Optical and Remote Sensors Training

Commitment 3 days, 7-8 hours a day.
Language English
User Ratings Average User Rating 4.8 See what learners said
Delivery Options Instructor-Led Onsite, Online, and Classroom Live


Optical and Remote Sensors Training reviews the underlying technology areas used to construct and operate space-based optical sensors, laser, and radar systems. The Optical and Remote Sensors course presents background information to allow an appreciation for designing and evaluating space-based sensing systems. The Optical and Remote Sensors Training course provides a broad introduction to a wide range of optical sensing systems with specific examples. Fundamental descriptions are given for various optical sensing systems, and, details associated with space applications are presented. System requirements are developed and the methodology of system component selection is given. Design considerations for space-based optical sensors are discussed and case studies describing previous and current space instrumentation are presented. Example systems will be discussed, along with applications and future directions.

  • 3 days of Optical and Remote Sensors Training with an expert instructor
  • Optical and Remote Sensors Electronic Course Guide
  • Certificate of Completion
  • 100% Satisfaction Guarantee



Upon completing this Optical & Remote Sensors 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.
  • We can adapt this Optical & Remote Sensors course to your group’s background and work requirements at little to no added cost.
  • If you are familiar with some aspects of this Optical and Remote Sensors course, we can omit or shorten their discussion.
  • We can adjust the emphasis placed on the various topics or build the Optical and Remote Sensors 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 Optical and Remote Sensors course in a manner understandable to lay audiences.

The target audience for this Optical & Remote Sensors Training course:

  • All

The knowledge and skills that a learner must have before attending this Optical and Remote Sensors course are:

  • N/A


  1. Introduction. The fundamentals of remote sensing, remote sensing sensors, detectors, the electromagnetic spectrum, and characteristics of space remote sensing systems.
  2. The History and Origins of Space Remote Sensing. The origins of space remote sensing, the origins, history, and current state of the Canadian remote sensing community, dual-use issues, ISS systems, the remote sensing process, remote sensing sensor design and development, visible and IR sensing, passive electro-optical systems, multispectral and hyperspectral sensing, international organizations and structures, remote sensing satellite orbits, etc.
  3. Optical Remote Sensing Sensors. Sensors and detectors, electromagnetic spectrum, Wien’s displacement law, Planck’s general equation, quantum photons, types of sensors, radiant energy, flux and intensity, and radiance, scanner designs, single detectors, push broom and two-dimensional arrays, framing and scanning systems, cross-track and along-track sensors, instantaneous field of view, optical vs. microwave, passive vs active sensors, radiometers, spectrometers, and imaging sensors, spatial, radiometric, temporal and spectral resolution, the electromagnetic energy budget, ultra-high resolution systems, etc.
  4. LiDAR Systems. The fundamentals of LiDAR, laser remote sensing, pulsed and continuous wave systems, history and development, UV, visible and Near IR systems, airborne and space systems, LiDAR applications, data processing, and unique data analysis and processing issues, creating Digital Elevation Models (DEMs) with LiDAR systems, space systems and applications, CMOS and hybrid CMOS/CCD systems, atmospheric and meteorology, Doppler LiDAR and Rayleigh Doppler LiDAR systems, scanning LiDAR systems.
  5. 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.
  6. 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.
  7. Applications. Space and airborne remote sensing applications, local, regional, and global applications, and land, water, and atmospheric applications
  8. 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, data presentation, data archiving, and metadata.
  9. 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.
Optical and Remote Sensors TrainingOptical and Remote Sensors Training Course Wrap-Up