This introductory remote sensing course provides an introduction to the physical principles of satellite remote sensing, and basic remote sensor data processing. In particular, this includes: (i) examining the basic physics of electromagnetic (EM) radiation and the complex interactions of radiation with the atmosphere and surface, (ii) examining the characteristics of the EM radiation (spectral signatures) across regions of the EM spectrum for various surface targets, (iii) reviewing the main resolutions of a sensor system, types of sensors (passive and active), remote sensing platforms (ground-based, airborne and spaceborne) and satellite remote sensing missions, (iv) basis for interpretation of remote sensing images, (v) hands-on basic remote sensor data processing i.e. performing image corrections for common sources of error in satellite imagery, and performing image enhancement and image classification in-order to generate thematic information. In particular, the classification of images will entail applying selected vegetation indices, supervised pixel- and supervised object-based classification techniques to the provided image data sets; followed by verification of classification results by constructing an error assessment matrix. Furthermore course will also cover various online remote sensor data archives where imagery of varying resolution characteristics can be obtained free of charge.

After completion of the course, delegates will

• understand and describe the key theoretical components involved in the remote sensing data collection process such as, energy sources, energy-terrain-atmosphere interactions, platforms and sensor resolution characteristics spanning multispectral and hyperspectral;
• search, order and download satellite imagery (free of charge) from various online data catalogues;
• satellite imagery exploration and statistical evaluation of raw multispectral data sets using ENVI software, in-terms quality assessment and influence of the varying four sensor resolutions (i.e. spatial, spectral, radiometric and temporal);
• Carry-out basic image correction procedures such as geometric, radiometric and atmospheric corrections as well as enhancement using ENVI and Snap software
• Apply and compare supervised pixel-based and object-based image classification methods using high (2-10 m) to ultra-high (1-5cm) spatial resolution multispectral imagery. Extract meaningful information and prepare a thematic map coupled with classification accuracy statistics;
• Know wide variety of applications of remote sensing e.g. in thermal, vegetation, water, soil and minerals, urban - as well as the characteristics of the full electromagnetic spectrum and wavelength selection for mapping of certain targets.

The following topics will be covered:
1. Overview of Remote Sensing of the Environment; Basic theory of electromagentic radiation (ER) and interaction of ER with the terrain features and atmosphere;Multispectral, Hyperspectral and Lidar remote sensing systems, and platforms;
2. Image pre-processing, enhancement, classification and accuracy assessment and 
3. Applications of remote sensing