Navigation

M-UZ-20-PDML - Primena daljinske detekcije u melioracijama

Course specification
Course title
Acronym M-UZ-20-PDML
Study programme
Module
Type of study
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 5.0 Status
    Condition Nema Oblik uslovljenosti
    The goal Introduction of remote sensing sensors, the method of recording, electromagnetic spectrum and changes in space and time, to explain the reflections of the radiation spectrum in relation to the spectrum of water, soil, vegetation, by different indices, to interpret the data obtained by remote sensing for water management, to assess the impact of drought across different indices.
    The outcome The student should be able to process data obtained by remote sensing for a variety of the need to map the infrastructure of reclamation facilities, so that the analysis of images can follow changes in crops and land in order to better manage natural resources in agriculture.
    Contents
    Contents of lectures Electromagnetic radiation and spectrum, interaction with the atmosphere, passive and active remote sensing; Sensors and satellites, resolution, multispectral and thermal detection, types of observational satellites; Image analysis: visual interpretation, digital image processing, highlighting of significant data and classification of data of importance for study; NDVI and other indices.
    Contents of exercises Making images with a thermal imaging, hyper-spectral -multispectral camera from the ground, over drones, download free satellite images TERRA, MODIS, Sentinel 2, metadata retrieval and image overlap, image analysis to determine drought, water-logging, the need for irrigation.
    Literature
    1. Čupković, T., Pavlović, R. Marković, M. (2004). Remote sensing, Faculty of Mining and Geology, Belgrade
    2. Hamlyn, G.J., Vaughan, R.A. (2010). Remote sensing of vegetation: principles, techniques and applications. United States by Oxford University Press Inc., New York. (Original title)
    3. Knipper, K.R., Kustas, W.P., Anderson, M.C., Alfieri, J.G., Prueger, J.H., Hain, C.R., Hipps, L.E. (2018). Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards. Irrigation Science, 1-19. (Original title)
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 2
    Methods of teaching Lectures: presentation of materials, checking the understanding of materials through discussion with students, analysis of remote sensing images, presenting materials and practical exercises, lectures in the field
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures Test paper
    Practical lessons 30 Oral examination 50
    Projects
    Colloquia 20
    Seminars