. In this study, spectral and spatial features of high-spatial resolution (1-m panchromatic and 4-m multispectral) IKONOS satellite imagery from a single post-disturbance date are coupled with field observations of disturbance within 0.045-ha field plots to access the potential for empirically modeling disturbance severity across this heterogeneous landscape within the BWCAW. Combining textural and spectral features led to a multiple regression model that explained 68% of the variance, and predicted disturbance severity equally well for ground data not included in the model development. The results suggest the utility of combining spatial and spectral data for detecting differences in forest structure caused by ecological processes such as disturbance.

Keywords 

Boundary Waters Canoe Area Wilderness (BWCAW)

Boreal forest

Image texture

IKONOS

Spatial hetereogeneity

Wind disturbance

Remote sensing

Disturbance severity

---

Fig. 1.

Fig. 2.

 Table 1

Table 1.

 Table 2

Table 2.

Fig. 3.

 Table 3

Table 3.

Fig. 4.

Fig. 5.

Fig. 6.

• ⁎ 
  Corresponding author. 1530 Cleveland Avenue North St Paul, MN 55113. Tel.: +1 612 624 3277.

For further details log on website :
http://www.sciencedirect.com/science/article/pii/S0034425709002776