Water as a Human Right and Fugitive Resource Safe and clean drinking water and sanitation are now recognized by the United Nations as human rights. However, the quantity and quality of fresh water vary over space and time, and therefore water is often understood as a “scarce” or “fugitive” resource. How does society understand and manage the water cycle, and how does water in turn shape society? We will investigate these questions through geographic analysis, drawing on evidence from local field observations, maps and geographic information systems, published research papers, and water laws and policy.

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.

Spatial Analysis with Geographic Information Systems Geographers use spatial analysis to understand human interactions with the environment and the spatial organization of society. For example, spatial patterns of settlements relative to environmental amenities and risks can reveal who benefits and who is harmed. In this course, we will learn how to use geographic data and geographic information systems (GIS) to support spatial analysis of a range of themes, for example urban, environmental, political, hazards, and/or health geography. We will learn how to use GIS to gather, create, analyze, visualize, and interpret geographic data through tutorials, collaborative labs, and independent work that culminate in cartographic layouts of our results.

Spatial Analysis with Geographic Information Systems Geographers use spatial analysis to understand human interactions with the environment and the spatialorganization of society. For example, spatial patterns of settlements relative to environmental amenities and risks can reveal who benefits and who is harmed. In this course, we will learn how to use geographic data and geographic information systems (GIS) to support spatial analysis of a range of themes, for example urban, environmental, political, hazards, and/or health geography. We will learn how to use GIS to gather, create, analyze, visualize, and interpret geographic data through tutorials, collaborative labs, and independent work that culminate in cartographic layouts of our results.

Seminar in Geographies of Climate Change Adaptation and Development Rapid anthropogenic climate change cannot be fully mitigated, requiring humans to adapt to changing climate conditions.  How will developing countries with high sensitivity and few resources manage to adapt to a changing climate?  Geography is uniquely suited to research social dimensions of climate change by integrating human and physical geography in the traditions of hazards, human-environment systems, and political ecology research.  In this seminar we will contrast approaches to three related concepts: resilience, vulnerability, and adaptation.  We will review their use in current academic research and literature, international climate negotiations, and adaptation planning and financing in least developed countries.  We will culminate the seminar with independent research into a particular case of planned climate change adaptation in a least developed country.

Open Geographic Information Science (formerly GEOG 0323) In this course we will study geographic information science (GIS) with open-source software and critical GIS scholarship. In labs, we will practice techniques to include: data acquisition and preparation for analysis, spatial SQL database queries, automating analysis, spatial interpolation, testing sensitivity to error and uncertainty, and data visualization. We will read and apply critical research of GIS as a subject and with GIS as a methodology. Spatial data sources for labs and independent research projects may include remote sensing, micro-data, smart cities and open government data, and volunteered geographic information (e.g. OpenStreetMap and social media).

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.

Human Geography of Hazards Why do storms, earthquakes, and other hazards result in disastrous loss of life in some places, and only minor losses in others?  In this course we will study human geographies of population, economic development, politics, and culture to explain the diverse outcomes from biophysical hazards.  We will compare hazard geographies at the global, regional, and local scales using diverse approaches, including quantitative analysis, geographic information systems (GIS), and comparative case studies.  We will examine how geographic analysis and technologies are used in disaster planning and response.  We will practice applying human geography theory and methods to hazards research through practical exercises, exams, and research projects.

Open Source Geographic Information Science In this course, we will study geographic information science (GIScience) by reproducing published research with open-source geospatial software. We will debate issues in GIScience by applying critical GIS scholarship, fundamentals of spatial data and analysis, and evidence from our reproduction studies. We will practice open GIScience by collaboratively developing research plans, acquiring and describing spatial data, analyzing and visualizing data with SQL and R, and testing for error and uncertainty. Our research products and results will be published with open science standards in public portfolios. We typically investigate research with themes of human-environment interactions, health, hazards, urban development, and more.These research themes require and integrate social/demographic data, environmental data, and big data.

Joseph Holler

Reviews and ratings for Joseph Holler at Middlebury College.Joseph Holler teaches Water Rights and Resources, Place And Society, Spatial Analysis with GIS and more.  Explore top rated instructors and find the best for you.Is Joseph Holler good ? Find out on MiddCourses.

I enjoyed taking this course with Prof. Holler. The labs were very difficult as someone who has no experience with GIS, but the TAs were very helpful. I often found myself spending several extra hours in the computer lab to catch up on the work. I found this course very valuable for my ES degree, and thought the subject matter was very interesting. 

The class was interesting but very fast paced. The teaching was sort of confusing and the grading was tough in various aspects. TAs would think a part of my project was great but then I would lose 10+ points in the grading which was frustrating. 

Holler is great, although he can be kind of intimidating toward the beginning of the semester. This class is not as hard as everyone thinks it is. The exams are kind of difficult, but they are open book (at least when I took it). The labs are not easy but I found TAs and course assistants to be very helpful. The 'reading' (panopto videos) was very helpful, but did take a long time to complete.