The most critical issue facing the world today is the sustainability of both human and physical systems in the 21st century. This class uses the context of regions of the world to explore the 21st century issues of climate change, development, politics, economy, and demography. Each region will be used to highlight aspects of sustainability.

The geography of economic, social, and environmental well-being and inequality. The course will provide an integrated perspective on the causes, interconnections, and consequences across time and space of, among others, globalization, climate change, poverty, employment, migration and urban growth, agricultural productivity, rural development, policies and international trade. Portraits of selected countries and regions will be developed.

Catastrophic Environmental Events (CCE) that are becoming more common i this time of global environmental change and it is essential that today's students be equipped with the knowledge and skills to be leaders as we, as a society, understand the upheaval that these CCEs are causing. Students will examine how CEEs shape human society and ecosystem from the interdisciplinary perspective afforded by the field of Geography. Students will use the latest geographic science concepts and techniques in exploring these events.

Introduction to technical methods used in gathering, analyzing, and presenting geospatial information, addressing the needs of geospatial analysis, such as environmental monitoring, situational awareness, disaster management, and human systems. Topics include basics of locational reference systems, map projections, satellite and airborne remote sensing, global positioning systems, geographic information systems, cartography, and introductory statistics and probability. The course is a gateway to more advanced technical classes in geoinformatics.

Earth observations from space enable the mapping and monitoring of our changing planet. This survey course reviews current observational capabilities and examines scientific applications in quantifying global environmental change. Drivers and outcomes of key dynamics will be illustrated and discussed, including sea and continental ice loss, deforestation, ocean warming, urbanization, agricultural expansion and intensification, and vegetation response to climate change.

A systematic introduction to the processes and associated forms of the atmosphere and earth's surfaces emphasizing the interaction between climatology, hydrology and geomorphology.

Introduction to what geographers do and how they do it. Systematic study of issues regarding social and cultural systems from a global to a local scale. Looks at the distribution of these variables and answers the question "Why here, and not there"?

A laboratory course to accompany GEOG 201. Analysis of the components of the earth's energy balance using basic instrumentation; weather map interpretation; soil analysis; the application of map and air photo interpretation techniques to landform analysis.

Purpose: increase student knowledge of professional development opportunities in Geography through classroom activities and invited speakers, and to build awareness of career development tools and strategies. The main focus of the class is to prepare students to use the tools needed to pursue professional opportunities, including internships, jobs, and graduate school. Special emphasis will be on résumé building, cover letter writing, communication skills, and job, internship, and graduate school research.

Concepts and principles of Earth observation and remote sensing in relation to photographic, thermal infrared and radar imaging. Methods of obtaining quantitative information from remotely-sensed images. Interpretation of remotely-sensed images emphasizing the study of spatial and environmental relationships.

Concepts and principles of Earth observation and remote sensing in relation to photographic, thermal infrared and radar imaging. Methods of obtaining quantitative information from remotely-sensed images. Interpretation of remotely-sensed images emphasizing the study of spatial and environmental relationships.

Introduces conceptual and practical aspects of scientific computing using the Python programming language. The main focus is on developing proficiency for the basic elements of the development environment, foundational syntax including variables, logical operators, looping, conditional statements, nesting, and common programming patterns for mathematical and textual computing. In addition, essential data structures and functionality for scientific computing, such as arrays, dataframes, and data visualization will be introduced.

How are the cities of the world adapting to or planning to adapt to climate change? This course focuses on urban areas and the environment, specifically how anthropogenic factors have impacted the environment and how the environment has responded. The aim is to discover how associated and concomitant problems owing to the development and use of the planets resources are created and the various approaches to reduce the negative impacts of these problems through a variety of approaches.

Contact department for information to register for this course.

Essentials in the quantitative analysis of spatial and other data, with a particular emphasis on statistics and programming. Topics include data display, data description and summary, statistical inference and significance tests, analysis of variance, correlation, regression, and some advanced concepts, such as matrix methods, principal component analysis, and spatial statistics. Students will develop expertise in data analysis using advanced statistical software.

