Introductory Remote Sensing: Physical Principles and Digital Image Processing
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Brief Description:
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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.
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Learning Outcomes:
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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.
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Course Content:
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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
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Entry Requirements:
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The candidate must have: a) basic statistics background and b) worked with at least one GIS or Remote sensing software. |
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Course Number:
P007118
Catalogue Category:
Environmental and Natural Sciences
Who Should Attend:
Professionals, managers and scientists who are beginners, having the appetite to acquire knowledge and skills in executing the remote sensing process by extracting meaningful information from remotely-sensed (i.e. satellite/aerial) multispectral imagery e.g. imagery acquisition, processing, analysis and reporting.
Delivery Mode:
Contact
Contact Days:
3
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E-mail address:
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Telephone number:
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+27(0) 12 434 2500
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Fax number:
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+27(0) 12 434 2505
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Website:
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