Education

Course#: SDEV4650GU
School: Columbia College
Mode: designated campus classroom
Instructor: Greg Yetman
Description: This course will educate students and support effective coastal resilience planning and climate justice through social and data science learning and data acquisition and analysis, making use of emerging technologies and best practices for collaboration with environmental and climate justice practitioners. Instruction is provided in two areas: i. Climate adaptation planning & climate justice; and, ii. Data science: acquisition, analysis and visualization. Students and  instructors will work with participating community-based climate and environmental justice organizations to collect and analyze biological, geographic and socio-economic data  relevant to local resilience needs. Once this data has been acquired or generated and quality-assured, the students and community partner organizations will prepare it for presentation to federal, state and local planning officials, to help ensure that the resilience goals and related concerns identified by our community partners will be fully reflected in future planning by those officials.  Upon completion of the course, students will better understand the challenges involved in creating and implementing collaborative, data-informed, multi-stakeholder plans for coastal resilience and ecosystem restoration in today’s increasingly climate-disrupted world.

Course#: SUSC5210PS
School: School of Professional Studies
Mode: designated campus classroom
Instructor: Alex de Sherbinin
Description: This course will present students with the architecture, data, methods, and use cases of environmental indicators, from national-level indices to spatial indices. The course will draw on the instructor’s experience in developing environmental sustainability, vulnerability and risk indicators for the Yale/Columbia EPI as well as for a diverse range of clients including the Global Environmental Facility, UN Environment, and the US Agency for International Development. Guest lecturers will provide exposure to Lamont experience in monitoring the ecological and health impacts of environmental pollution and the use of environmental indicators in New York City government. Beyond lecture and discussion, classroom activities will include learning games, role play and case study methods.

The course will explore alternative framings of sustainability, vulnerability and performance, as well as design approaches and aggregation techniques for creating composite indicators (e.g., hierarchical approaches vs. data reduction methods such as principal components analysis). The course will examine data sources from both in-situ monitoring and satellite remote sensing, and issues with their evaluation and appropriateness for use cases and end users. In lab sessions, the students will use pre-packaged data and basic statistical packages to understand the factors that influence index and ranking results, and will construct their own simple comparative index for a thematic area and region or country of their choice. They will learn to critically assess existing indicators and indices, and to construct their own. In addition, students will assess the impacts of environmental performance in several developing and developed countries using available data (e.g., pollutant levels in soils and air in Beijing and NYC), and project future changes based on the trends they see in their assessments. The course will also examine theories that describe the role of scientific information in decision-making processes, and factors that influence the uptake of information in those processes. The course will present best practices for designing effective indicators that can drive policy decisions.

Course#: SDEV3390UN
School: Columbia College
Mode: designated campus classroom
Instructor: Kytt Macmanus
Description: This course is designed to provide students with a comprehensive overview of theoretical concepts underlying GIS systems and to give students a strong set of practical skills to use GIS for sustainable development research. Geographic Information Systems (GIS) are a system of computer software, data and analysis methods used to create, store, manage, digital information that allow us to create maps and dynamic models to analyze the physical and social processes of the world. Through a mixture of lectures, readings, focused discussions, and hands-on exercises, students will acquire an understanding of the variety and structure of spatial data and databases, gain knowledge of the principles behind raster and vector based spatial analysis, and learn basic cartographic principles for producing maps that effectively communicate a message. Student will also learn to use newly emerging web based mapping tools such as Google Earth, Google Maps and similar tools to develop on-line interactive maps and graphics. The use of other geospatial technologies such as the Global Positioning System will also be explored in this class. Case studies examined in class will draw examples from a wide ranges of GIS applications developed to assist in the development, implementation and evaluation of sustainable development projects and programs. On completion of the course, students will: 1. use a variety of GIS software programs to create maps and reports; 2. develop a sound knowledge of methods to search, obtain, and evaluate a wide variety of spatial data resources; 3. develop skills needed to determine best practices for managing spatial data resources; 4. use GIS to analyze the economic, social and environmental processes underlying the concept of building a sustainable world; 5. Gain an understanding of the limits of these technologies and make assessments of uncertainty associated with spatial data and spatial analysis models. Offered in the fall and spring.

Geographic Information Systems (GIS) for Sustainability Management
Course#: SUMA5205PS
School: School of Professional Studies
Mode: designated campus classroom
Instructor: Antoinette Wannebo

This course introduces students to Geographic Information Systems (GIS) tools and concepts, provides practical experience using GIS software and focuses on the application of GIS for sustainable development.

