ETBRASIL - geeSEBAL
geeSEBAL is a open-source implementation of Surface Energy Balance Algorithm for Land (SEBAL) using Google Earth Engine (GEE). geeSEBAL is available in both Javascript and Python API.
A web application is also available (https://etbrasil.org/geesebal).
Python functions: Image(), Collection() and TimeSeries().
Javascript functions: image().
How to use Google Earth Engine?
You need an account in GEE (https://earthengine.google.com/).
Python API
Using pip to install earthengine-api
pip install earthengine-apiAuthenticate Earth Engine library
import ee; ee.Authenticate()JavaScript API
Editor code available (https://code.earthengine.google.com/)
Examples
Image
from etbrasil.geesebal import Image
Image_ID=ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_222081_20160118')
geeSEBAL_Image=Image(Image_ID)Collection
from etbrasil.geesebal import Collection
#inputs= init Year, init Month, init dat, end Year, end Month, end day, Cloud Cover
geeSEBAL_Collection=Collection(2000,1,1,2010,5,6,15)TimeSeries
from etbrasil.eesebal import TimeSeries
#inputs= init Year, init Month, init dat, end Year, end Month, end day, Cloud Cover,ee.Geometry.Point
point=ee.Geometry.Point([-50.161317, -9.824870])
geeSEBAL_Collection=TimeSeries(2000,1,1,2010,5,6,15,point)What is SEBAL?
Surface Energy Balance Algorithm for Land (SEBAL) was developed and validated by Bastiaanssen (Bastiaanssen, 1995; Bastiaanssen et al., 1998a, 1998b) to estimate evapotranspiration (ET) from energy balance equation (Rn – G = LE + H), where LE, Rn, G and H are Latent Heat Flux, Net Radiation, Soil Heat Flux and Sensible Heat Flux, respectively.
Cite this work
[Laipelt et al. (2021)] Long-term monitoring of evapotranspiration using the SEBAL algorithm and Google Earth Engine cloud computing. (https://doi.org/10.1016/j.isprsjprs.2021.05.018)