Jeremy Mennis

Associate Professor

Office: 329 Gladfelter Hall
Tel: 215 204 4748

E-mail:
jmennis@temple.edu

CV

Areas of Expertise:

Geographic information science and systems: spatio-temporal databases, spatial analysis, geographic data mining

Environmental justice, modeling contextual effects on human behavior (particularly concerning mental health, adolescent substance use, and crime)

Education:

2001 Ph.D., Pennsylvania State University, Geography
1997 M.S., Portland State University, Geography
1992 B.A., University of California at Santa Cruz, Environmental Geology

Courses:

GUS 0821: Digital Mapping

GUS 3062/4062: Fundamentals of Geographic Information Systems
GUS 3065/4065: Applications in GIS

GUS 5159: Geographic Inquiry

Research:

I am a geographic information scientist with research interests in how spatial information is represented and analyzed. My theoretical research focuses on developing designs and analytical methods for spatial and spatio-temporal databases. I am particularly interested in methods to facilitate the discovery of knowledge from the vast stores of data that are now becoming available from sources such as the U.S. Census, environmental monitoring networks, and satellite remote sensing. 

Recently, I became very involved in projects revolving around modeling contextual neighborhood and social network effects on human behavioral outcomes, particularly outcomes related to mental health, adolescent substance use, and juvenile drug offense delinquency and recidivism. Understanding how people and places affect human behavior is one of the central concerns of social science.  The growing prominence of contextual effects research provides a great opportunity for a scholar like myself, who has a background in social science and expertise in geographic information science and spatial analysis. I have sought out other researchers in applied domains such as Psychology, Psychiatry, and Criminal Justice with which to work, in order to make substantial contributions to the literature in these areas. Complementarily, I seek to leverage these new domains as testing places to advance geographic methodology.

Some of my current research projects are listed below.

Spatial Data Mining Juvenile Delinquency and Recidivism

This project, initially funded by a two year grant from NIJ to Temple University (P. Harris, P.I.), concerns modeling the likelihood of juvenile delinquency and recidivism by integrating characteristics of the individual juvenile, the neighborhood within which the juvenile resides, and the program to which the juvenile delinquent has been assigned. The project utilizes a data set of over 40,000 records of all delinquency cases assigned to a court-ordered program by the Family Court of Philadelphia, 1996-2004.

Social Ecology of Adolescent Substance Use

This project is funded by NIH/NIDA (M. Mason, P.I.). It addresses the influence of adolescents’ social networks and activity spaces (i.e. where the adolescent lives and spends their work and leisure time) on substance use.  We obtained data on the daily activities, social networks, and psychological characteristics of a sample of 301 adolescents from a public health facility in Philadelphia, PA for this research.

Neighborhood Effects on Mental Health Outcomes
This project has been funded by two small internal grants from the College of Liberal Arts and the Institute for Public Affairs at Temple University. The aim of the project is to understand place influences treatment continuity and the likelihood of rehospitalization for dually-diagnosed patients - those with both a mental illness and substance abuse diagnosis.

Spatio-Temporal GIS (Multidimensional Map Algebra)

Multidimensional Map Algebra (MMA) is a data processing language for 2D, 2D+time, 3D, and 4D spatial and spatio-temporal raster data.  It encompasses and extends conventional map algebra.  The aim is to develop open source, interoperable software that can facilitate research in a number of scientific spatio-temporal computing applications, such as the analysis of time series of satellite imagery and geocomputational simulation output.  This research was funded by NASA grant #NAG5-12598.

Spatial Analysis of Environmental Justice

Environmental justice is the principle that all people have equal protection under environmental laws and the right to participate in environmental decision-making in their community.  Environmental justice is a principle guiding U.S. environmental policy as well as an activist issue blending environmental and civil rights causes.  I am interested in the quantitative analysis of race, class, and other socioeconomic characteristics as they relate to indicators of environmental risk, particularly toxins produced from industrial and commercial activity.  Recent research has focused on the distribution of air toxic releases in New Jersey, as well as on racial equity in actions taken by agencies responsible for enforcing environmental policies.

Dasymetric Mapping and Areal Interpolation

A dasymetric map seeks to display statistical surface data by exhaustively partitioning space into zones where the zone boundaries reflect the underlying statistical surface variation.  The process of dasymetric mapping is the transformation of data from a set of arbitrary source zones to a dasymetric map via the overlay of the source zones with an ancillary data set.  This research addresses the design, implementation, validation, and application of a new ‘intelligent’ dasymetric mapping  (IDM) technique that supports a variety of methods for characterizing the relationship between the ancillary data and underlying statistical surface.  The technique is referred to as intelligent because an analyst may establish this relationship subjectively using their own domain knowledge, extract this relationship from the data using a novel empirical sampling technique, or combine the subjective and empirically-based methods.

Selected Publications:

Mason, M.J., Mennis, J., Coatsworth, D.J., Lawrence, F., Valente, T., and Zelenak, P., (in press). The relationship of place to substance use and perceptions of risk and safety in urban adolescents. Journal of Environmental Psychology.

Stahler, G., Mennis, J., Cotlar, R, and Baron, D., (in press). The influence of the neighborhood environment on treatment continuity and rehospitalization for dually diagnosed patients discharged from acute inpatient care. The American Journal of Psychiatry.

Mennis, J., 2009. Dasymetric mapping for small area population estimation. Geography Compass, 3(2): 727-745.

Mennis, J. and Hultgren, T., 2006. Intelligent dasymetric mapping and its application to areal interpolation. Cartography and Geographic Information Science, 33(3): 179-194.

Mennis, J., 2006. Mapping the results of geographically weighted regression. The Cartographic Journal, 43(2): 171-179.

Mennis, J., 2006. Socioeconomic-vegetation relationships in urban, residential land: the case of Denver, Colorado. Photogrammetric Engineering and Remote Sensing, 72(8): 911-921.

Mennis, J., Viger, R., and Tomlin, C.D., 2005. Cubic map algebra functions for spatio-temporal analysis. Cartography and Geographic Information Science, 32(1): 17-32.

Mennis, J. and Jordan, L., 2005. The distribution of environmental equity: exploring spatial nonstationarity in multivariate models of air toxic releases. Annals of the Association of American Geographers 95, 249-268.

Mennis, J., 2001. Exploring relationships between ENSO and vegetation vigour in the south-east USA using AVHRR data. International Journal of Remote Sensing, 22(16): 3077-3092.

Mennis, J.L., Peuquet, D.J., and Qian, L., 2000. A conceptual framework for incorporating cognitive principles into geographical database representation. International Journal of Geographical Information Science, 14(6): 501-520.