Online Course on Remote Sensing for Agricultural Water Management

Develop skills to use remote sensing for land cover classification, estimating evapotranspiration, water productivity, irrigation performance assessment & irrigation water accounting.

Apply now for

20192020

For whom?

Young and mid-career professionals, engineers and technicians and academics involved in agricultural water and irrigation system management in various government and non-government organizations.

Dates, Fee, ECTS

Start: 18 November 2019
End: 27 March 2020
Deadline IHE application: 16 November 2019 - 23.59 (CET)
Course fee: € 1035

Start: 07 September 2020
End: 15 January 2021
Deadline IHE application: 05 September 2020 - 23.59 (CET)
Course fee: € 1035

VAT is not included in the course fee

Course content

  • Subject 1: Introduction to Earth observation and remote sensing techniques
    Basics of RS and spatial data; introduction to common RS data portal; earth observation satellites; typical application of RS and existing products; hands-on exercises on need analysis and acquiring of relevant data.
  • Subject 2: Remote Sensing data analysis 
    Overview of RS data processing flow; satellite data pre-processing; mapping and visualizing spatial data; image analysis; hands-on exercise on deriving vegetation indices, zonal statistics using open source software and libraries.
  • Subject 3: Land cover classification
    Land cover classification theory; classification algorithms; machine learning approaches in classification; ground truthing methods; accuracy assessment; hands-on exercises on land cover classification using open source QGIS and cloud based Google Earth Engine (GEE)
  • Subject 4: Remote sensing for Evapotransipration, biomass production and water productivity assessment
    Theory of Surface Energy Balance Algorithm for Land (SEBAL); Introduction to python based implementation of SEBAL (pySEBAL); hands-on exercise on running pySEBAL to estimate evapotranspiration, biomass, and water productivity.
  • Subject 5: Remote sensing for enhancing performance of irrigation systems
    Assessment of the irrigation performance using remote sensing based indicators for productivity, adequacy, reliability, and equity; interpreting results to identify gaps, diagnose water management problems, and attribute to relevant factors for improvements; perform irrigation scheme level water accounting

Key lecturers

  • Dr. Poolad Karimi
  • Dr. Sajid Pareeth
  • Mr. Tim Busker

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