Remote sensing is a cutting-edge technology that allows us to observe and understand our planet like never before. At Geo-ICT, our Remote Sensing Course blends scientific theory with hands-on training to give you the skills needed to work with data from satellites and airborne sensors. Whether you’re in environmental monitoring, urban development, agriculture, or disaster response, this course teaches you how to collect, analyze, and interpret spatial data using industry-standard tools like Erdas Imagine.
Remote Sensing
Earth ObservationEarth Observation
Remote Sensing
Remote sensing has become an essential tool for observing and understanding the Earth from a distance. By capturing information through sensors mounted on satellites and aircraft, it enables us to monitor the planet’s surface, atmosphere, and subsurface without direct contact. This technology plays a vital role in tracking environmental conditions, supporting land management, and informing decisions across various disciplines—from agriculture to climate science.
Its importance continues to grow across public and private sectors. Remote sensing supports large-scale environmental assessments, urban development, emergency response, and sustainable resource planning. At the heart of this method is the interaction between electromagnetic radiation and Earth’s surface, which allows us to detect features, track changes, and analyze patterns over time.
Geo-ICT’s Remote Sensing Course is designed to prepare professionals with both the theoretical foundation and practical expertise to work with remote sensing technologies. You’ll learn how to interpret satellite imagery, use multispectral data, and apply key analytical tools like Erdas Imagine. Whether you’re looking to deepen your knowledge or expand your capabilities in spatial analysis, this course offers the skills you need to succeed in a fast-evolving field.
What will you learn
You’ll begin by exploring the fundamentals of remote sensing—how energy interacts with Earth’s surface and how sensors capture this data. You’ll study the electromagnetic spectrum, learn to identify different sensor types, and understand how remote sensing platforms acquire and transmit data.
Next, the course moves into more advanced techniques. You’ll work with multispectral analysis, photogrammetry, radar, lidar, and thermal imagery. Using Erdas Imagine, you’ll process satellite images, apply image enhancements, and extract useful insights.
You’ll also dive into classification methods, object-based image analysis, and time-series applications. Through practical exercises, you’ll assess environmental conditions, detect land cover changes, and interpret imagery to support decisions in areas like agriculture, climate, and spatial planning.
Why choose this course
This course is ideal if you’re looking to build practical skills in one of the fastest-growing areas of spatial science. Here’s what sets it apart:
- Expert instruction: Learn from experienced professionals with real-world expertise in remote sensing and geospatial analysis.
- Hands-on experience: Gain practical skills with software like Erdas Imagine that’s used across the industry.
- Job-market relevance: Apply your knowledge in high-impact fields such as urban planning, environmental monitoring, and agriculture.
- Balanced curriculum: Build a strong foundation in theory while applying what you learn through guided exercises and projects.
Course structure
Day 1
You’ll start with the basics: the history, principles, and evolution of remote sensing. You’ll explore how remote sensing connects to other spatial technologies, and learn about aerial photography, photogrammetry, and common data sources for satellite imagery.
Day 2
The focus shifts to the electromagnetic spectrum and radiation theory. You’ll study the characteristics of various satellite platforms and sensors, and learn how to orthorectify satellite images. Topics include radar, lidar, and hyperspectral data, as well as photogrammetric point clouds.
Day 3
You’ll apply advanced image analysis techniques, including filtering, classification, and object-based image analysis. You’ll also explore the use of machine learning, time-series analysis, and change detection in practical applications related to vegetation, water, air, and soil monitoring.
Learning Outcomes
- Understand the full remote sensing process, from data acquisition to analysis and real-world application
- Gain practical knowledge of key technologies, including multispectral, thermal, radar, lidar, and photogrammetry
- Build skills in image analysis and interpretation using tools like Erdas Imagine
- Understand how collaborative roles—from engineers to policymakers—contribute to remote sensing projects
- Apply remote sensing techniques to real-world challenges in agriculture, environmental monitoring, and spatial planning
More Information?
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
Frequently Asked Questions about Remote Sensing
Remote sensing is the process of collecting data about objects or areas from a distance, typically using satellite or aerial technologies. It involves capturing images and other information about the Earth’s surface or atmosphere without making physical contact with the area being observed.
Key components of remote sensing include:
- Sensors: Devices on satellites, airplanes, or drones that detect radiation or light reflected or emitted from the Earth’s surface. These sensors capture data in various forms such as optical, infrared, microwave, or radar signals.
- Platforms: These are the carriers for the sensors, like satellites, aircraft, drones, or even ground-based equipment.
- Data Processing: The raw data collected by sensors needs to be processed and analyzed to extract useful information, such as detecting land use changes, monitoring vegetation, mapping natural resources, or predicting weather patterns.
Types of Remote Sensing
- Passive Remote Sensing: This type relies on natural energy, usually sunlight, which is reflected or emitted from the surface. Optical and infrared imaging are common forms of passive sensing.
- Active Remote Sensing: In this type, sensors emit their own energy and measure the reflection or return of this energy from the Earth’s surface. Radar and LiDAR (Light Detection and Ranging) are examples of active remote sensing.
The Remote Sensing Course is typically intended for a wide range of individuals and professionals, including:
- Students and Researchers: Those studying geography, environmental science, geology, agriculture, urban planning, or related fields who want to learn how to use remote sensing techniques for research purposes.
- Environmental and Earth Scientists: Professionals working in environmental monitoring, conservation, or climate studies who use satellite data to track changes in ecosystems, weather patterns, or natural resources.
- GIS (Geographic Information Systems) Specialists: Individuals involved in mapping and spatial analysis who want to integrate remote sensing data into their work for more accurate and comprehensive analysis.
- Agriculture Professionals: Farmers, agronomists, and agricultural consultants interested in precision farming, crop monitoring, and resource management using remote sensing data.
- Urban Planners and Civil Engineers: Those who need to analyze urban development, infrastructure planning, and land use changes through remote sensing technologies.
- Disaster Management and Humanitarian Workers: Individuals involved in disaster response and management, who need real-time or historical remote sensing data to assess areas affected by natural disasters like floods, earthquakes, or hurricanes.
- Professionals in Defense and Security: Military and security personnel who use remote sensing for surveillance, reconnaissance, and geographic intelligence.
- Forestry and Natural Resource Managers: Those who monitor forest health, land degradation, and resource use, relying on remote sensing to manage natural environments.
We mainly use Erdas software and various image analysis tools. These are essential for processing and interpreting Remote Sensing data.