metode gap fill menggunakan arcgis
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DESCRIPTIONcara memperbaiki citra landsat 7 yang rusak (stripping)
On May 31, 2003, the Scan Line Corrector (SLC), which compensates for the forward motion of Landsat 7, failed. Subsequent efforts to recover the SLC were not successful, and the failure appears to be permanent. Without an operating SLC, the Enhanced Thematic Mapper Plus (ETM+) line of sight now traces a zig-zag pattern along the satellite ground track (Figure 1). As a result, imaged area is duplicated, with width that increases toward the scene edge
Luis Vega Ingeniera Ambiental
MODEL: Gap Fill for Landsat 7 images A correction of SLC-off
AUTHOR: Luis Vega Bustillos, Environmental Engineer
DATE: July 2012
About SLC-off On May 31, 2003, the Scan Line Corrector (SLC), which compensates for the forward motion of
Landsat 7, failed. Subsequent efforts to recover the SLC were not successful, and the failure
appears to be permanent. Without an operating SLC, the Enhanced Thematic Mapper Plus
(ETM+) line of sight now traces a zig-zag pattern along the satellite ground track (Figure 1). As
a result, imaged area is duplicated, with width that increases toward the scene edge.
Figure 1. SLC Failure
The Landsat 7 ETM+ is still capable of acquiring useful image data with the SLC turned off,
particularly within the central part of any given scene. The Landsat 7 ETM+ therefore continues
to acquire image data in the "SLC-off" mode. All Landsat 7 SLC-off data are of the same high
radiometric and geometric quality as data collected prior to the SLC failure.
The SLC-off effects are most pronounced along the edge of the scene and gradually diminish
toward the center of the scene (Figure 2). The middle of the scene, approximately 22
kilometers wide on a Level 1 (L1G, L1Gt, L1T) product, contains very little duplication or data
loss, and this region of each image is very similar in quality to previous ("SLC-on") Landsat 7
Figure 2. Complete Landsat 7 scene showing affected vs. unaffected area.
An estimated 22 percent of any given scene is lost because of the SLC failure. The maximum
width of the data gaps along the edge of the image would be equivalent to one full scan line,
or approximately 390 to 450 meters. The precise location of the missing scan lines will vary
from scene to scene.
SOURCE: USGS. (2010). SLC-off Products: Background. Obtenido de USGS - Landsat Missions:
Algorithms for the correction After reviewing various methodologies proposed by the USGS and by independent authors
raised some difficulties in the application. Among the methods outlined is the suggested by the
USGS to use a mosaic of at least 2 images of the same sector.
The main obstacle to using the above method was implemented in software, but a group of
scientists can adapt the method to work. Although in my opinion It doesdnt produce good
The methods can be found at:
The method developed First, the Fill Gap model was conducted in a practical and simplified way. I chose to work in
ArcGIS Desktop Platform 9.3 10 for the experience to be had with this software.
The algorithm that is created is shown in the following flowchart:
Identify invalid pixcels Pixel=0
Erase pixel = 0 (SetNull)
Keep pixel value
Interpolate values with valid data
Build attributes table
Raster witouth values 0"
Filling gaps: Original Raster= 0
Take the value of Raster original
Take the value of Smoothed
Original Raster: band.tif
The Original Raster can be any Landsat band or any clip
The model must be executed many times as needed
The Filled Raster can be used like a new original Raster
Description of the algorithm: 1. Select one to one Landsat bands that will be filled
2. The selected band will be our "Original Raster", we may even make a cut in our area of
interest to optimize model performance.
3. Create the table of attributes for the Original Raster, is important because we are working
4. By the condition "value = 0" delete cells with values of 0, using the tool SetNull
5. We proceed to use the Neighborhood tools, in this case we use the Filter LOW. This will
create a Smoothed Raster that fills the gaps with an average cell.
