"Education is not the learning of facts, but the training of the mind to think. It is the supreme art of the teacher to awaken joy in creative expression and knowledge."

                                                                                                                      — Albert Einstein

Assistant Teaching Professor

GEOG 582 AI in Geospatial Data Science

GEOG 589 Emerging Trends in Remote Sensing

This course focuses on the scientific and technical challenges that lie at the intersection of spatial data science and artificialintelligence (AI). Geospatial data and geographic visualizations are not readily supported by contemporary AI approaches, butdevelopment in this area of GeoAI is rapidly advancing. Spatial reasoning, spatial analysis, and cartographic design are all potentiallyaided via the use of AI in the near future. Students will engage with key theories, methods, and systems to develop new workflowsthat enable geospatial problem solving with the support of AI. Students will engage with emerging literature to contextualize andcritique ongoing scientific progress towards achieving GeoAI goals. They will also develop customized solutions for AI-supported spatial data science tasks through lab exercises. These labs will allow students the opportunity to create and evaluate AI-supportedspatial data science workflows with an emphasis on reproducibility and ethical responsibility. A culminating project in the class willallow students to create a new AI-supported spatial data science solution for a real-world application 

Exploring Imagery and Elevation Data in GIS Applications focuses on the use of remotely sensed imagery and elevation data in GIS applications. Students enrolling in GEOG 480 should have a solid conceptual foundation in geospatial information science and technology. This course is appropriate for those who are already working in the geospatial profession and wish to use imagery and elevation data in visualization and spatial analysis. Throughout the course, students confront realistic remote sensing problem scenarios that incorporate such skills and concepts as definition of data needs, metadata content standards, data formats and types, and analysis methods.

In this course you will encounter emerging tools, techniques, and sensors in the remote sensing industry, engaging with the scientific literature, guest lecturers from the remote sensing industry, and hands-on activities that focus on the state-of-the-art in remote sensing and image analysis. The focus for a given semester will be adapted based on emerging methods, technologies, and high-impact real-world contexts. Examples of the topics include bathymetric and waveform lidar, synthetic aperture radar, oblique aerial imagery, and Geiger-Mode lidar. You’ll have the chance to explore topics like these on a one-on-one basis with leaders in the profession while at the same time establishing a network of resources for staying ahead of future trends in remote sensing.