However, the lowest RMSE does not automatically lead to the best transformation method. Keeping a close eye on the RMSE (error between the control point on each image) and running each transformation method, the initial response to selecting the appropriate method should be the one that produces the lowest RMSE. The next step was to select an transformation method that was felt to be appropriate. The raster cell resolution of the 19 images are 4 ft and 1 ft, respectively, which illustrates that control points between the two images are accurate at best to 4 ft. As you can imagine, this can be a challenge because selecting control points is subjective and identify correct coordinates has some inherent error based on the raster resolutions of both images. The idea was to identify points that were assumed to not have significantly changes from 1953 to 2002. I tried to select control points at corners of buildings, road intersections, and private parcel intersections. More control points were identified in both images. To get the 1953 image into the field of view, one control point was selected in both images so the 1953 image was simply moved to the general correct location.

Methods: Task 1The first step of this task was to identify control points that are analogous on both the 2002 imagery (already on a NAD 1983 State Plane California II FIPS 0402 feet coordinate system) and the 1953 imagery. As you increase the number of control points, the better the transformation should be while reducing distortion that may not be real. Note that the higher-order polynomial and adjust transformation methods cannot be used unless you have six control points. Selecting the appropriate transformation method depends on the number of control points available, the portion of imagery you wish to have georeferenced, and the amount of distortion from the original and acceptable RMSE. The transformation methods of original data in AcrMap to a defined coordinate system (georeferencing) are affine (1st-order polynomial), higher-order polynomials, and adjust. This was completed by selecting analogous control points on both the 1953 image and the 2002 image. In this task, a scanned non-georeferenced historic aerial photograph from 1953 is georeferenced to a more recent and correctly georefernced aerial photograph from 2002. Task 1: Georeferencing a Scanned Historical Image

In Task 2, higher-resolution aerial imagery obtained from a blimp platform was georeferenced to know ground points and compared to the 2002 imagery and the previously georeferenced 1953 imagery from Task 1. Next in this task, a portion of land use (undeveloped, agricultural, and urban) was compared from the two years to arrive at a change in percent land use. The 1953 imagery is from a scanned historic photograph while the imagery from 2002 has been georeferenced to a defined coordinate system. In Task 1, imagery from 1953 was georeferenced to imagery from 2002. To learn this skill of proper raster imagery georeferencing, we completed two distinct tasks in this lab exercise using imagery from Sulphur Creek that flows through St. This can provide managers and policy makers to effectively plan projects while minimizing impacts. For example, changes in river morphology over time can be compared and land usage change can be estimated. Georeferencing raster images has many useful applications and is an important skill to develop for producing maps and analyses. This may sometimes be tricky, however, based on raster resolution, transformation methods, and the number of available control points (assumed known points) used for aligning an image. Georeferencing is simply the process of correctly overlaying or aligning raster aerial imagery or imagery from a scanned map onto a map coordinate system. Introduction In this lab exercise we georeference a scanned historic photograph to a more current georeferenced digital aerial photograph, identify a change in land use, and finally georeference a high-resolution digital photograph taken from a blimp platform to known ground points.

3 Task 2: Georeferencing a Digital Aerial Photograph.

2 Task 1: Georeferencing a Scanned Historical Image.

Taskr georeference