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Technologies of Remote Sensing

Course developer

Replaced course

BūvZB005 [GBUVB005] Technologies of Remote Sensing

Course abstract

The aim of the study course is to give students the essential knowledge and practical skills to choose, apply, and use modern digital photogrammetry data and technologies in various situations and sectors related to surveying and land management, forestry and agriculture. The program is intended for comprehensive training of specialists of cadastre, agriculture, forestry and other rural areas.

Learning outcomes and their assessment

Knows modern remote sensing technologies, their data acquisition methods, the nature of methods for application, data processing and spatial analysis.
Is able to orientate oneself in the issues of identification of photogrammetry and remote sensing application possibilities and definition / ordering and realization of work tasks while performing one's professional duties;
Is able to apply the acquired basic skills to work with remote sensing data, using photogrammetric methods and techniques, their application in modern applied aspects and research directions.
Assessment: Written exam, covering the issues of the whole course of the subject; laboratory works and students' independent work.

Course Content(Calendar)

Full-time studies:
1. Definitions of remote sensing and photogrammetry. Review of historical development (2h)
2. Basic principles of remote sensing technology; electromagnetic radiation and Electromagnetic Spectrum (1h)
3. Characteristics of remote sensing data: spatial resolution, spectral resolution, radiometric and temporal resolution. Passive vs. Active Remote Sensing (1h)
4. Remote sensing and its relationship to photogrammetry unifying and difference. Instruments and technologies for remote sensing and photogrammetry. Sensor selection (2h)
5. Passive (optical image) acquisition sensors. Photography, photographic basics and photographic equipment (2h)
6. Work with imagery, measurements and interpretation, spectral analysis technologies (1h)
7. Coordinate systems of remote sensing. Geo-referencing of remote sensing data, integration of GPS/INS (1h)
8. Computer Vision. Theory of image comparison (image matching) (1h)
9. Definitions of orthophoto, principles of calculations. Accuracy of orthophoto (1h)
10. Passive (optical) sensors for obtaining satellite images: LandSat 5-8, Sentinel 2 – data processing methodology and application of the obtained products (2h)
11. Digital Surface elevation models. Methods for obtaining 3D point clouds (1h)
12. Active sensors-laser scanning (LiDAR), data processing and application (2h)
13. Active sensors-radar of the Earth's surface (basic principles of synthesized aperture radar (SAR) and radar data processing) (1h)
14. UAV technologies for remote sensing and photogrammetry. Selection of technological solutions (2h)
15. Classification of land use by remote sensing data. Supervised classification of satellite imagery (2h)
16. Monitoring of forest resources and facilitating forest inventory using satellite and aerial imagery and LIDAR data (1h)
17. Integration and fusion of remote sensing data, digital mapping and geographic information systems (1h)

Laboratory works:
• Cloud generation of 3D dots using photogrammetry techniques (10h)
• Processing of freely available laser scanning data (LiDAR) and satellite data (Sentinel2) using remote sensing techniques and free software (14h)

Part-time studies:
All topics specified for full-time studies are implemented, but the number of contact hours is 1/2 of the total allocated full-time hours.

Requirements for awarding credit points

Written Exam, covering the questions of the whole subject course, according to the received exam ticket.
Completed and defended laboratory work tasks and student independent practical work.

Description of the organization and tasks of students’ independent work

Students' independent work task – using the skills and abilities acquired during laboratory work, a student has to process freely available remote sensing data (LiDAR and Sentinel-2 imagery) using open-source software; presenting the results in written form (submitted electronically).

Criteria for Evaluating Learning Outcomes

The study course evaluation depends on the written exam's assessment and the cumulative evaluation of the study course tests and student independent practical work.
A student can obtain a successful mark on a test or exam if at least 50% of the test questions are answered correctly.
The student works and exam performance is assessed by the university established 10-point grading system.
The final exam mark is calculated as the arithmetic mean of the written exam marks and students' independent work.

Compulsory reading

1. Konecny Geoinformation: remote sensing, photogrammetry and geographic information systems. CRC Press, 2014.
2. Kraus K. Photogrammetry: geometry from images and laser scans. Walter de Gruyter, 2011.
3. Lillesand T., Kiefer R., Chipman W. Remote sensing and image interpretation. Hoboken, NJ: Wiley & Sons, 2015.
4. J.Štrauhmanis J. Ģeomātikas pamati. , RTU, 2006.

Further reading

1. Luhmann T.Robson S., Kyle S., and Boehm J. Close-range photogrammetry and 3D imaging. Berlin; Boston: Walter de Gruyter, 2013.
2. Vosselman G., Maas H.G., Airborne and terrestrial laser scanning. Dunbeath: Whittles Publishing,2010.

Periodicals and other sources

1. Copernicus Open Access Hub. Pieejams: https://scihub.copernicus.eu/ (Sentinel 1-2 data);
2. The International Society for Photogrammetry and Remote Sensing. Pieejams: https://www.isprs.org
3. EuroSDR National Mapping and Cadastral Agencies with Research Institutes and Universities in Europe [tiešsaiste] Pieejams: https://www.eurosdr.net

Notes

Professional higher education bachelor study program “Geoinformatics and Remote Sensing” in full-time studies and part-time studies