Hyperspectral and Multispectral Imaging Training
Course Authors
Hyperspectral and Multispectral Imaging Training Hands-on (Online, Onsite, and Classroom Live)
| Commitment | 3 days, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
Hyperspectral and Multispectral Imaging Training are 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 the government and industry, and the types of data processing used for various applications. Case studies of applications will be used throughout the course. After taking this course, students should be able to communicate and work productively with other professionals in this field.
WHAT'S INCLUDED?
- 3 days of Hyperspectral and Multispectral Imaging Training with an expert instructor
- Hyperspectral and Multispectral Imaging Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- Hyperspectral and Multispectral Imaging – https://www.wiley.com/
- Hyperspectral and Multispectral Imaging – https://www.packtpub.com/
- Hyperspectral and Multispectral Imaging – https://store.logicaloperations.com/
- Hyperspectral and Multispectral Imaging Training – https://us.artechhouse.com/
- Hyperspectral and Multispectral Imaging – https://www.amazon.com/
RELATED COURSES
ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completing this Hyperspectral and Multispectral Imaging course, learners will be able to meet these objectives:
- The properties of remote sensing systems
- How to match sensors to project applications
- The limitations of passive optical remote sensing systems and the alternative systems that address these limitations
- The types of processing used for the classification of image data
- Evaluation methods for spatial, spectral, temporal, and radiometric resolution analysis
CUSTOMIZE IT
- We can adapt this Hyperspectral and Multispectral Imaging Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this Hyperspectral and Multispectral Imaging course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the Hyperspectral and Multispectral Imaging course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the Hyperspectral and Multispectral Imaging course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
The target audience for this Hyperspectral and Multispectral Imaging course:
- All
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this Hyperspectral and Multispectral Imaging course are:
- N/A
COURSE SYLLABUS
- Introduction to Multispectral and Hyperspectral Remote Sensing
- Sensor types and characterization. Design trade-off applications
- Optical properties for remote sensing.
- Sensor modeling and evaluation. Spatial, spectral, and radiometric
- Multivariate Data Analysis. Scatterplots, the impact of sensor performance on data characteristics
- Assessment of unique signature characteristics. Differentiation of water, vegetation, soils, and urban infrastructure.
- LIDAR systems and applications.
- Hyperspectral Data Analysis. Frequency band selection and band combination assessment
- Matching sensor characteristics to study objectives. Sensor matching to specific application examples
- Classification of Remote Sensing Data. Supervised and unsupervised classification; Parametric and non-parametric classifiers
- Application case studies. Application examples used to illustrate principles and show in-the-field experience
.
