3.3. Framework of Research 3.3.1. Framework of Coastal Ecosystem Development Decision Making
The decision-making problem of land suitability analysis for coastal ecosystem development coastal land use planning is analyzed using integration of
remote sensing, GIS and MCDM. Fig 3.2 depicts the conceptual flow of the
research approach completely.
3.3.2. Data Compilation
Data used for this research are primary and secondary data. Primary data was derived from remote sensing imagery Landsat TM, while secondary data
was derived from field check and some institutions. Compiling data is needed to recognize research location and to build model of coastal landuse development
planning.
3.3.3. Image Preprocessing
For acquiring better geometric and radiometric aspects from Landsat TM imagery, geometric and radiometric corrections should be accomplished. It is the
first step prior to analysis of the remotely sensed data that is to remove errors. Geometric correction is a replacing pixel position as truly condition.
Geometric correction that is commonly used to make digital remote sensor data truly useful is geometric rectification. It is a process using Ground Control Point
GCPs, which are selected transform the geometry of the image so that each pixel corresponds to a position in a real world coordinate system.
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Diagram Alir Penelitian lihat file diagram
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RMS Roat Mean Square is differentiating between original coordinates based on line and row of GCP coordinates that are measured with square of
deviation of GCP on satellite imagery. Equation following: RMS
error =
√ x
i
– x
orig
2 + y
i
– y
orig 2
Where: x orig and y orig are original coordinate line and row. xi and yi are GCP from Imagery corrected.
Raw Image Radiometric Correction
Geometric Correction Corrected Image
Image Calibration Atmospheric Correction
Ground Control Point GCPs Rectification
Resampling to common grid
Fig 3.3. Image Preprocessing
Radiometric correction is one of histogram adjustment as a way to minimize bias. The effect of atmospheric scattering caused by particles is a
problem in imagery and should be removed or minimized to avoid bias in each spectral band. Radiometric correction is performed to reduce bias effect of
atmosphere on satellite imagery for good display, it means that pixel value on imagery is represented actual real value of field.
Radiometric correction on this research was done by displaying all histogram used to known actual value. The lowest spectral value must be 0 zero
as well as bit-coding sensor. The equation used for radiometric correction is:
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BV
ijout
= BV
i – l, j, k
+ BV
i+j, j,k
2 Where : BV
ijout :
Correction Result BV
i – l, j, k :
Actual Spectral Value BV
i+j, j,k :
Actual Value
3.4. Field Checking
