Optical Sensors & Remote Sensing Training
Optical Sensors & Remote Sensing Training Course – Hands-on
Optical Sensors & Remote Sensing Training Course – Customize it
- We can adapt this 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 training course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the training 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 training course in manner understandable to lay audiences.
Optical Sensors & Remote Sensing Training Course – Audience/Target Group
The target audience for this training course:
Optical Sensors & Remote Sensing Training Course – Objectives:
Upon completing this training course, learners will be able to meet these objectives:
- What are the fundamentals of optical remote sensing.
- Sensors and detectors for optical remote sensing.
- Active and passive microwave systems.
- LiDAR systems, data and data processing
- End to end data acquisition and processing.
- Optical data, data handling and data formats.
- Calibration and pre-processing of optical data
- Integration of optical remote sensing data with ancillary data in a Geomatics and Geographic Information System
- • Future directions and advances.
- Where the most promising international research is being performed.
Optical Sensors & Remote Sensing Training- Course Content
Microwave Systems-Passive and Active. The fundamentals of microwave remote sensing, passive vs active microwave sensing, microwave sensing design and considerations, SLAR image geometry, incidence angle, scattering mechanisms and specular reflectance, scene illumination, radar bands, layover and foreshortening, dielectric constant, polarization, interferometry, differences between active and passive data, data analysis and data processing, case studies of Canadian RADARSAT, RADARSAT Constellation, and TerraSAR-X, future systems.
Calibration, Noise, Pre-processing and Processing of Optical Remote Sensing Data The end-to-end data processing chain, sensor signal processing, FFT, digital numbers (DNs), data transmission, data calibration, atmospheric scattering and absorption, image restoration, remote sensing data structure and data formats, metadata, data pre-processing, data calibration, atmospheric calibration, geometric registration, coordinate transformations, data processing, modular transfer functions, spatial filters, temporal analysis and time series modeling, thematic classifications, supervised and unsupervised classifications, spectral signatures, accuracy assessment, data fusion, references.
Applications. Space and airborne remote sensing applications, local, regional and global applications, land, water and atmospheric applications
Integration of Data within the Geomatics and GIS Context. Integration of data within the GIS context, data fusion, geomatics, fundamentals of GIS, integration with vector and GNSS point data, the multi-concept, GIS data modeling, final data analysis and data presentation, data archiving and metadata.
Current Status and Future Directions. Future directions for optical remote sensing systems, sensors, data and data processing. New systems such as Planet Labs and Google’s Sky-Box satellites.