Cultural geography course on society and sustainability. Culture is the basic building block that is key to sustainability of societies. Course will cover sustainability of societies on different scales, examining local, regional, and worldwide issues. Sustainability will be examined as a key element of environmental sustainability. How societies adjust to rapid world change will be examined as a positive and/or negative factor in sustainability. (Human Geography)

Introduction to global-scale interrelationship between human beings and the environment. The development of global issues including but not limited to the environment, food, energy, technology, population, and policy.

Principles of managing scarce resources in a world where everyone faces tradeoffs across both time and space. Focuses on the relationship between globalization processes and changing patterns of locational advantages, production, trade, population, socioeconomic and environmental grace and sustainability. (Human Geography)

How cities have been produced, consumed, and theorized as complex social, economic, ecological, and political systems; the main debates over geographical interpretations of the urban world; the major forces and inter-dependencies that shape internal spatial structure of the city and drive urban trends and public policy. (Human Geography)

Introduces application programing interface (API) functions and image processing techniques for efficient processing of satellite images. The main programing language of the course is Python. The course will use a Geospatial Data Abstraction Library (GDAL) which provides a unified way of manipulating images incorporating geospatial information. For image processing, the course will use Python-based libraries such as scikit-image and OpenCV.

Characteristics and organization of geographic data; creation and use of digital geospatial databases; metadata; spatial data models for thematic mapping and map analysis; use of geographic information system in society, government, and business. Practical training with use of advanced software and geographic databases. (Technical)

Introduces conceptual and practical aspects of programming for geographic applications. The main focus is on developing a solid understanding of basic programming techniques irrespective of the specific programming language including variables, looping, conditional statements, nesting, math, strings, and other concepts. In addition, students will develop a proficiency in applying these basic programming principles to manipulating spatial data sources within the Geographic Information Systems (GIS).

Supervised field training to provide career experience. Introduction to professional level activities, demands, opportunities. Placement at a public agency, non-profit organization, or private firm. Participation requires application to the internship advisor in preceding semester.

Supervised field training to provide career experience. Introduction to professional-level activities, demands, opportunities. Placement at a public agency, nonprofit organization, or private firm. Participation requires application to the internship advisor in preceding semester.

Second course in the departmental honors sequence. Student research under the auspices of a faculty advisor, culminating in a research paper to be defended orally before the geography honors committee.

An introductory course to spatial artificial intelligence (AI), providing a big picture of spatial AI applications (e.g., Google Maps, Uber/Lyft, Earth observation, smart cities, autonomous vehicles), techniques, platforms, trends, debates, etc. The course will cover basics of AI, identify challenges faced by AI techniques in the context of spatial data and applications, and introduce spatial-aware AI methods to address them. AI topics include but are not limited to: spatial data models and knowledge representation, pattern mining, machine learning, perception, planning, etc.

Develops an understanding of the push and pull factors that have contributed to human mobility (migration) that has transformed the Americas. The class is divided in two parts: immigration and emigration from Latin American and Latin America migration to the United States. We will be interested in studying the migration shifts that have occurred in Latin America and the theories that help explain them.

The issues of climate change and land use change as two interlinked global and regional environmental issues and their implications for society and resource use are explored.

The course will be a lab practical. Students will be introduced to the image processing steps required for characterizing land cover extent and change. Key components of land cover characterization, including image interpretation, algorithm implementation, feature space selection, thematic output definition, and scripting will be discussed and implemented.

Applied introduction to field methods. This class is built around a two week field trip (mid-August) with a base camp in the headwaters of the Potomac River in the mountains of West Virginia. During the camp the following topics are covers: GPS (global positions system), stream hydrology measurements, vegetation classification and ordination, micrometeorlogical measurements, soils, water quality, remote sensing and GIS, local environmental issues, geomophology and paleohistory, and natural and cultural history. (Technical)

To develop an understanding of the geographic contexts of Sub-Saharan Africa, including an overview of the physical,
bioclimatic, historical, cultural, political, demographic, health and economic geographies of Sub-Saharan Africa. Students will ‘fill in the map’ of Africa by studying the spatial distribution within each of these geographic domains. In addition to an overview of geography South of the Sahara, the Congo will be taken as a more intensive case study through additional readings, lectures and discussions. (Integrated Geography)

Basic issues concerning the natural history of humans from the perspective of the geographer. Basic components of selected behavioral and natural systems, their evolution and adaptation, and survival strategies. (Human Geography)

This course will provide an introduction to modern econometric techniques in general and spatial econometrics in particular. It is designed for senior and graduate students of geography department who may have relatively limited background in statistics, mathematics, and econometrics but are keen to learn this ‘difficult’ subject. This course will use the popular open source statistical computer language R. Its focus is on using statistical computing to produce analytical reports for real-world applications, research papers, and dissertations.

