Physical Principles of Remote Sensing

What you will learn

On successful completion of this course you will be able to:

• Define the primary physical quantities that are directly related to measured radiance,
• Discuss the nature of surface and atmospheric interactions with electromagnetic radiation,
• Describe how satellite images are formed and explain the physical relations underlying the retrieval of satellite measured reflectance, temperature and backscattering coefficients,
• Analyse the complete remote sensing process from data reception to information extraction, including applying calibration and atmospheric correction methods to image data,
• Explain a wide range of image processing techniques and the underlying mathematical principles,
• Select appropriate image processing sequences to achieve predetermined objectives,
• Operate and manage an image processing system,
• Integrate image processing techniques into applications of remote sensing.

Core content

Physical principles

• Electromagnetic radiation: radiometric units and terms, radiation laws, radiation sources optical, thermal and microwave,
• Atmospheric interactions and correction,
• Surface interactions and interpretation of spectral response patterns,
• Plant, soil and water spectral properties,
• Image formation and collection,
• Image formation: passive systems (detectors, opto-mechanical line scanners, waveband separation, linear and area arrays) and active systems (Lidar, RAR and SAR concepts),
• Spatial resolution and geometry,
• Orbits and platforms,
• Review of satellite and airborne systems,
• Data reception and distribution: data suppliers, product levels, internet.

Image processing and analysis

• Calibration: DN to radiance, irradiance standards, calibration methods. Radiometric, spectral and spatial image enhancement. Contrast stretching (linear, bilinear, gaussian, histogram equalisation and manual), digital filtering in the spatial domain (low-pass, high-pass, high-boost, median and directional),
• Band algebra: Derivation of soil and vegetation indices: ratios, normalised differences, PVI, SBI, tasselled cap concept,
• Geometric correction: map projections, selection of ground control points, transform equations, resampling methods (nearest neighbour, bilinear interpolation, cubic convolution),
• Supervised and unsupervised image classification: parametric and non-parametric techniques, clustering, segmentation, pixel and object-based approaches, machine learning and validation (accuracy assessment),
• Post processing, processing chains, change detection, cloud computing and applications.

Upgrade to a professional qualification

Speakers

Dr Toby Waine

Accommodation options and prices

This is a non-residential course. If you would like to book accommodation on campus, please contact Mitchell Hall or Cranfield Management Development Centre directly. Further information regarding our accommodation on campus can be found here.

Alternatively you may wish to make your own arrangements at a nearby hotel.

Location and travel

Cranfield University is situated in Bedfordshire close to the border with Buckinghamshire. The University is located almost midway between the towns of Bedford and Milton Keynes and is conveniently situated between junctions 13 and 14 of the M1.

London Luton, Stansted and Heathrow airports are 30, 90 and 90 minutes respectively by car, offering superb connections to and from just about anywhere in the world. 

Location address