ATI's Hyperspectral and Multispectral Imaging course

Summary: This three-day class is designed for engineers, scientists and other remote sensing professionals who wish to become familiar with multispectral and hyperspectral remote sensing technology. Students in this course will learn the basic physics of spectroscopy, the types of spectral sensors currently used by government and industry, and the types of data processing used for various applications. Lectures will be enhanced by computer demonstrations. After taking this course, students should be able to communicate and work productively with other professionals in this field. Each student will receive a complete set of notes and the textbook/CD Rom set, Imaging Spectrometry, Basic Principles and Prospective Applications. Instructor: Dr. Richard Gomez is a Research Professor at George Mason University (GMU) and Principal Research Scientist at the Center for Earth Observing and Space Research (CEOSR). At GMU he teaches and is actively involved in the scientific and technology fields of hyperspectral imaging and high resolution remote sensing. He has also served in industry and government (Texas Instruments and USACE). Dr. Gomez is internationally recognized as a leader and expert in the field of spectral remote sensing (multispectral, hyperspectral and ultraspectral) and has published extensively in scientific journals. He has organized and chaired national and international conferences, symposia and workshops. He earned his doctoral degree in physics from New Mexico State University. He also holds an M.S. and a B.S. in physics. Dr. Gomez currently serves as Director for the ASPRS Potomac Region and as Remote Sensing Chair for the IEEE-USA Committee on Transportation and Aerospace Technology Policy. What You Will Learn: The limitations on passive optical remote sensing. The properties of current sensors. Component modeling for sensor performance. How to calibrate remote sensors. The types of data processing used for applications such as spectral angle mapping, multisensor fusion, and pixel mixture analysis. How to evaluate the performance of different hyperspectral systems. Course Outline: Introduction to multispectral and hyperspectral remote sensing. Sensor types and characterization. Design tradeoffs. Data formats and systems. Optical properties for remote sensing. Solar radiation. Atmospheric transmittance, absorption and scattering. Sensor modeling and evaluation. Spatial, spectral, and radiometric resolution. Statistics for multivariate data analysis. Scatterplots. Impact of sensor performance on data characteristics. Spectral data processing. Data visualization and interpretation. Radiometric calibration. Partial calibration. Relative normalization. Image registration. Resampling and its effect on spectral analysis. Data and sensor fusion. Spatial versus spectral algorithms. Classification of remote sensing data. Supervised and unsupervised classification. Parametric and nonparametric classifiers. Application examples. Hyperspectral data analysis. Tuition: Tuition for this three-day course is $1490 per person at one of our scheduled public courses. Onsite pricing is available. Please call us at 410-956-8805 or send an email to ati@ATIcourses.com. Register Now Without Obligation