
Compute evapotranspiration of croplands with the SEBAL model in Google Earth Engine, guided by step by step tutorials, scripts, manuals in PDF format, and two JavaScript plugins for the course.
Identify cold anchor pixels from water bodies to estimate evapotranspiration and near-zero sensible heat, and hot anchor pixels in dry bare fields to map residual heat via surface temperature differences.
Open your Google Earth Engine profile, create a repository for the sebal model, upload the farmland shapefile, add country shapefiles, develop the net radiation flux script, and save.
Compute incoming shortwave radiation in Google Earth Engine using the solar constant, sun elevation, and atmospheric transmissivity, mapping a radiation band across the dataset with SEBAL.
Compute the outgoing longwave radiation using the Stefan-Boltzmann equation in Google Earth Engine, add it as a band with this name, and save after each step in the SEBAL workflow.
Export net radiation flux to Google Drive, download the TIFF rasters, and open them in ArcGIS or QGIS to analyze albedo, NDVI, SAVI, and temperature for evapotranspiration mapping.
Develop momentum roughness length for sensible heat flux within a Google Earth Engine workflow, using Copernicus land use land cover classification at 100 m to extract UAE class areas.
Import uncorrected momentum roughness lengths and net radiation flux into the Sebal script, define and clip study-area geometry with Copernicus land cover, and layer leaf area index for visualization.
Compute the grain ratio from ndvi, setting it to 0.5 if ndvi is negative, then derive soil heat flux G as grain ratio times net radiation, and compute Rn ratio.
Map a function over an image collection to create a feature collection, computing weather parameters and including day of year, year, minutes, temperature, surface radiation, wind, and dew point.
Compute daily evapotranspiration with SEBAL in Google Earth Engine by importing net radiation flux, wind speed, soil heat flux, and Landsat imagery, then derive correlations, boundaries, and ndvi-based estimates.
Compute instantaneous evapotranspiration and the transpiration fraction, then derive daily evapotranspiration using SEBAL in Google Earth Engine. Visualize results with color palettes, export maps, and repeat the workflow across images.
In this course, you will master a step-by-step guide to developing a script in Google Earth Engine for the most famous Evapotranspiration model - Surface Energy Balance Algorithm for Land (SEBAL) for agricultural areas. Before starting a course, please read the requirements for the course - you need to have a Google Earth Engine profile (free to open), and a basic or better intermediate level of scripting in GEE or JavaScript.
As a research study area an agricultural field that is located in Dubai Emirate, the UAE was taken. You can apply this course to your study area by making minor changes. It is good if you also have some knowledge/ experience of evapotranspiration.
The course is divided into a theoretical part and a practical part, the latter of which constitutes almost 90 % of the course. Each practical part of the course contains an attached script in txt format.
After finishing the course, besides developing the SEBAL model, you can apply different parts of the course in your other projects, that involve remote sensing.
The course also contains two QGIS plugins ( to calculate instantaneous reference evapotranspiration and correlation coefficients) developed deliberately for the course which is free to download.
Get ready to boost your knowledge in remote sensing and Google Earth Engine!