13
3.4.2.1. Geometric Correction
Geometric correction on the image aims to reduce the geometric error, so that the resulting geometric corrected image. In this study, geometric correction is done
by a method based on the Ground Control Point GCP. Reference data used for the selection was Indonesia Topographical Map Tanah Laut Regency, year 2007 of GCP
with the scale 1: 50.000. GCP sought is spread evenly and relatively permanent, such as roads, rivers, bridges. Interpolation was performed using nearest neighborhood
interpolation method. This method is most efficient and does not change the digital value of the original number. GCP elimination was performed to get Root Mean
Squared Error RMSE value 1.0 pixels.
RMSE is expressed by the formula: RMSE =
2
with - P
1
-P
2
+ L
1
-L
2
Where P and L are the estimated coordinates, P and L are the original coordinates of GCP Jaya, 1997.
3.4.2.2. Radiometric Correction
The aim of radiometric correction to make correction of the bias in the digitalpixel brightness values measured on the histogram data channels of spectral
imagery, which is caused by the atmospheric disturbances or due to an error detector response. Radiometric correction to use the minimum histogram method. At a
minimum histogram method, the atmospheric disturbance allegedly some of the smallest value measured on each channel plot histograms of multi channel digital
image. To eliminate the atmospheric interference from multi-channel data it is done by subtracting the smallest digital value to each digital pixel value measured in each
channel image Lillesand and Kiefer, 1994.
14
3.4.2.3. Cropping
Study area should be cropped to avoid any disturbance influence of other objects beyond the concern area and to reduce size data processing can be made
shorter. The administrative boundary of Tanah Laut Regency was used area of interest aoi.
3.4.2.3. Supervised Classification
Image classification is useful to obtain landcover from remote sensing imagery. Supervised classification with Maximum Likelihood method. This
classification is aimed to classify pixel values in the image into several classes based on the training area. Classes were determined namely pastures, corn fields, forests,
settlements, water body, paddy field, palm plantations, and rubber plantations. This process is resulted land cover Tanah Laut regency.
3.4.2.4. Validation Results of Classification
Kategori