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-api

Authenticate 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)

More about SEBAL:

Bastiaanssen, W.G.M., 1995. Regionalization of surface flux densities and moisture indicators in composite terrain: a remote sensing approach under clear skies in Mediterranean climates. Dr. thesis, Wageningen Agric. Univ. Wageningen Netherlands. SC-DLO, Wageningen.

Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A., Holtslag, A.A.M., 1998a. A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation. J. Hydrol. 212–213, 198–212.

Bastiaanssen, W.G.M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J.F., Roerink, G.J., van der Wal, T., 1998c. A remote sensing surface energy balance algorithm for land (SEBAL): 2. Validation. J. Hydrol. 212–213, 213–229.

Our work:

Ruhoff, A., Paz, A., Collischonn, W., Aragão, L., Rocha, H., S. Malhi, Y., 2012. A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas, Remote Sensing, vol. 4, issue 3, pp. 703-725.

Ruhoff, A. R. Paz, L. E. O. C. Aragao, Q. Mu, Y. Malhi, W. Collischonn, H. R. Rocha & S. W. Running (2013) Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin, Hydrological Sciences Journal, 58:8, 1658-1676

Laipelt, L.; Ruhoff, A.L.; Fleischmann, A.S.; Kayser, R.H.B.; Kich, E.M.; da Rocha, H.R.; Neale, C.M.U. Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil. Remote Sens. 2020, 12, 1108.

Carlitosh/geeSEBAL