Materials and Methods
1.2.2. Geometric Correction of Remote Sensing Data:
The objective of geometric correction is to compensate for the distortions and degradations caused by the errors due to variation in altitude, velocity of the sensor platform, variations in scan speed and in the sweep of the sensors field of view, earth curvature and relief displacement. The method to do the geometric correction can be divided into two steps according to the different kinds of errors. For the systemic error, geometric correction can be done relatively easily and the errors are corrected for at the receiving station. The random distortion needs to be corrected by the analyst through selecting sufficient number of ground control points with correct coordinates usually from maps or GPS points, which can be accurately localized in satellite images. Then through a transformation function it determines the correct coordinates for the distorted image positions and forms an undisturbed output grid. After this, each cell in this new grid is assigned a grey level according to the corresponding pixel in the original image and the process is called resampling. As the cells in the original image and the new grid are not overlapped, the DN values cannot be assigned by simply overlaying the two but it is done through some interpolation methods. Commonly used resampling algorithms are:
Nearest Neighbour: The pixel value is assigned the DN value of the closest pixel in the original image. This method closely preserves the original image spectral information but because this method will cause one half pixels mismatched, so images resampled by this method are slightly disjointed.
Bilinear Interpolation: Distance weighted average is calculated over the four nearest pixels in the original image and this value is assigned to the new pixel. This method will change the original image information by changing the DN values of the pixels in the image.
Cubic Convolutions: A polynomial approach based on the values of sixteen surrounding pixels is applied and the values calculated by this approach are assigned to new pixels. This method will also change the original image information. The images used in this study are corrected geometrically by using the ground control points (GCP’s) from the field and resampled by nearest neighbour.
In this study the resampling algorithm used was nearest neighbour for the geometric correction of the images.