Download Lab 4 Questions Georectification is a tool that allows you to

Lab 4 Questions
1.
Georectification is a tool that allows you to transform paper maps or other images into an
ArcGIS layer; the process allows you to manually match up raster data with vector data in an
ArcGIS map. You begin by adding the shapefile and image to an ArcMap document. You then
use the georeferencing tools “fit to display” and “add control points” to better match up the
image with the shapefile. By adding control points, you can link readily identifiable images on
the image with those on the shapefile, aligning the image more and more closely with the
shapefile. Once the image and shapefile are matched up to your satisfaction, choose “rectify”
from the georeferencing menu and select the appropriate rectification method.
2. I or another researcher might use this technique in the future to compare older maps (which
must first be digitalized) with current satellite images of the same area. By comparing the area
now with a time of the past, changes in the landscape including property ownership and land
usage can be observed quite easily.
3. There are three different rectification methods available: nearest neighbor (for discrete data),
bilinear interpolation (for continuous data), and cubic convolution (for continuous data).
Nearest neighbor is a simple method of multivariate interpolation in one or more dimensions.
The nearest neighbor algorithm selects the value of the nearest point and does not consider the
values of neighboring points at all, yielding a piecewise-constant interpolant. Bilinear
interpolation is an extension of linear interpolation for interpolating functions of two variables
on a regular 2D grid. The idea is to perform linear interpolation first in one direction, and then
again in the other direction. Although each step is linear in the sampled values and in the
position, the interpolation as a whole is not linear but rather quadratic in the sample location.
Cubic convolution has a number of desirable features which make it useful for image processing.
The cubic convolution interpolation function converges uniformly to the function being
interpolated as the sampling increment approaches zero. With the appropriate boundary
conditions and constraints on the interpolation kernel, it can be shown that the order of
accuracy of the cubic convolution method is between that of linear interpolation and that of
cubic splines. I chose nearest neighbor (for discrete data).
4. The RME got larger as I added more points, because for each additional point added after the
third point, more potential for error was introduced. This is because the ArcMap assumes that
all of the points being paired have been clicked in precisely the right spot, even though human
nature leads to imprecise clicks that might be close to the desired point, but not exactly on it.