i.landsat.acca - Performs Landsat TM/ETM+ Automatic Cloud Cover Assessment (ACCA).

       E. Jorge Tizado  (ej.tizado unileon es), Dept. Biodiversity and Environmental Management,  University  of
       León, Spain

i.landsat.acca implements the AutomatedCloud-CoverAssessment (ACCA) Algorithm from  Irish  (2000)  with
       the  constant  values  for  pass  filter  one from Irish et al. (2006). To do this, it needs Landsat band
       numbers 2, 3, 4, 5, and 6 (or band 61 for Landsat-7 ETM+) which have already been processed from DN  into
       reflectance and band-6 temperature with i.landsat.toar).

       The  ACCA  algorithm  gives good results over most of the planet with the exception of ice sheets because
       ACCA operates on the premise that clouds are colder than the land surface they cover. The  algorithm  was
       designed for Landsat-7 ETM+ but because reflectance is used it is also useful for Landsat-4/5 TM.

       Run  the  standard  ACCA  algorithm  with  filling  of  small  cloud  holes  (the -f flag): With per-band
       reflectance  raster  maps  named  226_62.toar.1,  226_62.toar.2,   ...   and   LANDSAT-7   thermal   band
       226_62.toar.61, outputting to a new raster map named 226_62.acca:
       i.landsat.toar sensor=7 gain=HHHLHLHHL date=2003-04-07 \
         product_date=2008-11-27 band_prefix=226_62 solar_elevation=49.51654
       i.landsat.acca -f band_prefix=226_62.toar output=226_62.acca

       imagery, ACCA, cloud detection, satellite, Landsat

i.landsat.acca  - Performs Landsat TM/ETM+ Automatic Cloud Cover Assessment (ACCA).

i.landsat.acca works in the current region settings.

           •   Irish  R.R.,  Barker J.L., Goward S.N., and Arvidson T., 2006.  Characterization of the Landsat-7
               ETM+ Automated Cloud-Cover Assessment (ACCA) Algorithm. Photogrammetric  Engineering  and  Remote
               Sensing vol. 72(10): 1179-1188.

           •   Irish,  R.R.,  2000.  Landsat  7  Automatic Cloud Cover Assessment. In S.S. Shen and M.R. Descour
               (Eds.): Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI. Proceedings of
               SPIE, 4049: 348-355.

i.atcorr,i.landsat.toar

       Available at: i.landsat.acca source code (history)

       Accessed: Friday Apr 04 01:20:56 2025

       Main index | Imagery index | Topics index | Keywords index | Graphical index | Full index

       © 2003-2025 GRASS Development Team, GRASS GIS 8.4.1 Reference Manual

GRASS 8.4.1                                                                               i.landsat.acca(1grass)

i.landsat.accai.landsat.acca--helpi.landsat.acca    [-5fx2s]    input=basenameoutput=name     [b56composite=float]     [b45ratio=float]
       [histogram=integer]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:-5
           Data is Landsat-5 TM
           I.e. Thermal band is ’.6’ not ’.61’)

       -f
           Apply post-processing filter to remove small holes

       -x
           Always use cloud signature (step 14)

       -2
           Bypass second-pass processing, and merge warm (not ambiguous) and cold clouds

       -s
           Include a category for cloud shadows

       --overwrite
           Allow output files to overwrite existing files

       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:input=basename[required]
           Base name of input raster bands
           Example: ’B.’ for B.1, B.2, ...

       output=name[required]
           Name for output raster map

       b56composite=float
           B56composite (step 6)
           Default: 225.b45ratio=float
           B45ratio: Desert detection (step 10)
           Default: 1.histogram=integer
           Number of classes in the cloud temperature histogram
           Default: 100