Description

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


Prerequisites:

General knowledge about remote sensing and GIS and their application in water-related issues.

Learning objectives:

Upon completion, the participant should be able to:

  • Explain RS theory, technology, typical applications of earth observation data
  • Download, pre-process satellite data, extract biophysical features, derive and analyse vegetation indices in agricultural systems
  • Perform land cover classification using time-series satellite data through the application of machine learning algorithms in desktop and cloud-based platforms
  • Explain the theory and implement surface energy balance model to estimate Evapotranspiration (ET), biomass production, and Water Productivity (WP)
  • Assess the irrigation performance using remote sensing, interpret them to identify gaps, diagnose water management problems, and attribute to relevant factors for improvements
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 the 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

Cost Details

VAT is not included in the course fee.

Deadline IHE application: 05 September 2020 - 23.59 (CET)

Cost

€1035

Who

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.

More information

Register here

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