How to translate text using browser tools
1 August 2007 Monitoring succession from space: A case study from the North Carolina Piedmont
Robert I. McDonald, Patrick N. Halpin, Dean L. Urban
Author Affiliations +

Question: Is the successional transition from pine to hardwood, which has been inferred from chronosequence plots in previous studies, validated through a time line of satellite imagery?

Location: Durham, North Carolina, USA.

Methods: We examined successional trends in a time-series of winter-summer pairs of Thematic Mapper imagery from 1986 to 2000. We calculated the normalized difference of vegetation index (NDVI) for winter and summer, as well as the difference between summer and winter NDVI (i.e., summer increment NDVI). A set of approximately 50 forest stands of known age and phenology were used to interpret patterns in winter and summer increment NDVI over successional time, and a continuum was found to exist between pine-dominance and hardwood-dominance. We fitted a series of linear regressions that modeled the change in winter and summer increment NDVI as a function of initial winter and summer increment NDVI, and additional explanatory variables.

Results: All regressions were highly significant (P < 0.0001, R2 = ca. 0.3). Predicted dynamics are in accord with successional theory, with pixels moving from evergreen dominance to deciduous dominance along a line of fairly constant summer NDVI. A large disturbance event that occurred over the course of this study, Hurricane Fran, appeared to slow rates of succession in the short term (1–3 years), but increase the rate of conversion to hardwoods over longer time spans.

Conclusions: We conclude that temporal sequences of remote sensing images provide an excellent opportunity for broad-scale monitoring of successional processes, and that continuous metrics of that change are essential to accurate monitoring.

Robert I. McDonald, Patrick N. Halpin, and Dean L. Urban "Monitoring succession from space: A case study from the North Carolina Piedmont," Applied Vegetation Science 10(2), 193-203, (1 August 2007).[193:MSFSAC]2.0.CO;2
Received: 2 March 2005; Accepted: 26 June 2006; Published: 1 August 2007

This article is only available to subscribers.
It is not available for individual sale.

Conditional auto-regression
Dark Object Subtraction
Duke Forest
edge effect
loblolly pine
Get copyright permission
Back to Top