• GEOG 3963: Special Topics

  1.00 - 5.00 Credits

  University of Utah

  
  Lecture, special topics. Generally offered on a one-time basis depending on faculty/instructor availability and interests. Different topics and titles.
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• GEOG 4140: Advanced Methods in GIS

  4.00 Credits

  University of Utah

  
  Graduate students should enroll in GEOG 6140 and will be held to higher standards and/or more work. This course explores the practice of using a geographic information system (GIS) to support geographic inquiry and decision making. Students will strengthen their technical knowledge of the common tasks that a geographic analyst faces in applying a GIS to a variety of spatial problems. The lab sections offer an opportunity to gain hands-on experience using a leading commercial GIS to complete a series of real-world projects. Prerequisites: 'C' or better in GEOG 3100
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• GEOG 4150: Geospatial Big Data

  4.00 Credits

  University of Utah

  
  Our society collects data at increasing volume, velocity, and variety due to rapidly advancing technologies such as social media, GPS, mobile devices, and remote sensing. Big data may contain crucial information for solving issues in the natural and social sciences, environment, inequality, public health, or engineering. However, our ability to make sense of the constant data stream is lagging behind our ability to collect and store it. For instance, geographic data cannot be analyzed easily using standard GIS or database software. In this course, you learn three essential skills for solving geographic problems using big data and modern computing infrastructure: 1) managing geospatial data (database), 2) leveraging the web (web GIS), and 3) using cloud-based computing services (cloud computing). We focus on the fundamentals of database design and data management to support GIS and other spatial applications. With the internet being the main source of information and communication for many people, the demand for accessing information via maps is increasing at a rapid pace. GIS is quickly moving towards a web-based environment where everyone can access GIS data/functionality regardless of location and GIS skill level. This course provides an overview of web GIS and associated techniques to leverage web technologies for spatial analysis. Cloud computing is a fundamental component of modern IT infrastructure and application design. You learn about the design and implementation of cloud computing environments and apply the concepts in a lab environment. Prerequisites: 'C' or better in GEOG 4140
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• GEOG 4165: Data Visualization

  3.00 Credits

  University of Utah

  
  Many aspects of our world are very complex. Scientists collect data on issues like climate change, gentrification, or disease epidemics to understand them and guide response. However, these data are too large to grasp, too convoluted to decipher, or too noisy to comprehend. Visualization provides a way of combating information overload, as a well-designed graph, map or chart can help to understand large, complex data streams. Furthermore, visualization is an inclusive way of communication and therefore, engages diverse audiences in the process of analytic thinking. In this class, students learn a definition and brief history of data visualization, including its fundamental concepts. In addition, we will review and learn the skills/tools that are relevant in working with visualization environments, using state-of-the-art software tools and techniques. Prerequisites: 'C' or better in GEOG 4150
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• GEOG 4999: Honors Thesis/Project

  3.00 Credits

  University of Utah

  
  Restricted to students in the Honors Program working on their Honors degree. Prerequisites: Instructor Consent.
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• GEOG 5110: Remote Sensing Analysis

  3.00 Credits

  University of Utah

  
  Graduate students should enroll in GEOG 6110 and will be held to higher standards and/or more work. High-resolution multispectral data, coupled with expanding computing power and increasingly sophisticated image processing software, provides a large set of quantitative, graphic, and science visualization tools for solving science-based environmental problems using remote sensing data. The theory and application of image-processing techniques such as data corrections, enhancements, transformations, and classification are aimed at specific environmental problems in the natural and human domains. Hands-on experience is gained through image processing laboratory techniques and real-world science projects. Prerequisites: "C" or better in GEOG 3110.
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• GEOG 5120: Adv Opti Remote Sensing

  3.00 Credits

  University of Utah

  
  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 IR, thermal IR, 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 to the opportunity to learn advanced remote sensing techniques and who are curious about how remote sensing really works. Prerequisites: "C" or better in GEOG 5110.
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• GEOG 5130: Adv Actv Remote Sensing

  3.00 Credits

  University of Utah

  
  Graduate students should enroll in GEOG 6130 and will be held to higher standards and/or more work. Active remote sensing uses radar or laser energy emitted by satellites or aircraft to measure and image the Earth's surface. Synthetic aperture radar (SAR) and lidar remote sensing permit precise measurement of surface height and changes in surfaces over time, enabling diverse applications such as glacier movement, ground displacement, and forest biomass. SAR also offers images of the earth's surface that provide information not available with traditional visible and infrared satellite sensors and the ability to image through clouds and darkness. This course covers theory and applications of active remote sensing using a combination of lectures and project-based learning. Prerequisites: "C" or better in GEOG 5110.
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• GEOG 5131: Capstone in RS

  3.00 Credits

  University of Utah

  
  Prerequisites: 'C' or better in GEOG 3100 AND GEOG 5110
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• GEOG 5160: Spatial Data Science

  3.00 Credits

  University of Utah

  
  Graduate students should enroll in GEOG 6160 and will be held to higher standards and/or more work. This course is designed to build from GEOG 3160 (Introduction to Spatial Data Science) by covering more advanced topics. These will include greater detail on the algorithms used in machine learning, the use of hyperparameter tuning, deep learning and the use of dashboards to communicate results. Most topics will be introduced as a case study, allowing discussion of the methods, results and choices taken in developing the analysis. Topic will include a mix of video lectures and in-class demonstrations, followed by a hands-on lab where students can walk through the analysis using Python or R. In addition, students will be required to carry out a short spatial data science project and present the results to the class. Prerequisites: 'C' or better in GEOG 3160 AND GEOG 4140
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