GEOG:1030 Our Digital Earth

I teach this course during the Fall semester.

Approved for GE: Quantitative or Formal Reasoning and Sustainability

The Earth is undergoing an era of rapid change. Understanding this change and its impacts on life on Earth depends on systematically analyzing and interpreting evolving data, tools, and theories that are highly interdisciplinary. Spatial technologies, such as geographic information systems (GIS) and remote sensing, are uniquely positioned to tackle sustainability issues to increase resiliency in a changing planet. There is a sizeable amount of spatial data that has become accessible through platforms such as Google Earth Engine. This class will introduce students to introductory geospatial skills using inquiry-based activities to build success in basic geospatial data analysis and critical spatial thinking. Through this class, students will use cutting-edge technology to examine sustainability issues such as urban heat islands, glacier retreats, deforestation, and drought. Ultimately the goal is for students to gain experience working with different types of geospatial data used to illuminate and improve sustainability issues that face our current and future generations.

Learning Objectives:

  • Extend knowledge of the underlying physics to execute geospatial data analysis through the implementation of geospatial programming. 
  • Connect how geospatial data and analysis can support a systems-approach to sustainability concepts and topics.
  • Critically examine geospatial datasets and visualizations regarding social-environmental issues to appraise how these may or may not be misleading to the general public by supporting your ideas with evidence and reason.

GEOG:2050 Foundations of GIS

I teach this course during the Spring semester, but it is also offered in the Fall from another instructor.

The intent of this course is to introduce students to the basic principles and applications of Geographic Information Science (GIScience) and Geographic Information Systems (GISystems). Lectures provide the basic knowledge and theory needed to understand and implement spatial analysis skills. Laboratory exercises are designed to familiarize students with ArcGIS Pro, a GIS software commonly used by companies and the government. Labs ground the theoretical classroom discussions in practical applications. The semester-long GIS Project is designed to provide students the opportunity to apply their newly developed GIS skills to a topic of their choice. By the end of this course, students will have developed a strong foundation of spatial analysis skills.

Learning Objectives:

  • Students will execute introductory spatial thinking and analysis skills.
  • Students will implement common techniques and software tools for collecting, storing, querying, analyzing, and visualizing geographic data.
  • Students will recognize the concepts, software, and hardware associated with geospatial technologies.
  • Students will compare the strengths, weaknesses, and assumptions built into common GIS functions.
  • Students will complete a GIS project using the skills acquired throughout the course.

GEOG:3500 Introduction to Environmental Remote Sensing

I teach this course during the Spring semester, alternating with Advanced Remote Sensing. This course is also taught in the Fall by another instructor.

Remote sensing data have become fundamental to many applications in environmental and socioeconomic sciences. Aerial photographs and satellite images are used to examine issues ranging from city planning to global climate change. The aim of this course is to provide an introduction to remote sensing data, methods, and applications with a particular focus on human-environment interactions. This will include topics on data acquisition from aerial and satellite sensors, the development of spatial information commonly used in Geographic Information Systems (GIS), and digital analyses of multispectral remote sensing data. The course will include a lecture and lab to provide theoretical understanding and practical experience using remote sensing software. Some example topics include visual interpretation of aerial photographs, image photogrammetry and geometric correction, digital enhancements and classifications, biophysical analyses of multispectral, hyperspectral, and lidar data, and field methods and applications in the natural and social sciences.  For undergraduate students, you will be expected to understand the theory and applications expected for an entry‐level position. Graduate students should focus on applications most relevant to their research.

Learning Objectives

By the end of the course, it is expected that you will be familiar with topics on:

  • Electromagnetic radiation and spectral reflectance characteristics
  • Data acquisition from aerial and satellite sensors
  • Visual interpretation of the data
  • Common digital analyses of data including: Calculating and interpreting spectral indices, data classifications, image processing, and validation
  • Finally, it is expected you will be able to conduct a basic application of remote sensing from start to finish of a question related to social or physical geography and/or their interactions.

GEOG:4500 Advanced Remote Sensing

I teach this course during the Spring semester, alternating with Introduction to Environmental Remote Sensing. 

Optical remote sensing uses reflected sunlight and emitted thermal infrared radiation to measure the Earth’s surface and atmosphere. This course covers remote sensing theory that determines how light and matter interact. It also investigates applications of visible, near-infrared, thermal infrared, and hyperspectral remotely sensed data. Quantitative labs make measurements that demonstrate remote sensing theory, and also work with state-of-the-art data from aircraft and satellites. Topics include modeling absorption and emission of electromagnetic radiation, directional reflectance, spectroscopy, and hyperspectral remote sensing techniques. This class is perfect for students who want the opportunity to learn advanced remote sensing techniques and who are curious about how remote sensing really works.

Learning Objectives:

  • Verbally and mathematically describe interactions between electromagnetic radiation and matter.
  • Integrate conceptual and mathematical descriptions of interactions with remote sensing applications.
  • Students will complete a remote sensing project using the skills acquired throughout the course.