About the use of Filter LOW. - This point is one of the most important model, here are filled
the gaps of the image, the same can use different tools from which are Block Statistics,
Statistics Focal these two options fill with statistics (means, medians, etc..). Filter LOW was
chosen because of my appreciation is the one with better results, in part because it makes
processing of data on the type of interpolation. Despite my choice can still testing the use of
the Statistics Tools (Block or Focal).
6. Finally replace the cells with value = 0 of the Original Raster to Raster Smoothed values,
using the tool condition "Con"
The Gap Fill in ArcGis 9.3 10 Part1
NOTE: If you find another Neighborhood tools (Focal or Block Statistics) best suited to your
project you must replace Filter and Filter (2) by your new choice.
You can download the model here:
Or you can send me a e-mail to firstname.lastname@example.org or email@example.com
Annex: How Filter Works SOURCE:
Filter calculates new z-values by centering the specified 3 x 3 filter over each input
raster cell. As the filter is passed over each cell, the center is assigned the sum of
the products of the cell value and the corresponding operand in the 3 x 3 filter.
Consider the following nine raster cells and 3 x 3 filter:
The output raster cell at the center of the filter (Z5) is assigned a z-value based on
the following formula:
Z = Z1*F1 + Z2*F2 + Z3*F3 + ... + Z9*F9
When an input raster cell on the edge of the filter has a NoData value, the z-value
of the cell is substituted for the missing z-values.
On the edges of the raster, the filter lies partially outside the raster. When this
occurs, the z-value of the cell at the center of the filter is substituted for the
The LOW option is an averaging filter. The nine z-values are weighted
equally to calculate the value of the center cell.
The sum of the weights for the low pass filter is 1.000. This ensures that the
general elevation of the surface is maintained after smoothing.
The 3 x 3 filter for the LOW option is:
1/9 1/9 1/9
1/9 1/9 1/9
1/9 1/9 1/9 (where 1/9 is approximately = 0.11111...)
In the following example, the input raster has an anomalous data point
caused by a data collection error. The averaging characteristics of the LOW option
have smoothed the anomalous data point.
This example shows the resulting raster generated by FILTER with the LOW option
on a demonstration raster. Partial listings of the input and output raster cell values
are provided for comparison. Note how the NODATA locations are processed.
2.000 3.000 4.000 5.000 6.000
2.000 3.000 4.000 NODATA 6.000
2.000 3.000 4.000 5.000 6.000
2.000 30.000 4.000 5.000 NODATA
1.000 2.000 2.000 3.000 NODATA
After the low pass filter is performed, the values on the output raster are:
2.333 3.000 3.889 5.000 5.778
2.333 3.000 3.889 NODATA 5.778
5.333 6.000 6.889 4.889 5.778
5.000 5.556 6.444 4.333 NODATA
4.667 5.111 5.889 3.111 NODATA
MODELO: Gap Fill para imagines Landsat 7Una alternativa de correccin al SLC-off
AUTOR: Luis Vega Bustillos, Ingeniero Ambiental
FECHA: Julio de 2012
Sobre el SLC-off
Las imgenes del satlite Landsat 7 a partir del 2003 sufre del fallo en su sistema SLC, el SLC
es la parte del sensor ETM+ que compensa el movimiento hacia adelante del satlite durante la
adquisicin de las imgenes. Sin el SLC, el rea escaneada por el sensor delinea un patrn de
zigzag provocando un bandeado o efecto gaps en la imagen, como se muestra a continuacin:
Una vez revisados varias metodologas propuestas por la USGS y por autores independientes
surgieron algunas dificultades para su aplicacin. Entre los mtodos destacados est el
sugerido por la USGS para usar un mosaico de por lo menos 2 imgenes del mismo sector.
El principal obstculo para utilizar el anterior mtodo fue la implementacin en un software;
sin embargo un grupo de cientficos puedo adaptarlo para que el mtodo trabaje. A pesar de
esto no se obtuvieron buenos resultados.
El mtodo creado
En primer lugar, el modelo Gap Fill se llev a cabo de