Fundamentals of Remote Sensing

How can you use satellite imagery to better understand our environment? In this Blended Learning course, you’ll be introduced to the basic principles of remote sensing and learn how satellites and sensors collect information about the Earth’s surface. You’ll work with up-to-date Earth observation data from sources such as the European Copernicus Sentinel missions and learn how to view, interpret, and analyze this data using open-source tools like QGIS.
This will help you build a broad foundation for applying remote sensing and for further specialization in the field of Remote Sensing and Satellite Data.

What types of problems will you learn to solve in the Remote Sensing Fundamentals course?

What information can you extract from satellite images about the Earth’s surface and changes to it?
Which satellite data are suitable for a specific spatial problem?
How do you identify and explain differences between water, vegetation, soil, buildings, and other forms of land cover?
How do spatial, spectral, and temporal resolutions influence what you can and cannot infer from satellite data?
How do you combine satellite data with other geodata to reliably analyze a spatial issue?

During this Blended Learning course, you’ll learn how to use remote sensing to observe areas, identify spatial patterns, and analyze changes on the Earth’s surface. You’ll discover how satellite observations are made, what information different sensors provide, and how to translate satellite data into usable geospatial information for a variety of applications.

The Theory Behind Remote Sensing

A thorough analysis of satellite data begins with an understanding of how satellites and sensors observe the Earth. You’ll learn how electromagnetic radiation interacts with water, vegetation, soil, and built-up areas, and why this interaction allows different materials to be distinguished from one another in satellite images.

You’ll also be introduced to key concepts such as spectral bands, reflectance, spatial resolution, spectral resolution, and temporal resolution. You’ll learn how these characteristics determine which satellite data are suitable for a particular problem and what conclusions—and what limitations—you can draw from a satellite image.

Working with Satellite Data and Earth Observation

Satellite data is now widely available for free. You will therefore be introduced to major Earth observation programs and data sources, with a special focus on the European Copernicus program and the Sentinel missions.

You will learn to recognize and evaluate different types of satellite images and discover how optical, multispectral, and radar observations provide different information about the Earth’s surface. In doing so, you will not only learn to interpret satellite images but, more importantly, to determine which data are suitable for addressing a spatial problem.

Analyzing Satellite Data in QGIS

After covering the theoretical foundations, you’ll get hands-on experience with real Earth observation data. You’ll combine satellite images with other geographic data and investigate patterns and differences in the landscape.

You’ll analyze vegetation, water, soil, built-up areas, and land use, among other things, and discover how different spectral bands and image combinations reveal information that isn’t always visible to the human eye. You’ll also be introduced to simple spectral indices and how to compare satellite images from different time periods.

The focus is not on the software itself, but on answering the spatial question: what information do you need, which satellite data are suitable for that purpose, and how do you translate the observations into a reliable conclusion?

From Satellite Images to Actionable Geoinformation

During the Blended Learning program, you’ll work with realistic real-world examples and open-access satellite data. You’ll explore issues encountered by government agencies, consulting firms, research institutions, and organizations working in the fields of water, agriculture, nature, climate, infrastructure, and spatial development.

You’ll work on assignments such as:

Determine which satellite data are most suitable for a spatial issue and justify your choice.
Analyze an area and distinguish between water, vegetation, soil, and built-up areas based on satellite observations.
Investigate how different spectral bands and image combinations provide additional information about the same area.
Compare satellite images from different time periods and identify changes in the landscape.
Combine satellite information with other open geodata to analyze a spatial issue using multiple sources.
Translate the results of a remote-sensing analysis into clear maps, conclusions, and usable geoinformation.

Upon completion, you will have a broad practical foundation for independently evaluating, interpreting, and applying satellite data to spatial issues. You will be able to determine which Earth observation data are suitable for an analysis, thereby laying the groundwork for further specialization in Remote Sensing and Satellite Data.

Enroll

€395,-

Start: 1-hour online session
Self-study: Review course materials
End: 1-hour online session

Register for this course

You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.

Learning Objectives

Interpret satellite and drone imagery to identify spatial patterns, characteristics, and changes on the Earth's surface.
Determine which sensors and observation platforms are suitable for various research questions and understand what information can be collected using them.
Process and analyze image data to extract relevant information from satellite and drone imagery and combine it with other geographic data.
Examining changes in space and time by comparing images taken at different times.
Apply remote sensing to real-world situations in fields such as agriculture, water management, urban development, nature conservation, and environmental monitoring.
Evaluate results from remote sensing analyses and translate them into usable geographic information for monitoring, analysis, and decision-making.

Want to know more?

Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.

FAQs: Blended Learning in Remote Sensing (Basic)

Satellite imagery is particularly well-suited for regularly monitoring large areas and tracking changes over time. Drone imagery generally offers much higher spatial resolution and is suitable for detailed analyses of smaller areas. The choice depends on the specific issue, the desired level of accuracy, the study area, and how often new images are needed.

Satellite sensors not only measure visible light, but can also detect other parts of the electromagnetic spectrum, such as near-infrared, thermal infrared, and microwaves. This makes it possible, for example, to study vegetation condition, soil moisture, surface temperature, and water.

By comparing images taken at different times, changes in land use, vegetation, buildings, water, and soil can be identified. In doing so, it is important to take into account differences in season, weather conditions, resolution, and the characteristics of the sensor used.

This is determined by factors such as spatial, spectral, and temporal resolution. The spectral bands that are important for monitoring vegetation differ from those used for urban development or water management. The size of the area, the desired repeat frequency, and cloud cover also play an important role.