Comparing the use of Synthetic Aperture Radar and Landsat Thematic Mapper to predict slash pine (Pinus elliottii) plantation attributes

Abstract

Aerial photographs and, more recently, Landsat Thematic Mapper (LTM) have long been a source for spatial information in forest management. Recently, Synthetic Aperture Radar (SAR) has been introduced as another source upon which to base forest management decisions. This study explores use of LTM and SAR data to predict Slash Pine basal area and yield. Forest attribute estimation models were developed using two model-building techniques - stepwise multiple-linear regression and a more biologically motivated approach.|SAR data were found to explain more variability in both basal area and yield than LTM. Combining SAR and LTM significantly improved the amount of variation explained in basal area and yield in comparison to models developed from either SAR or LTM independently. The biologically motivated models explained more variation than a standard stepwise regression procedure due to model forms that were consistent with biological behavior. These more biologically motivated models also exhibit better extrapolative behavior.