GIS are a set of tools to collect, store, analyze and display spatial  information. As part of the class, students will receive a comprehensive introduction to GIS. Through a mixture of  lectures, readings, focused discussions, hands-on exercises, and guest lecturers, students will acquire an understanding of the different types and structures of spatial data and databases, gain knowledge of the principles behind raster- and vector-based spatial  analysis and learn basic cartographic principles for producing maps that effectively communicate a message.  Case studies examined in class will draw  examples from a wide range of GIS applications supporting the design, implementation and evaluation of sustainable development projects and programs. Students will complete a term project on a topic of their choice giving them the opportunity to apply their learnings to design and complete a GIS project from start to finish.

Course#: SDEV3400UN
School: Columbia College
Mode: designated campus classroom
Instructor: Susana Adamo
Description: Population processes and their outcomes in terms of population size and distribution have a fundamental role in sustainable development and also broad policy implications. This course will introduce students to the scientific study of human populations as a contribution toward understanding social structure, relations, and dynamics, as well as society-nature interactions. The aim is to offer a basic introduction to the main theories, concepts, measures, and uses of demography. The course will cover the issues of population size, distribution and composition, and consumption, at different scales from global to regional to local, as well as the implications for population-environment relationships. It will also address the fundamental demographic processes of mortality, fertility, and migration, including their trends and transitions, we will consider these topics in the context of economic development, sustainability, and cultural change. The course will also include an overview of basic demographic techniques and tools used for identifying, managing, analyzing and interpreting population data, and an introduction to population projections. Lab sessions will supplement readings and lectures by enabling students to explore data sources, calculate rates, and graphically represent demographic data.

Course#: CLMT5013GR
School: Climate School
Mode: designated campus classroom
Instructors: Susana Adamo and Alex de Sherbinin
Description: It is widely accepted that climate factors can and do affect human mobility, though the degree of their influence varies depending on local contexts. In the case of population displacement, rapid onset climate extremes have a relatively direct impact on mobility, and for longer-term migration climate factors also have been shown to play a role, often mediated by more direct drivers. There is a growing recognition that underlying institutional and structural factors (i.e., root causes) shape the way the climate stressors impact local migration decision-making, and that cultural proclivities and inequitable access to resources, markets, and political power structures often set the stage for ensuing migration flows (domestic and international). In many low income settings the donor and development assistance community are grappling with these complex nexus issues as they seek to develop policies and programs that reduce the potential for distress or mass migration. Responses to date generally fall into four categories; 1) those that address the livelihood aspects of climate migration -- e.g., by improving the prospects for local adaptation; 2) those that seek to facilitate mobility as an adaptation mechanism; 3) those that resettle people in new locations and offer migrant protections; and 4) those that seek to mitigate the impacts of those movements, including environmental impacts, on receiving communities. In high income settings, responses to current and potentially increased immigration from developing countries tends to fall into two camps: a resurgent nationalism with measures to prevent or deter migration versus more migrant-friendly policies that seek to protect migrant rights while acknowledging responsibility for historic greenhouse gas emissions. In addition, high income countries are facing climate impacts of their own such as sea level rise, riparian flooding and massive fires that have displaced thousands and prompted managed retreat from at-risk areas. All this has brought to the fore questions of equity and climate justice as marginalized populations everywhere are often disproportionately affected and least compensated. This interdisciplinary course focuses on the social, demographic, economic, political, environmental and climatic factors that shape human mobility, while addressing the legal categories of international mobility (e.g., migrant versus refugee). We explore underlying drivers of the various types of migration – from forced to voluntary and those forms in between – in order to better understand current and future trends. The course brings to the fore equity, climate justice, and human rights considerations, as well as the mental health dimensions of climate displacement and migration.

Course#: SUMA5255PS
School: School of Professional Studies
Mode: designated campus classroom
Instructor: Greg Yetman
Description: Data science is an exciting new field of applied research that takes advantage of the ever-growing volume of data being collected to support decision-making in both the public and private sectors, with limits and issues that are important to understand before applying to problem solving. In anticipation of increased use of data science in promoting sustainability, this course introduces the common methods used in data science, best practices in data management, and the basic scripting skills required to start analyzing data in R and Python. After introducing foundational scripting and data analysis methods, a case study approach will be used to highlight both what can be accomplished with data analysis and the limits of the data and methods used. Lab exercises will teach basic skills in scripting in Python and R and then move to a common approach for data analysis: adapting existing scripts and software libraries to solve applied data problems.

