Peter Nelson

Urban Geography
Urban landscapes are the expression of economic, political, and socio-cultural processes layered on top of each other in particular time-space contexts. In this course, students will theoretically and empirically examine the complex and dynamic urban landscape. Students will gain a theoretical understanding of the location of cities within a larger global economic system of cities, along with the internal organization of economic, cultural, and social functions within cities. We will also examine the processes behind contemporary urban issues such as homelessness, boosterism, urban renewal, gentrification, poverty, and crime. 3 hrs. lect.

Population Geography
Through a combination of lectures, readings, and exercises, this course provides background and analytical experience in the spatial dimensions of population dynamics. Students will theoretically and empirically examine geographic variations in natural increase, domestic and international migration, infant mortality, disease, and hunger. Topics will include the intersection of settlement-environment-disease, circular migration systems, cultural influences on demographic processes, and linkages between international and domestic migration flows. We will also assess various policy options and their effectiveness in addressing important demographic issues. The exercises will expose students to the vast amount of population data publicly available and introduce them to techniques used to examine and assess population related issues.

Rural Geography
This course explores the intersection between demographic, economic, cultural, and environmental forces on the rural landscape in both advanced economies and LDCs. Students will be exposed to theoretical and empirical approaches to rural development in different international and regional contexts, as well as problems associated with these development paradigms. Particular attention will be paid to neoliberal economic policies and their impacts on rural areas, and the course will frequently draw on examples from New England and North America. Additionally, the world is becoming increasingly urbanized, so we will examine the ways people come to know rural areas through the media, literature, and travel. This course includes opportunity for service learning. (Formerly GEOG 0221) 3 hrs. lect.

Data Science Across Disciplines
In this course, we will gain exposure to the entire data science pipeline—obtaining and cleaning, large and messy data sets, exploring these data and creating engaging visualizations, and communicating insights from the data in a meaningful manner. During morning sessions, we will learn the tools and techniques required to explore new and exciting data sets. During afternoon sessions, students will work in small groups with one of several faculty members on domain-specific research projects in Biology, Geography, History, Mathematics/Statistics and Sociology. This course will use the R programming language. No prior experience with R is necessary.

BIOL 1230: Students enrolled in Professor Casey’s (Biology) afternoon section will use the tools of data science to investigate the drivers of tick abundance and tick-borne disease risk. To do this students will draw from a nation-wide ecological database.

GEOG 1230: In this section, we will investigate human vulnerability to natural hazards in the United States using location-based text data about hurricane and flood disasters from social media. We will analyze data qualitatively, temporally, and spatially to gain insights into the human experience of previous disasters and disaster response. We will present findings using spatial data visualizations with the aim of informing future disaster preparedness and resilience.

HIST 1230: In U.S. history, racial differences and discrimination have powerfully shaped who benefited from land and farm ownership. How can historians use data to understand the history of race and farming? Students will wrangle county- and state-level data from the U.S. Census of Agriculture from 1840-1912 to create visualizations and apps that allow us to find patterns in the history of race and land, to discover new questions we might not know to ask, and to create tools to better reveal connections between race, land, and farming for a general audience.

STAT 1230: In this course students will dive into the world of data science by focusing on invasive species monitoring data. Early detection is crucial to controlling many invasive species; however, there is a knowledge gap regarding the sampling effort needed to detect the invader early. In this course, we will work with decades of invasive species monitoring data collected across the United States to better understand how environmental variables play a role in the sampling effort required to detect invasive species. Students will gain experience in the entire data science pipeline, but the primary focus will be on data scraping, data visualization, and communication of data-based results to scientists and policymakers.

SOCI 1230: Do sports fans care about climate change? Can sports communication be used to engage audiences on environmental sustainability? In this section of the course, students will use the tools of data science to examine whether interest in sports is associated with climate change knowledge, attitudes and behaviors, as well as other political opinions. Participants will use survey data to produce visualizations and exploratory analyses about the relationship between sports fandom and attitudes about environmental sustainability.