This course focuses on computer-based methods for information extraction from remotely sensed data to support geographic inquiries in environmental and social domains. It comprises three major components: an overview on the remote sensing process and the major remote sensing systems; an in-depth discussion on the major components in digital image processing ranging from preprocessing, image enhancements, thematic information extraction through pattern recognition and artificial intelligence, digital change detection, to thematic accuracy assessment; and an introduction to lidar remote sensing and hyperspectral remote sensing.

The participants will be taken through fundamental definitions such as image, digital image, and digital image processing. Different sources of digital images, image processing to computer vision and image acquisition and different types of image sensors shall be covered.

On completion of the course the successful participants will:

• Be proficient in the use of QGIS/ArcGIS
• Understand and be able to undertake geometric referencing of images
• Understand and be able to display image composites for known purposes.
• Know about the potential of and procedures for image processing in a range of application areas
• Proficiency in image processing as outlined in this course is the basis for:
• Developing advanced image processing techniques
• Using image processing in a very wide array of applications with any type of digital image and with a range of software products

Important Dates
Classroom Training Calendar 2026

Online Training Calendar 2026

Course content overview

Topics to be covered include:

• Basis of Remote Sensing
• Downloading data from earth explorer, earth data and SCP menu.
• Prospects for development of remote sensing
• Active vs. Passive Remote Sensing
• SCP main menu;
• Region of Interest tool (ROI)
• Masks
• Image registration and orthorectification
• Geometric Correction: image to image and image to map
• Orthorectification;
• Reprojection data.
• Georeferencing and mosaicking
• Automatic contrast
• Mosaicking
• Vector and raster data
• Editing vector data
• Getting information about vector from attribute table
• Spectral Analysis
• Working with spectral libraries
• Spectral Transforms
• Atmospheric and Radiometric Correction
• Thematic processing of remote sensing data
• Supervised and Unsupervised Classification
• Post Classification tools
• Accuracy assessment and ground truthing
• Change Detection Analysis.
• Normalized Difference Vegetation Index (NDVI)
• Mapping

Who should apply for the course.

New users, Planners, GIS experts, Resource managers, Spatial Analysts, remote sensing individuals

Software Used:

QGIS ,ArcGIS, Geosetter ,Google Earth Pro

Certification

Upon successful completion of the course all participants will be issued a certificate at no extra cost.