Integration of GIS Data and Classified Satellite Imagery for Regional Forest Assessment

Abstract

New methods are needed to derive detailed spatial environmental data forlarge areas, with the increasing interest in landscape ecology andecosystem management at large scales. We describe a method thatintegrates several data sources for assessing forest composition acrosslarge, heterogeneous landscapes. Multitemporal Landsat Thematic Mapper(TM) satellite data can yield forest classifications with spatiallydetailed information down to the dominant canopy species level intemperate deciduous and mixed forests. We stratified a large region(10(6) ha) by ecoregions (10(3)-10(4) ha). Within each ecoregion,plot-level, field inventory data were aggregated to provide informationon secondary and subcanopy tree species occurrence, and tree age classdistributions. We derived a probabilistic algorithm to assigninformation from a point coverage (forest inventory sampling points) anda polygon coverage (ecoregion boundaries) to a raster map (satelliteland cover classification). The method was applied to a region innorthern Wisconsin, USA. The satellite map captures the occurrence andthe patch structure of canopy dominants. The inventory data provideimportant secondary information on age class and associated species notavailable with current canopy remote sensing. In this way we derived newmaps of tree species distribution and stand age reflecting differencesat the ecoregion scale. These maps can be used in assessing forestpatterns across regional landscapes, and as input data in models toexamine forest landscape change over time. As an example, we discuss thedistribution of eastern white pine (Pinus strobus) as an associatedspecies and its potential for restoration in our study region. Ourmethod partially fills a current information gap at the landscape scale.However, its applicability is also limited to this scale.