Multitemporal censusing of a population of eastern hemlock (Tsuga canadensis L.) from remotely sensed imagery using an automated segmentation and reconciliation procedure

Large-scale (1:3000) color aerial images of a population of eastern hemlock (Tsuga canadensis L.) were collected in the early spring of 1997, 1998, and 1999. An automated spatial segmentation procedure was developed to identify and measure individual population objects or blobs within the forest population. To ensure the comparability of multiyear segmentation maps, an automated blob reconciliation procedure was also developed to make certain that no hemlock pixels were assigned to different blobs in different years. The automated segmentation and reconciliation procedures were applied to a population of naturally occurring hemlock. Following spatial segmentation, a large majority of hemlock blobs (∼66-71%) were found to be closely associated with ground referenced, manually delineated individual hemlock crowns. The remaining blobs consisted of spatially distinct parts of a crown or closely clumped multiple crowns. Similar overall classification accuracies (∼63-72%) were found following the reconciliation of multitemporal image pairs. The development of these spatially explicit multitemporal population data sets should prove useful to further investigations of the dynamics of and environmental influence on plant populations.