Remote Sensing Image Processing
Course description sheet
Basic information
- Field of study
- Geospatial Computer Science
- Major
- Remote Sensing and GIS
- Organisational unit
- Faculty of Geo-Data Science, Geodesy, and Environmental Engineering
- Study level
- Second-cycle (engineer) programme
- Form of study
- Full-time studies
- Profile
- General academic
- Didactic cycle
- 2024/2025
- Course code
- DGEITGS.IIi2.07201.24
- Lecture languages
- English
- Mandatoriness
- Obligatory
- Block
- Core Modules
- Course related to scientific research
- Yes
Lecturer
Krystyna Michałowska
|
Period
Semester 2
|
Method of verification of the learning outcomes
Completing the classes
Activities and hours
Lectures:
15
Project classes: 30 |
Number of ECTS credits
4
|
Course's learning outcomes
| Code | Outcomes in terms of | Learning outcomes prescribed to a field of study | Methods of verification |
| Knowledge – Student knows and understands: | |||
| W1 | the applied methods of remote sensing data processing | GEI2A_W01, GEI2A_W03 | Activity during classes |
| W2 | the creation, recording and main characteristics of the image in the most important sensors used in photogrammetry and remote sensing | GEI2A_W03, GEI2A_W06 | Activity during classes |
| Skills – Student can: | |||
| U1 | interpret content and process satellite images in a basic scope | GEI2A_U01, GEI2A_U03, GEI2A_U05 | Activity during classes, Report |
| Social competences – Student is ready to: | |||
| K1 | continuous update and broaden a knowledge in the field of photogrammetry and remote sensing; act independently and creatively solve problems | GEI2A_K01, GEI2A_K04 | Project |
Student workload
| Activity form | Average amount of hours* needed to complete each activity form | |
| Lectures | 15 | |
| Project classes | 30 | |
| Preparation for classes | 25 | |
| Realization of independently performed tasks | 30 | |
| Contact hours | 1 | |
| Student workload |
Hours
101
|
|
| Workload involving teacher |
Hours
45
|
|
* hour means 45 minutes
Program content
| No. | Program content | Course's learning outcomes | Activities |
| 1. | Execution of the sample environmental analysis: Formulation of the problem (selection of one of the available analyzes: identification of contaminated sites, determination of the environment, analysis of multispectral changes, etc.), analysis of available data for the selected area (checking availability and timeliness of data), performing advanced analysis based on current data and the adopted methodology, the implementation of an exemplary report. | U1, K1 | Project classes |
| 2. | Processing of remote sensing data - examples of practical projects: Discussing the issues of remote sensing data processing in example projects in the country and in the world. The use of modern advanced methods of data processing in environmental analysis (fuzzy set theory, artificial neural networks, deep learning, big data). Copernicus program, the use of Sentinel data perspective in the perspective of use for the work of the Agency for Restructuring and Modernization of Agriculture. Precision agriculture. | W1, W2 | Lectures |
| 3. | Remote and hyperspectral sensing: Multispectral image, spectral compositions, spectral curve for multi and hyperspectral images, spectral range and resolution, classification of multispectral images, work on remote sensing images, multi-resolution database, data-cube concepts in the sense of remote sensing. | W1, W2 | Lectures |
| 4. | Operations on remote sensing data: Basic operations on images and remote sensing data (loading of multisensory data, filtration, compression, improvement of data quality, automatic extraction of data by various methods). | U1, K1 | Project classes |
| 5. | Land use and land cover map: Execution of an exemplary utility / land cover map. The use of current classical methods (supervisory and unattended classification) and object-oriented methods (object classification). Performing a multitrack analysis based on current and archived data. | U1, K1 | Project classes |
| 6. | Characteristics of remote sensing systems: Presentation of currently available remote sensing systems, review in relation to historical data, principles of operation of imaging systems (cameras and scanners, lidars, radars, etc.), advantages and disadvantages of individual sensors, use in practice, data availability, procedures for ordering and obtaining data from various sensors. | W1, W2 | Lectures |
| 7. | The basics of remote sensing data processing: Basics of image processing, filtration, lossy and lossless compression, filter splitting, adaptive filters, discussion of the problem of correction of remote sensing data (geometric and atmospheric correction), general issues of remote sensing data processing, discussion of passive and active techniques, geometric models. | W1, W2 | Lectures |
| 8. | Remote sensing in environmental monitoring: Discussion of the issues of the use of remote sensing data in environmental monitoring. Overview of current monitoring systems. The advantages and disadvantages of monitoring remote sensing techniques from various ceilings (terrestrial, air and satellite). | W1, W2 | Lectures |
Extended information/Additional elements
Teaching methods and techniques :
Lectures
| Activities | Methods of verification | Credit conditions |
|---|---|---|
| Lectures | Activity during classes | |
| Project classes | Activity during classes, Project, Report |
Rules of participation in given classes, indicating whether student presence at the lecture is obligatory
Lectures: Studenci uczestniczą w zajęciach poznając kolejne treści nauczania zgodnie z syllabusem przedmiotu. Studenci winni na bieżąco zadawać pytania i wyjaśniać wątpliwości. Rejestracja audiowizualna wykładu wymaga zgody prowadzącego. Project classes: Studenci wykonują prace praktyczne mające na celu uzyskanie kompetencji zakładanych przez syllabus. Ocenie podlega sposób wykonania projektu oraz efekt końcowy.
Literature
Obligatory- 1. Gonzales R.C., Woods R.E., 2008, Digital Image Processing, Third Edition. Pearson Education, Inc.
- 2. Kurczyński Z. "Fotogrametria", PWN, 2014
- 2. Kurczyński Z., Preuss R.: "Podstawy Fotogrametrii", Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa, 2002
- 3. Sitek Z.: "Zarys teledetekcji lotniczej i satelitarnej" – Wydawnictwa AGH, Kraków, 1992
- 4. Mularz S., „Podstawy Teledetekcji. Wprowadzenie do GIS”, Wydawnictwo PK, Kraków 2004
Scientific research and publications
Publications- 1. Praca zbiorowa pod redakcją S. Mikrut. 2010. Sieci neuronowe w procesach dopasowania zdjęć lotniczych. Monografia. Wydawnictwa AGH. Kraków.
- 2. Mikrut S., 2009, Przydatność algorytmów podpikselowej detekcji cech w wybranych zagadnieniach fotogrametrycznych. Archiwum Fotogrametrii, Kartografii i Teledetekcji, Vol. 19, Kraków, s. 299-308.
- 3. Mikrut S.: Wpływ skanowania i kompresji metodą JPEG na wykrywanie obiektów liniowych i punktowych na obrazach cyfrowych. Geoinformatica Polonica, T. 7, Kraków 2005; s. 101-10
- 4. GIS i teledetekcja w monitoringu środowiska. 2015. Autorzy: Borkowski A., Głowienka E., Hejmanowska B., Kwiatkowska-Malina J., Kwolek M., Michałowska K., Mikrut S., Pękala A., Pirowski T., Zabrzeska-Gąsiorek B., Praca zbiorowa pod redakcją dr inż. E. Głowienki. Wydawnictwa WSIE, Rzeszów 2015. ISBN 978–83–60507–27–8