.TH i.landsat.acca 1grass "" "GRASS 8.3.1" "GRASS GIS User's Manual"
.SH NAME
\fI\fBi.landsat.acca\fR\fR  \- Performs Landsat TM/ETM+ Automatic Cloud Cover Assessment (ACCA).
.SH KEYWORDS
imagery, ACCA, cloud detection, satellite, Landsat
.SH SYNOPSIS
\fBi.landsat.acca\fR
.br
\fBi.landsat.acca \-\-help\fR
.br
\fBi.landsat.acca\fR [\-\fB5fx2s\fR] \fBinput\fR=\fIbasename\fR \fBoutput\fR=\fIname\fR  [\fBb56composite\fR=\fIfloat\fR]   [\fBb45ratio\fR=\fIfloat\fR]   [\fBhistogram\fR=\fIinteger\fR]   [\-\-\fBoverwrite\fR]  [\-\-\fBhelp\fR]  [\-\-\fBverbose\fR]  [\-\-\fBquiet\fR]  [\-\-\fBui\fR]
.SS Flags:
.IP "\fB\-5\fR" 4m
.br
Data is Landsat\-5 TM
.br
I.e. Thermal band is \(cq.6\(cq not \(cq.61\(cq)
.IP "\fB\-f\fR" 4m
.br
Apply post\-processing filter to remove small holes
.IP "\fB\-x\fR" 4m
.br
Always use cloud signature (step 14)
.IP "\fB\-2\fR" 4m
.br
Bypass second\-pass processing, and merge warm (not ambiguous) and cold clouds
.IP "\fB\-s\fR" 4m
.br
Include a category for cloud shadows
.IP "\fB\-\-overwrite\fR" 4m
.br
Allow output files to overwrite existing files
.IP "\fB\-\-help\fR" 4m
.br
Print usage summary
.IP "\fB\-\-verbose\fR" 4m
.br
Verbose module output
.IP "\fB\-\-quiet\fR" 4m
.br
Quiet module output
.IP "\fB\-\-ui\fR" 4m
.br
Force launching GUI dialog
.SS Parameters:
.IP "\fBinput\fR=\fIbasename\fR \fB[required]\fR" 4m
.br
Base name of input raster bands
.br
Example: \(cqB.\(cq for B.1, B.2, ...
.IP "\fBoutput\fR=\fIname\fR \fB[required]\fR" 4m
.br
Name for output raster map
.IP "\fBb56composite\fR=\fIfloat\fR" 4m
.br
B56composite (step 6)
.br
Default: \fI225.\fR
.IP "\fBb45ratio\fR=\fIfloat\fR" 4m
.br
B45ratio: Desert detection (step 10)
.br
Default: \fI1.\fR
.IP "\fBhistogram\fR=\fIinteger\fR" 4m
.br
Number of classes in the cloud temperature histogram
.br
Default: \fI100\fR
.SH DESCRIPTION
\fIi.landsat.acca\fR implements the \fBAutomated Cloud\-Cover
Assessment\fR (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 \fIi.landsat.toar\fR).
.PP
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.
.SH NOTES
\fIi.landsat.acca\fR works in the current region settings.
.SH EXAMPLES
Run the standard ACCA algorithm with filling of small cloud holes
(the \fB\-f\fR 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:
.br
.nf
\fC
i.landsat.toar sensor=7 gain=HHHLHLHHL date=2003\-04\-07 \(rs
  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
\fR
.fi
.SH REFERENCES
.IP
.IP \fB1\fR
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.
.IP \fB2\fR
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.
.PP
.SH SEE ALSO
\fI
i.atcorr,
i.landsat.toar
\fR
.SH AUTHOR
E. Jorge Tizado  (ej.tizado unileon es), Dept. Biodiversity and Environmental Management, University of León, Spain
.SH SOURCE CODE
.PP
Available at:
i.landsat.acca source code
(history)
.PP
Accessed: Sunday Dec 17 17:22:41 2023
.PP
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.PP
© 2003\-2023
GRASS Development Team,
GRASS GIS 8.3.1 Reference Manual