Remote Sensing and Satellite Imagery Analysis Training Course
Turn freely available satellite imagery into land cover, vegetation and change detection insight.
5 Days
Duration
Certificate
Included
Instructor-Led
Delivery
Intermediate
Level
Remote Sensing and Satellite Imagery Analysis Training Course
Starting From
$800
per participant
Flexible Delivery
In-Person, Live Online
Language
English
Dedicated Support
Pre & post training
Course Overview
This intermediate course develops technical skills in remote sensing and satellite imagery analysis, covering imagery sourcing, preprocessing, spectral index calculation and land cover classification. Participants work hands-on with real satellite imagery throughout, using freely available Sentinel and Landsat data rather than pre-processed samples, building the judgement to assess their own analysis critically. The course closes with a land cover classification and change detection analysis for a defined area of interest.
Introduction
Freely available satellite imagery from missions like Sentinel and Landsat has transformed what is possible for organisations without their own remote sensing budgets, but sourcing, preprocessing and correctly interpreting that imagery requires specific technical skills that basic GIS training does not cover.
Remote sensing sits at the intersection of image processing and spatial analysis, and practitioners who skip the fundamentals often produce classifications and indices that look plausible but do not hold up to scrutiny. This intermediate course builds remote sensing skills systematically, from sourcing and preprocessing imagery through to classification and change detection, so participants understand what their analysis is actually showing.
Learning Objectives
By the end of this course, participants will be able to:
- Explain the fundamentals of remote sensing and satellite sensor types
- Source and download freely available satellite imagery
- Preprocess satellite imagery for analysis
- Calculate spectral indices for vegetation, water and built-up areas
- Perform supervised and unsupervised land cover classification
- Assess classification accuracy against reference data
- Conduct change detection analysis across multiple time periods
- Interpret false colour composites and band combinations
- Integrate remote sensing outputs into broader GIS analysis
Who Should Attend
This course is suitable for:
- M&E and research staff working with satellite imagery
- Environmental and natural resource management staff
- Agricultural monitoring and early warning staff
- Disaster risk and climate resilience programme staff
- Urban and land use planning staff
- Conservation and protected area management staff
- Researchers incorporating remote sensing into evaluation design
- GIS analysts progressing beyond basic mapping skills
Training Methodology
The programme is delivered through facilitator-led hands-on sessions working with real satellite imagery inside QGIS, structured around progressive exercises rather than lecture alone. Each module closes with a short applied task so participants leave with working remote sensing skills rather than notes alone.
Organizational Impact
Institutions sending staff on this course can expect:
- Reduced dependence on external consultants for remote sensing analysis
- Improved use of freely available satellite imagery for programme monitoring
- Stronger land cover and vegetation monitoring capability
- More credible change detection analysis over time
- Reduced risk of remote sensing outputs that do not withstand scrutiny
- Improved integration of remote sensing into broader M&E and planning work
- Increased in-house geospatial analytical capability
- A documented, reusable remote sensing analysis approach
- Cost savings from reduced reliance on commercial imagery and analysis services
Personal Impact
By the end of this course, participants gain:
- Advanced technical skill in satellite imagery sourcing and analysis
- Confidence to calculate and interpret spectral indices
- Sharper land cover classification skills
- Practical experience conducting change detection analysis
- Stronger standing in remote sensing and spatial analysis discussions
- A completed classification and change detection analysis for direct application
- Improved ability to assess classification accuracy critically
- A specialist skill set distinguishing them from basic GIS users
- A foundation for progressing into advanced spatial statistics
Course Outline
- Fundamentals of remote sensing and satellite sensor types
- Understanding spatial, spectral and temporal resolution
- Sourcing freely available satellite imagery
- Downloading and organising Sentinel and Landsat data
- Understanding electromagnetic spectrum bands and their uses
- Loading and displaying satellite imagery in QGIS
Practical session: source, download and load satellite imagery for a defined area of interest.
- Preprocessing satellite imagery for analysis
- Atmospheric correction considerations
- Building true colour and false colour composites
- Interpreting different band combinations
- Managing cloud cover and image quality issues
- Clipping and mosaicking imagery for an area of interest
Practical session: build and interpret false colour composites for a defined area of interest.
- Calculating vegetation indices for crop and vegetation health
- Calculating water and moisture indices
- Calculating built-up and urban indices
- Interpreting spectral index outputs
- Managing index calculation across multiple imagery dates
- Common spectral index interpretation errors
Practical session: calculate and interpret a vegetation index for a defined area of interest.
- Supervised classification methodology
- Unsupervised classification methodology
- Building and using training and validation data
- Assessing classification accuracy
- Comparing classification approaches and their trade-offs
- Common land cover classification errors
Practical session: perform a land cover classification and assess its accuracy against reference data.
- Conducting change detection analysis across time periods
- Interpreting change detection results credibly
- Integrating remote sensing outputs into broader GIS analysis
- Communicating remote sensing findings to non-technical audiences
- Common pitfalls that undermine remote sensing credibility
- Building a land cover classification and change detection analysis
Practical session: build a land cover classification and change detection analysis for a defined area of interest.
Certification
At Strategic Revenue Africa, our certification goes beyond proof of attendance—it represents practical competence and measurable capability. Upon successful completion of our training programs, participants are awarded a Certificate of Completion from Strategic Revenue Africa, recognizing their ability to apply acquired knowledge in real-world settings. As an organization focused on architecting sustainable revenue and strengthening organizational performance, our certifications signal that participants are equipped with skills that drive results, not just theory.
Programme Inclusions
- Course materials & workbook
- Certificate of completion
- Post-training support (6 months)
Prerequisites
Prior QGIS experience is expected, equivalent to completing a QGIS fundamentals course. No prior remote sensing experience is required.
Schedule & Investment
Upcoming Dates & Fees
Accommodation & Transfer
Accommodation and airport transfer are arranged upon request. Contact the Training Officer to reserve.
Payment
Transfer payment to the Strategic Revenue Africa account before the course starts. Send proof of payment to:
[email protected]Course Fee Includes
- Course tuition & training materials
- Two break refreshments and lunch
- Certificate of completion
- Post-training support (6 months)
Travel, visa, insurance and personal expenses are the participant's responsibility.
Frequently Asked Questions
About Remote Sensing and Satellite Imagery Analysis Training Course
M&E and research staff, environmental and natural resource management staff, agricultural monitoring staff and conservation staff working with satellite imagery.
No prior remote sensing experience is required, but prior QGIS experience equivalent to a fundamentals course is expected.
The course focuses on freely available imagery from missions like Sentinel and Landsat, keeping the skills accessible without ongoing licensing costs.
Yes. A dedicated module covers assessing classification accuracy against reference data with a hands-on exercise.
Yes. The final module covers change detection methodology and interpreting results credibly.
Yes. The final exercise produces a land cover classification and change detection analysis for a defined area of interest.
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