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.

Seminar in Population Geography: Migration in the Twenty-first Century On average, 20 percent of the U.S. population changes residence in any given year, yet the scale, geography, motivations, and impacts of these movements are highly variable, making migration an incredibly pervasive and complex phenomenon. Furthermore, international immigration continues to attract considerable academic, political, and media attention. This course will explore contemporary approaches to migration studies emphasizing the important insights and contributions of geographers. How have geographers examined migration, and how have geographical approaches changed over time? In what ways has technology influenced the motivations, frequency, and implications of migration behavior? What are the different impacts of migration on individuals, households, and communities? And, what are the new innovations in scholarly approaches to migration? Through a combination of readings from contemporary migration literature, discussions, and analyses, students in this seminar will gain an appreciation for and understanding of this incredibly rich and complex phenomena of migration.

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.

Placebased Data Analysis (formerly GEOG 0139) Who migrates from urban areas during a pandemic? How are livelihoods distributed around protected areas in Central Africa? How much does location influence the price of a house? In this course students will discover ways  to answer questions like these by introducing fundamentals for generating and analyzing data about people and the places they are connected to. Students will practice constructing datasets, visualizing relationships, formulating and testing hypotheses, modeling outcomes, and conveying results. We will cover descriptive and inferential statistics, focusing on geographic applications and the unique complexities of spatial data. Through cases and problem sets, students will explore complementarities between quantitative and qualitative analysis, emphasizing critical and reflexive approaches. Labs will build proficiency with software packages like R and GeoDa. The course aims to make students more savvy consumers of published work, to produce careful analysts, and to foster a deeper appreciation for the research process. No prior experience with Statistics or Geography is required; the course is designed to introduce students to approaches broadly relevant in Geography and allied social sciences.

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.

Place and Society: Local to Global This course is an introduction to how geographers view the world and contribute to our understanding of it. Where do the phenomena of human experience occur? Why are they there? What is the significance? These questions are fundamental for explaining the world at different scales from the global to the local. Throughout, we will focus on the spatial basis of society, its continual reorganization through time, and how various human and environmental problems can be usefully analyzed from a geographic perspective.

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.

Practicing Human Geography Whether you are planning to do your own research or want to be a more savvy consumer of research produced by others, it is useful to develop an understanding of the process of creating, discovering, and interpreting information about the world. In this course, students will explore quantitative and qualitative methodologies and the ways they can be used in human geography research. Through examples, exercises, and readings, students will learn the types of questions different techniques are designed to answer, how they work, and how to interpret the results. Students will gain hands on experience conducting surveys, generating and interpreting qualitative data, selecting and implementing statistical analyses, and writing research reports, to build competence and critical awareness in the practice and communication of research.

Peter Nelson

Reviews and ratings for Peter Nelson at Middlebury College.Peter Nelson teaches Rural Geography, Seminar: Population Geography, Urban Geography and more.  Explore top rated instructors and find the best for you.Is Peter Nelson good ? Find out on MiddCourses.

Professor Nelson is just an amazing person to take a course with. He is always enthusiastic and is extremely knowledgeable in his fields. He always makes the class super fun and while you have to go to lectures to score well, they are worth the time. There are quite some writings needed for the course, which were time consuming but the content was interesting.

This course is fast paced, but it needs to be in order for students to actually learn R in one semester. I feel like I took a lot away from this class, and even though it was a decent amount of work outside of class it didn't feel like a burden. Whether or not you are into Geography, if you want to learn R this is a great course for you.

I thought this was a great class! I went in with no prior data science experience, and honestly I'm not sure I'd recommend doing that. Students with any kind of prior experience had an easier time starting out compared to those who didn't, though it evened out over the semester. Just know you'll need to learn R fast and lean hard on tutoring, office hours, and the TA.

Professor Nelson is very kind and genuinely wants to help you improve, so seek him out! Things can get confusing if you don't have an R background, but ask questions often, and he'll be there to answer them. Googling R errors also helps a lot. The projects followed a similar format throughout the semester and were manageable as long as you don't procrastinate. Each one takes 10+ hours and can't be rushed, so plan accordingly.