Orthophotos and Processes

Digital orthophotography (similar in appearance to aerial photography) is a computerized database which gives accurate distance measures and is, therefore, an accurate base for planimetric (i.e., road, stream), cadastral (i.e., tax parcel) and application specific mapping and database development. The scale of the DO (Digital Orthophoto) is 1:1,500 (1"=125) scale product, with a pixel resolution of approximately one foot.

Digital orthophoto - A digital image that has the properties of an orthographic projection. It is derived from a digitized perspective aerial photograph and other remotely sensed image data by differential rectification so that image displacements caused by camera tilt and terrain relief are removed.

Scanning an aerial photograph transparency (diapositive) with a precision image scanner creates the digital orthophoto. The scanned data file is then digitally rectified to an orthographic projection by processing each image pixel through photogrammetric space resection equations. This process requires, as input, ground control points acquired from ground surveys or developed in aerotriangulation, conjugate photo coordinates of ground control, camera orientation parameters, and a digital elevation model (DEM) with the same area of coverage as the digital orthophoto.  These inputs are used to register the image file to the scanner and to the sensor platform, to determine the orientation and location of the sensor platform with respect to the ground, and to remove the relief displacement from the image data.

Orthophoto for Map Revision/Creation of Vector Layers
Orthophoto is an ideal tool for assessing the completeness and correctness of vector data. Overlaying vectors on imagery immediately draws attention to areas of change, errors of omission and geometric inconsistencies. Also, orthophoto is an ideal tool for creation of a new vector layer(s). In practice, however, the use of digital orthophoto for creation of a data layer is not as simple an exercise as one would think.  There are three issues which arise: mismatches between existing vectors and the image; displacement of vertical structures; and the lack of photons due to obstruction.

Each of these problems causes the operator to question the validity of data, prompts analysis and necessitates decisions. When the existing vectors do not fit the image data exactly, one must decide whether to fix the existing vectors or adjust the new information compiled from the image. This decision can result in significant spatial inconsistencies over the area.  The data  I used in my project did not encounter this problem.  Pervious collected vector data overlaid the raster data as expected.  In addition, a city official located in the Information Services Division stated that the raster data had the proper geometric data applied which corrected for mismatches between vector data and the image.

Regardless of the amount of geometric correction performed on the image data, as the data moves away from nadir, the structure(s) will have displacement of vertical structures.  In my project,  there were no tall buildings or other structures to cause a problem with vertical displacement.  One problem  to be resolved was the distortion of shapes due to the sun angle and the objects distance from nadir.  The features that exhibit this phenomena were sidewalks.  The widths of the sidewalks often vary in shape; whereas, I digitized the features as I saw them.

The last problem, the lack of photons (or energy) reaching the sensors in the aircraft due to obstruction, was a common problem.  The cause of the problem was primarly shadows caused by the building or by trees.  Depending on the location of a building and the sun angle, several times the shadow of the building or tree would block photons reaching the sensors.  The results cause the image's spectral resolution to be diminished.  Often, parts of a house's rooftop were difficult to determine the exact shape and position.  Additionally, shadows from the buildings and/or trees would obstruct the outline of the driveways and associated impervious structures.

I took extreme measures to look for structure patterns to determine the proper extent of objects that were compiled.  I will note here that digitization requires human interactions.  People will make mistakes while digitizing; therefore, I  have no doubt that I made mistakes.  I strive for perfection so the digitized vector layer would reflect ground truth.

Data Characteristics

Spatial Resolution
Resolution is the minimum distance between two adjacent features or the minimum size of a feature that can be detected by a remote sensing system. The ground sample distance (GSD) is the distance on the ground represented by each pixel in the x and y components. The ground sample distance of the digital orthophoto is a result of the scanning aperture of the microdensitometer used to capture the digital image and the resampling algorithm. For example, if a scanning aperture of 25 micrometers is used on a 1:40,000 photo scale image, the ground (pixel) sample distance is approximately 1 meter. A 15 micrometer scan equates to a 0.6 meter while a 7.5 micrometer scan yields a pixel size of 0.3 meters. For the processed image, the GSD is 1 foot for digital orthophoto.

Spectral Range
In order to assure that the image brightness values of the orthophoto closely portray the source imagery, very little image enhancement, other than a limited amount of analog dodging, is performed when preparing the photograph for scanning. Some deviation of brightness values may also occur during the scanning and rectification processes. Radiometric accuracy and quality are verified through visually inspecting and comparing the digital orthophoto to the original unrectified image.

Data Organization
A gray scale digital orthophoto has the following characteristics:

Radiometric image brightness data which are stored as 256 gray levels and represented as integers in the  range of 0-255 formatted as a tiff image..

The ground sample distance of the image is one foot.

The geographic extent of the digital orthophotos is 50+ square miles from M-14 on North to Morgan Road on the South.  The range extends from Wagner Road on the West to Gale Road on the East..

Standard digital orthophotos are cast on the Michigan State Plane - South Zone projection on the North American Datum of 1983 (NAD83) with coordinates in feet.

The ordering of the data is by lines (rows) and samples (columns) with each line containing a series of  pixels ordered from west to east. The order of the lines is from north to south. When displayed on a computer, the image projection grid north is at the top.

The four primary datum (NAD83) corners are imprinted into the image as four solid white crosses with an image value of 255 and the four secondary datum corners as four dashed white crosses with similar intensity values.

Data Availability

Obtaining Data
The raster data was obtained from the City of Ann Arbor. For additional information to obtain digital orthorectifiedphoto, contact Mr. Merle Johnson, Information Services Division.

URL address: http://www.ci.ann-arbor.mi.us