Remote Sensing (MGIS1I1)

  • Level of study master academic studies
  • Subject status: elective
  • ECTS: 7
  • Semester: I
  • Number of classes: 3+0

Determination real and change condition of geospatial elements by remote sensing.

 

The results are the control and auditing of the physical-geographical and socioeconomic elements of the environment. The final result is data base of geospatial elements.

Theoretical lectures per weeks

  1. Introduction of remote sensing.
  2. Comparison of aerial and satellite images.
  3. Bases procedures of image processing.
  4. Processing of satellite images.
  5. Measuring on satellite images (point, line and polygon objects).
  6. Correction of visual interpretation.
  7. Spatial image filtering.
  8. Improvement of geometry edges at images.
  9. Indices of vegetation.
  10. Supervised and unsupervised classification of satellite images.
  11. Application of different models in the analysis of geospatial elements.
  12. Application of remote sensing in the analysis of natural phenomena and processes.
  13. Application of remote sensing in the analysis of social phenomena and processes.
  14. Application of remote sensing in environmental protection.
  15. Application of remote sensing in spatial planning.

 

Practical lectures per week
I to III - Application of different models in the analysis of geospatial elements
IV to VI - Application of remote sensing in the analysis of natural phenomena and processes.
VII to IX - Application of remote sensing in the analysis of social phenomena and processes.
X to XII - Application of remote sensing in environmental protection.
XIII to XV - Application of remote sensing in spatial planning.

Милановић М., Љешевић М. (2009): Теледетекционе методе истраживања животне средине, Универзитет у Београду, Географски факултет, Београд.

Horning N., Robinson J., Sterling E., Turner W., Spector S. (2015): Remote Sensing for Ecology and Conservation, Oxford, UK, Oxford University Press.

Weng Q. (2015): Remote Sensing and GIS Integration – Theories, Methods, and Applications, The McGraw Hill, New York.

Thenkabail S. P. (2016): Remote Sensing of Water Resources, Disasters, and Urban Studies, CRC Press, London/New York.

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