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摘要

This issue largely focuses on geospatial applications in forestry with papers on forest cover and income (northeastern United States), tenure characteristics and rural well-being(Black BeltAlabama), and modeling forest species to estimate forest canopy distribution (Cap Cod, Massachusetts). These studies employ a range of geostatistical techniques and models including a spatial error regression, geographically weighted regression and the environmental Kuznets curve (Bentley, Cromley, Hanink, & Heidkamp), descriptive statistics and Mann Whitney U tests (Dyer, Marzen, & Hite), and species distribution models (McCauley, Rogan, & Miller). That there is a sustained interest in using geospatial technologies for forestry studies should be no surprise. Remembering Aronoff's(1989) Geographic Information Systems: A Management Perspective from days (years) as a graduate student at the University of North Carolina at Chapel Hill I scanned its index for "forestry" and found pages 7-13, 223-225, and plates 1 and 2 listed.