Remote Sensing

Remote Sensing is the most valuable source for the acquisition of actual geodata, e.g. land use / land cover (LULC). Remotely sensed imagery is acquired by high resolution spaceborne sensors with ground resolutions up to 0.6m, airborne imagery nowadays provide spatial resolution better than 0.1m. Both types of imagery record the reflected electromagnetic energy in several spectral bands, ranging from the visible wavelength to the near infrared.This Remote Sensing module follows a multi step education, the typical workflow of remote sensing process: recording, processing, analyzing, and applying. The introduction gives a fundamental background about the theory of spectral data origin and its digital acquisition first. Operational sensors and platforms available for data acquisition will be described as well. Remotely sensed data processing means the elimination of system errors and the georeferencing of the image data. A very important part in the process is the data analysis, that is generating information from raw remote sensing data, such as extracting real world objects or mapping land use land coverage. Therefore, in principle two different methods are available: a statistical pixel-per-pixel approach and the more sophisticated object-based image analysis. The results of image analysis in general are transferred into and stored in a Geographical Information System (GIS), where they can be combined with additional data for a more advanced modelling and visualization. Vice versa, already existing GIS data can support the image analysis process.

29 June 2020

Remote Sensing – Registration

June 29 - September 21
16 November 2020

Remote Sensing – Registration

November 16 - February 8, 2021

3 months



The module is free of charge for UNIGIS students working to meet their elective subject requirements. Included are:

  • all related study materials
  • supervision and assessment
  • module accreditation according to the curriculum

ClubUNIGIS members can register at a price of € 300,-. Included are:

  • all related study materials
  • supervision and assessment
  • course certificate upon completion of the module

  • Explain the relationship between electromagnetic radiation, geo objects and the generation of geo information
  • Give insight into different kinds of sensors, systems and satellite platforms
  • Explain where and how to obtain remote sensing data
  • Explain how to handle different kinds and formats of data
  • Demonstrate and enable student to apply methods and the typical workflow of processing remote sensing data for information extraction
  • Enable students to assess data and valuate analysis results for typical application purposes
  • Demonstrate typical examples for applied remote sensing

Core UNIGIS modules 1-3 or equivalent understanding of GIS, data modeling, data structures and data acquisition. Basic knowledge in working with GIS Software and data.

Nice-to-have: Basic knowledge in physics, especially in optics. Apart from the general system requirements, the following software is required for the completion of this module: ERDAS IMAGINE Professional. For the completion of this module we provide you with 1 free evaluation license. eCognition Developer Trial is used in this module as well.

We would like to inform you that this is an exclusively english language module, hence any kind of communication with the module lecturer should be in English. A discussion forum is maintained in moodle in order to support efficient module instruction. You are requested to submit all your questions related to this module to this forum only. The lecturer will check all incoming comments on a regular basis. He will answer your questions or provide you with pointers for solving your problems. The module is delivered in form of an instructed self-study that is based on explorative learning process and process. Theoretical concepts are complemented with practice oriented examples demonstrated with help of multimedia elements. Upon completion of the module students are requested to evaluate the module, which is a part of our quality assurance policy and practice.

ERDAS Imagine 2014; eCognition Developer Trial (64-bit), …
Literature: LILLESAND T./KIEFER R., 2008, 6th Ed.,:Remote sensing and image interpretation. New York.

System requirements
Students are supposed to work with the software eCognition Developer Trial 64-bit. Please be aware that eCognition Developer Trial will not work with Windows 32-bit or “Home” Versions! If you need a Windows 7 Professional 64-bit EDU copy, please ask for a Dreamspark Account to get one!

Software Requirements
– Microsoft Windows 7 Professional (64-Bit)
– Microsoft Windows 8.1 (64-Bit)

Minimum Hardware Requirements
– Intel Pentium 4 or compatible / Intel Dual Core or compatible
– NVIDIA or ATI OpenGL graphics card
– 1 GB RAM l 50 GB available hard disk space
– 1280 x 1024 display.

Recommended Hardware Requirements
– Intel Dual Core or Quad Core
– NVIDIA or ATI OpenGL graphics card
– 4 GB RAM 1 l 200 GB available hard disk space
– 1600 x 1200 display

The assessment is based on your completed assignments. They must be submitted in written format (.PDF/.DOC) to the Dropbox within the required time period. If assignments are submitted late, the lecturer is not obligated to grade them. It will be listed as such on your transcript.

Lesson 1 – Electromagnetic spectrum and interaction of radiation with matter and atmosphere
Remote sensing is the science and art of obtaining information about an object, an area, or a phenomenon through the analysis of data acquired by devices that are not in contact with the objects, areas, or phenomena under investigation.

Lesson 2 – Data acquisition process
How is remote sensing data acquired? What is important to know about the workflow of data acquisition and related processes? How does it influence the information we want to extract from the data? This lesson should help you to understand the processes and constraints along a common data acquisition workflow.

Lesson 3 – Sensors and platforms
There is a variety of available remote sensing data representing earth´s surface, acquired during different times of the year. The sensors which are the eyes of the sensor platform have different properties in resolution, channels, etc. Similalry, platforms have different properties such as the time period they rescan the same area on the surface. In everyday life the different cost models force one to perform a cost-benefit calculation. These differences are the key parameters to decide which sensor is optimal for give an answer to a specific question.

Lesson 4 – Visual image interpretation
This lesson gives an insight into the process of interpreting images visually. It is important to know how we scan, interpret and what we see with our own eyes and brain. That helps to understand limitations and potential sources of error that could be also included in digital image interpretation process.

Lesson 5 – Basic methods of image processing
From colour or contrast enhancement to channel mixing up to basic data compression methods are covered in this lesson.

Lesson 6 – Rectification and geo-coding of images
In this lesson you deal with the process to assign a reference system to an image relating each pixel of this image to a point/area on earth’s surface. Thus, geometric correction and rectification are the main topics here.

Lesson 7 – Advanced methods of image processing
Besides filtering operations and pan-sharpening, this lesson deals with advanced methods like principal component transformation, channel ratios and texture transformations.

Lesson 8 – Digital image analysis – classification methods
The step from pixel-based image data to objects and classes of objects is a key element in remote sensing and the main benefit from this discipline.

Lesson 9 – Planning a remote sensing image application
The planning process is a key element in remote sensing. It should help you to avoid common mistakes and you can save much time in your daily work.

Lesson 10 – Application: map production from remote sensing imagery
In this lesson you will get an idea of the various applications of remote sensing. The goal of turning geo-spatial data into information is both a question of cartography and/or illustration and classifying, filtering the extracted information so that it is useful (and reliable) for serve its original purpose.

Lesson 11 – Application: Land Use Land Cover (LULC) mapping
Land use/Land cover classification, a remote sensing product, is one of the most important applications.Besides the principles of the so called LULC classification the workflow to perform a reliable LULC classification is developed and performed in this lesson.

Lesson 12 – Application: Regional planning, water resources and geology
This lesson touches some applications of remote sensing in regional planning, water resources management and geology. It intends to demonstrate some fields of application of remote sensing.

Lesson 13 – Application: Change detection
This lesson will give you an overview on principles of change detection and monitoring with remote sensing data.

Lesson 14 – Active systems
Radar and Laser scanning are active systems that have some advantages over classical remote sensing approaches and data sources.

Lesson 15 – Future trends
This lesson focuses on planned remote sensing missions, trends in data acquisition & data quality and on methodological aspects.