metode gap fill menggunakan arcgis

Download metode Gap Fill menggunakan ArcGis

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cara memperbaiki citra landsat 7 yang rusak (stripping)

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    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

    E-MAIL: luispvb@gmail.com

    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

    image data.

  • 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:

    http://landsat.usgs.gov/using_Landsat_7_data.php

    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

    results.

    The methods can be found at:

    http://landsat.usgs.gov/sci_an.php

    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:

    Gap Filling

    Identify invalid pixcels Pixel=0

    Erase pixel = 0 (SetNull)

    Yes

    Keep pixel value

    No

    Interpolate values with valid data

    (Filter LOW)

    Build attributes table

    Raster witouth values 0"

    Smoothed Raster

    Filling gaps: Original Raster= 0

    Take the value of Raster original

    Take the value of Smoothed

    Raster

    NoYes

    Filled Raster

    Original Raster: band.tif

    Process

    Condition

    Start

    Result

    Leyend:

    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

    with ArcGIS.

    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

    Part2

    Part3

  • 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.

    The Link

    You can download the model here:

    https://rapidshare.com/files/1632645659/GapFill.tbx

    Or you can send me a e-mail to luispvb@gmail.com or nomoxxx@gmail.com

    Annex: How Filter Works SOURCE:

    http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=How%20Filter%20works

    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

    missing z-values.

    Low

    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.

  • Example

    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

    E-MAIL: luispvb@gmail.com

    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