Spring Semester, Online

Online learning is at its best when it is through carefully crafted courses. The spring semester has a series of one-credit modules that are frequently updated based on what you need. In addition, you will be a master of earth observation by learning advanced image processing techniques and the emerging technologies. While you can learn from anywhere in the world, if you choose to stay in Madison, you can come to campus weekly to meet with your peers and instructors — the choice is yours.

Spring Courses

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Remote Sensing for Conservation & Management (1 credit)

Tools modules for environmental conservation graduate students. Modules will provide training in specific tools and methods related to environmental conservation. Topics may include GIS, conservation finance, conservation governance and institutions, biodiversity monitoring, and science communication and environmental mediating.

Conservation Governance, Institutions, and Legislative Processes (1 credit)

Tools modules for environmental conservation graduate students. Modules will provide training in specific tools and methods related to environmental conservation. Topics may include GIS, conservation finance, conservation governance and institutions, biodiversity monitoring, and science communication and environmental mediating.

Conservation Grant Writing (1 credit)

Tools modules for environmental conservation graduate students. Modules will provide training in specific tools and methods related to environmental conservation. Topics may include GIS, conservation finance, conservation governance and institutions, biodiversity monitoring, and science communication and environmental mediating.

Statistics: Methods for Spatial Data (1 credit)

Detecting and quantifying spatial patterns and modeling in the presence of such patterns. Spatial Point Patterns: testing nonrandomness, simulating and characterizing patterns. Lattice Data: spatial autocorrelation and regression. Geostatistics: variograms, ordinary and universal kriging, inference, assessing assumptions, and extensions.

Environmental Sensing Technologies (3 credits)

Many diverse technologies for monitoring the environment have become available in recent years, including traditional remote sensing data sources: aerial photography and satellite imagery, hyper-spectral data, imagery on demand, RADAR and LiDAR. Other new data sources are quite unconventional, with many emerging relatively recently: unmanned aerial vehicles (UAVs or drones), social media, smartphones as sources of crowd-sourced data, and more.

Sophisticated data management, analytics, and presentation technology are required to effectively leverage both the spatial (including 3D) and temporal dimensions of these often untapped data sources. Intended to survey and explore these newly developing technologies, and provide direct experience to the student to understand and interact with the data and methods (geocomputing, coding, cloud-based platforms), and to learn to plan, manage, and utilize them effectively.

Advanced Remote Sensing (3 credits)

Focuses on the fundamental physical principles of terrestrial remote sensing, followed by an examination of advanced topics in earth observation and digital image processing. Topics include radiation interaction with the atmosphere and the surface; radiative transfer theory; land surface characteristics including energy balance; thermal sensing; atmospheric and radiometric correction of image data; automated cloud detection and removal.

Applications of remote sensing data for environmental problems will be explored in depth, including biophysical remote sensing with 3D modeling of vegetation canopies, dense time series analysis, data mining techniques, data fusion, as well as object vs. per-pixel approaches to pattern recognition. Explores all major data types, including optical, RADAR, LiDAR, and hyperspectral data, and provide instruction in hands-on image processing using open source software.

Bonus Activities

Spring commencement celebration