Evaluating the use of remotely sensed data in matrix population modeling for eastern hemlock ( Tsuga canadensis L.)

Abstract

Matrix population models for a population of eastern hemlock ( Tsuga canadensis L.) were constructed from population data collected on the ground using traditional field methods and analogous data extracted from low elevation aerial imagery. This aerial derived data was obtained using spectral and spatial segmentation and reconciliation procedures that segmented hemlock “blobs” from the forest canopy image. Fertility estimates in the aerial derived matrix model were obtained using the spatially explicit nature of remotely sensed data, including functions relating fertility to both parental size and distance between prospective parent and newborn. Matrix analysis produced a number of useful population characteristics including overall population growth rate ( λ), stable stage distributions, reproductive values, and elasticity values. λ's calculated from the aerial and ground derived matrices were compared using randomization tests. λ's from both aerial and ground derived matrices showed significant increases in population growth rate from the 1997–1998 to the 1998–1999 census periods. Other data measured from the aerial imagery and on the ground seemed to support this population change, the result of a damaging February 1998 ice storm. While providing a perspective and description of a population that differs from traditional ground approaches, demographic studies using remote sensing provide some promising advantages. The spatially explicit nature of the data permits more biologically realistic modeling of the population and the investigation of potential environmental influences on population dynamics. Automated extraction of demographic or megademographic data from remotely sensed images represents an important first step toward scaling population analysis to the landscape and regional levels.