i.eb.soilheatflux(1)

✨ i.eb.soilheatflux ✨

okay bestie, welcome to the GRASS GIS User's Manual page for i.eb.soilheatflux(1) 🫢 β€” yes that's the module name, yes it's a mouthful, we're gonna get through it together πŸ’…

🌸 NAME 🌸

i.eb.soilheatflux β€” Soil heat flux approximation (Bastiaanssen, 1995).

πŸŽ€ KEYWORDS πŸŽ€

imagery, energy balance, soil heat flux, SEBAL


πŸ¦‹ SYNOPSIS πŸ¦‹

i.eb.soilheatflux
i.eb.soilheatflux --help
i.eb.soilheatflux [-r] albedo=name ndvi=name temperature=name
netradiation=name localutctime=name output=name  [--overwrite]  [--help]
[--verbose]  [--quiet]  [--ui]

πŸ’– Flags πŸ’–

  • -r β€” HAPEX-Sahel empirical correction (Roerink, 1995) ✨
  • --overwrite β€” Allow output files to overwrite existing files
  • --help β€” Print usage summary
  • --verbose β€” Verbose module output
  • --quiet β€” Quiet module output
  • --ui β€” Force launching GUI dialog

πŸ’œ Parameters πŸ’œ

  • albedo=name [required] β€” Name of albedo raster map [0.0;1.0]
  • ndvi=name [required] β€” Name of NDVI raster map [-1.0;+1.0]
  • temperature=name [required] β€” Name of Surface temperature raster map [K]
  • netradiation=name [required] β€” Name of Net Radiation raster map [W/m2]
  • localutctime=name [required] β€” Name of time of satellite overpass raster map [local time in UTC]
  • output=name [required] β€” Name for output raster map

🌈 DESCRIPTION 🌈

so i.eb.soilheatflux calculates the soil heat flux approximation (g0) after Bastiaanssen (1995) πŸ”₯. The main reference for implementation is Alexandridis, 2009 β€” noted, respected, iconic πŸ“š.

It takes input of Albedo, NDVI, Surface Skin temperature, Net Radiation (see r.sun), time of satellite overpass, and a flag for the Roerink empirical modification from the HAPEX-Sahel experiment. no cap, that's the whole roster πŸ’«

The "time of satellite overpass" map can be obtained as follows:

  • MODIS: a related sub dataset is included in each HDF file, and simply to be imported as a raster map;
  • Landsat: to be generated as map from the overpass time stored in the metadata file (given in Greenwich Mean Time - GMT), see below.

For Landsat, the overpass map can be computed by using a two-step method:

# 1) extract the overpass time in GMT from metadata file
i.landsat.toar -p input=dummy output=dummy2 \
   metfile=LC81250452013338LGN00_MTL.txt lsatmet=time
# ... in this example approx. 03:12am GMT
# 2) create map for computational region of Landsat scene
g.region rast=LC81250452013338LGN00_B4 -p
r.mapcalc "overpasstime = 3.211328"
fr fr, copy those commands exactly, they're doing the Lord's work πŸ™

πŸ‘‘ REFERENCES πŸ‘‘

Bastiaanssen, W.G.M., 1995. Estimation of Land surface parameters by remote sensing under clear-sky conditions. PhD thesis, Wageningen University, Wageningen, The Netherlands. (PDF)

Chemin Y., Alexandridis T.A., 2001. Improving spatial resolution of ET seasonal for irrigated rice in Zhanghe, China. Asian Journal of Geoinformatics. 5(1):3-11,2004.

Alexandridis T.K., Cherif I., Chemin Y., Silleos N.G., Stavrinos E., Zalidis G.C. Integrated methodology for estimating water use in Mediterranean agricultural areas. Remote Sensing. 2009, 1, 445-465. (PDF)

Chemin, Y., 2012. A Distributed Benchmarking Framework for Actual ET Models, in: Irmak, A. (Ed.), Evapotranspiration - Remote Sensing and Modeling. InTech. (PDF)


⭐ SEE ALSO ⭐

r.sun, i.albedo, i.emissivity, i.eb.hsebal01, i.eb.evapfr, i.landsat.toar


πŸ“ AUTHOR πŸ“

Yann Chemin, Asian Institute of Technology, Thailand


πŸ’€ SOURCE CODE πŸ’€

Available at: i.eb.soilheatflux source code (history)

Accessed: Saturday Jan 17 05:41:39 2026

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