Develop skills to use remote sensing for land cover classification, estimating evapotranspiration, water productivity, irrigation performance assessment & irrigation water accounting.
General knowledge about remote sensing and GIS and their application in water-related issues.
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
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
- Dr. Poolad Karimi
- Dr. Sajid Pareeth
- Mr. Tim Busker
Cost DetailsVAT is not included in the course fee.
Deadline IHE application: 05 September 2020 - 23.59 (CET)
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.