Course#: SDEV3390UN
School: Columbia College
Mode: designated campus classroom
Instructor: Linda Pistolesi and Antoinette Wannebo
Description: This course is designed to provide students with a comprehensive overview of theoretical concepts underlying GIS systems and to give students a strong set of practical skills to use GIS for sustainable development research. Geographic Information Systems (GIS) are a system of computer software, data and analysis methods used to create, store, manage, digital information that allow us to create maps and dynamic models to analyze the physical and social processes of the world. Through a mixture of lectures, readings, focused discussions, and hands-on exercises, students will acquire an understanding of the variety and structure of spatial data and databases, gain knowledge of the principles behind raster and vector based spatial analysis, and learn basic cartographic principles for producing maps that effectively communicate a message. Student will also learn to use newly emerging web based mapping tools such as Google Earth, Google Maps and similar tools to develop on-line interactive maps and graphics. The use of other geospatial technologies such as the Global Positioning System will also be explored in this class. Case studies examined in class will draw examples from a wide ranges of GIS applications developed to assist in the development, implementation and evaluation of sustainable development projects and programs. On completion of the course, students will: 1. use a variety of GIS software programs to create maps and reports; 2. develop a sound knowledge of methods to search, obtain, and evaluate a wide variety of spatial data resources; 3. develop skills needed to determine best practices for managing spatial data resources; 4. use GIS to analyze the economic, social and environmental processes underlying the concept of building a sustainable world; 5. Gain an understanding of the limits of these technologies and make assessments of uncertainty associated with spatial data and spatial analysis models.

Course#: SDEV3450UN
School: Columbia College
Mode: designated campus classroom
Instructor: Kytt MacManus
Description: This is an intermediate course in spatial modeling developed specifically for students in the Undergraduate Sustainable Development program. This course will provide a foundation for understanding a variety of issues related to spatial analysis and modeling. Students will explore the concepts, tools, and techniques of GIS modeling and review and critique modeling applications used for environmental planning and policy development. The course will also offer students the opportunity to design, build and evaluate their own spatial analysis models. The course will cover both vector and raster based methods of analysis with a strong focus on raster-based modeling. We will draw examples from a wide range of applications in such areas as modeling Land Use and Land Cover for biodiversity and conservation, hydrological modeling, and site suitability modeling. The course will consist of lectures, reading assignments, lab assignments, and a final project.

Course#: GR5013
School: Climate and Society Master’s Program, The Climate School
Mode: designated campus classroom
Instructors: Susana Adamo and Alex de Sherbinin
Description: This team-taught interdisciplinary course focuses on the social, demographic, economic, political, environmental and climatic factors that shape mobility as well as the legal categories of international mobility (e.g., migrant versus refugee), exploring underlying drivers of the various types of migration—from forced to voluntary—in order to better understand current and future trends. It brings to the fore equity, climate justice, and human rights considerations, as well as the mental health dimensions of climate displacement and migration. The course will offer students the opportunity to undertake a role-play that explores policy and programmatic responses to climate  migration, guided by leading policy experts. In a simulated negotiation of the Global Compact for Migration (GCM), teams of students will employ the knowledge they have gained and a zero-draft of the compact to negotiate the final text of the GCM, taking into account the interests of the party they will represent. This component builds on the Climate School’s Fourth Purpose, which is to apply research to policy design and programs.

Course#: SUMA PS5255
School: School of Professional Studies/Sustainability Management Program
Mode: designated campus classroom
Instructor: Greg Yetman
Description: Data science is an exciting new field of applied research that takes advantage of the ever-growing volume of data being collected to support decision-making in both the public and private sectors, with limits and issues that are important to understand before applying to problem solving. In anticipation of increased use of data science in promoting sustainability, this course introduces the common methods used in data science, best practices in data management, and the basic scripting skills required to start analyzing data in R and Python. After introducing foundational scripting and data analysis methods, a case study approach will be used to highlight both what can be accomplished with data analysis and the limits of the data and methods used. Lab exercises will teach basic skills in scripting in Python and R and then move to a common approach for data analysis: adapting existing scripts and software libraries to solve applied data problems.

Course#: SDEV W3390
School: Columbia College
Mode: designated campus classroom
Instructor: Linda Pistolesi
Description: A comprehensive overview of theoretical concepts underlying geographic information systems (GIS) as a foundation for practical GIS skills used in sustainable development research. Through a mix of lectures, readings, focused discussions, and hands-on exercises, students will acquire an understanding of the variety and structure of spatial data and databases, gain knowledge of the principles behind raster- and vector-based spatial analysis, and learn basic cartographic principles for producing maps that effectively communicate a message. Students will also learn to use emerging Web-based mapping tools such as Google Earth, Google Maps, and similar tools to develop online interactive maps and graphics. The use of other geospatial technologies such as the Global Positioning System (GPS) will also be explored.

Course#: SDEV W3450
School: Columbia College
Mode: designated campus classroom
Instructor: Kytt MacManus
Description: This is an intermediate course in spatial modeling developed specifically for students in the Undergraduate Sustainable Development program. This course will provide a foundation for understanding a variety of issues related to spatial analysis and modeling. Students will explore the concepts, tools, and techniques of GIS modeling and review and critique modeling applications used for environmental planning and policy development.