Steve is a GIScientist and biogeographer who studies forested ecosystems, with a focus on forests prior to European settlement in the Northeastern US Steve's research examines the factors that shaped past geographic distributions of tree species, as well as methodological issues surrounding this area of inquiry (e.g. spatial representations of ecological phenomena, positional uncertainty in species data). His research utilizes geospatial tools and quantitative methods, such as geographic information systems (GIS), predictive modeling, statistical computing, and programming. Steve's research also utilizes – and studies the usefulness of – unconventional or "found" data sources, such as original land survey records of the 17th to 19th centuries CE. His dissertation explored the impacts of Native American settlement upon tree species composition in Chautauqua County, New York (ca. 1800 CE). Steve's teaching interests include GIS, environmental issues, and geospatial and statistical software. Future research interests are in applying recent methods and paradigms in geographic study – such as information retrieval, text mining, and citizen science – to the pursuit of comprehending past forest conditions in the Northeast.
National Science Foundation (NSF)-funded research
Classes
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GEOG 125: Digital Earth
How do sensors on airplanes discover lost ancient cities? How does a GPS know where you are? How does Google Maps determine the fastest route between two locations? This course focuses on quantitative reasoning and problem-solving in geography, including methods associated with current tools and technologies that geographers use to study the earth. Students will first learn about 21st century tools including global positioning systems (GPS), geographic information systems (GIS), and remote sensing. Students will also learn specific quantitative methods and skills that geographers use, such as structured query language (SQL), map algebra, and network analysis.
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GEOG 278: Statistics in Geography
An introduction to statistical research methods in geography. This course covers classical and spatial statistics as applied to research in physical and human geography. Topics covered include description, inference, significance, and prediction based on samples drawn from geographic data. (Students may not receive credit for more than one 200-level statistics course, including credit for more than one of the following courses: ECON 205, GEOG 278, MATH 242, PLSC 251, PSYC 250, and SOCL 211.) Prerequisites: GEOG 102 or GEOG 111 and GEOG 112 or GEOG 123 or permission of instructor. Offered every year
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GEOG 385: Adv Geographic Info Sys (GIS)
This course provides a detailed examination of conceptual issues presented in the introductory GIS class. It also involves additional material on data acquisition, data structures, spatial data standards and error analysis, spatial analysis operations, the effects of geographical information science on society, and GIS applications.