The harsh environment of the vast polar regions makes them some of the most inaccessible places on Earth. With widespread environmental change already underway, satellite remote sensing provides the only means by which to obtain year-round observations of the polar climate system. The objective of this course is to provide students with an overview of polar remote sensing techniques, including the physical principles of active and passive sensors, orbits, electromagnetic radiation, atmospheric transmission, calibration and validation.

Introduction to coastal oceanography, focusing on the physical, biological, and geological aspects of ocean areas on the inner continental shelves. Wave, currents, and tidal dynamics of bays, open coast, estuaries, and deltas. Sedimentary environments of major coastal types. Ecology and biogeochemical relationships, including benthic and planktonic characteristics. Coastal evolution with sea level rise. Human impacts: eutrophication, modification of sedimentation. The coastal future: rising sea level, hypoxia, and increased storminess.

Biogeographical topics of global significance, including a consideration of measurement techniques, and both descriptive and mechanistic modeling. Topics may include: scale in biogeography, climate and vegetation, global carbon cycle, biodiversity, interannual variability in the biosphere, land cover, global biospheric responses to climate change, NASA's Mission to Planet Earth and Earth Observation System. (Physical Geography)

An introduction to fundamental geospatial objects and geometric algorithms for spatio-temporal data processing and analysis. Point data representation and analysis: spatial data models and data structures, algorithms for spatial queries, point clustering algorithms. Surface and scalar field modeling, such as terrains: raster and triangle-based models (TINs), algorithms for building and querying TINs. Algorithms for natural and urban terrain analysis: morphology computation and visibility analysis.

Introduction and exploration of remote sensing datasets that are not emphasized in existing GEOG computational classes. Emphasis on the strengths and limitations of each technology for various applications in science and resource management (e.g. forestry, agriculture, cryosphere). Fusion techniques, product calibration and validation, and common processing pitfalls will be presented. Hands-on computer labs will allow students to explore each dataset and work toward a unique student-driven project using one or several data sources.

Digital image processing and analysis applied to satellite and aircraft land remote sensing data. Consideration is given to preprocessing steps including calibration and geo registration. Analysis methods include digital image exploration, feature extraction thematic classification, change detection, and biophysical characterization. One or more application examples may be reviewed. (Technical)

Analytical uses of geographic information systems; data models for building geographic data bases; types of geographic data and spatial problems; practical experience using advanced software for thematic domains such as terrain analysis, land suitability modeling, demographic analysis, and transportation studies.

Advanced skills of computer mapping using more sophisticated software packages. Map projection evaluation and selection, coordinate system conversion, techniques of quantitative thematic mapping, map design and generalization, hypermedia and animated cartography. Emphasis on designing and making cartographically sound sophisticated thematic maps. (Technical)

This course considers various ways of understanding interactions and feedback loops between human and natural systems. We begin with core readings on coupled systems, then proceed into different methods for researching such systems. Students will gain fundamental understandings of this emerging area, opportunities to "'practice" appropriate methodological approaches, and a chance to conduct their own research.

Introduction to key aspects of database design for GIS applications; major database models that support spatial data; formal models for key spatial relationships that underlie many different GIS applications; basics of SQL for making queries on datasets; design and construction of ArcGIS geodatabases; ArcGIS tools for geoprocessing. Lab sections will occasionally meet in LEF 1136 or 1138. Students must pay a $40.00 lab materials fee.

This course is intended as a survey of the theory and methods pertaining to social networks. Class time will be devoted to learning principles, theoretical perspectives, and appropriate software packages (mainly those in R) for designing a study for gathering network data, and analyzing those data. The readings are a combination of introductory-level material, classic, scholarly readings in the field, and empirical studies that apply social network analytic techniques to topics relevant to the social sciences as a whole.