what is the minimum number of control points you must use to properly georeference an aerial photo?

Raster data is obtained from many sources, such every bit satellite images, aerial cameras, and scanned maps. Modern satellite images and aerial cameras tend to have relatively accurate location data, merely might need slight adjustments to line upwards all your GIS data. Scanned maps and historical data usually do not contain spatial reference information. In these cases y'all will need to employ authentic location data to align or georeference your raster data to a map coordinate system. A map coordinate system is defined using a map projection-a method by which the curved surface of the world is portrayed on a flat surface.

When you georeference your raster data, you lot define its location using map coordinates and assign the coordinate system of the map frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with your other geographic data. The georeferencing tools on the Georeference tab allows you to georeference any raster dataset.

In general, there are four steps to georeference your data:

1. Add the raster dataset that you want to marshal with your projected data.
2. Use the Georeference tab to create control points, to connect your raster to known positions in the map
3. Review the control points and the errors
4. Save the georeferencing outcome, when you are satisfied with the alignment.

Aligning the raster with control points

Generally yous will georeference your raster information using existing spatial data (target data), such as georeferenced rasters or a vector feature course that resides in the desired map coordinate organization. The process involves identifying a series of basis command points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data. Control points are locations that tin be accurately identified on the raster dataset and in real-earth coordinates. Many different types of features can be used as identifiable locations, such equally road or stream intersections, the oral cavity of a stream, stone outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows.

The control points are used in conjunction with the transformation to shift and warp the raster dataset from its existing location to the spatially correct location. The connexion between one control point on the raster dataset (the from indicate) and the corresponding control point on the aligned target data (the to point) is a control point pair.

The number of links you need to create depends on the complication of the transformation you plan to apply to transform the raster dataset to map coordinates. However, adding more links will non necessarily yield a better registration. If possible, you lot should spread the links over the unabridged raster dataset rather than concentrating them in one area. Typically, having at least one link near each corner of the raster dataset and a few throughout the interior produces the all-time results.

More often than not, the greater the overlap betwixt the raster dataset and target data, the meliorate the alignment results, because you lot'll take more widely spaced points with which to georeference the raster dataset. For example, if your target data only occupies one-quarter of the surface area of your raster dataset, the points you could use to marshal the raster dataset would be confined to that area of overlap. Thus, the areas outside the overlap area are not likely to be properly aligned. Keep in mind that your georeferenced information is only as accurate equally the data to which it is aligned. To minimize errors, yous should georeference to data that is at the highest resolution and largest scale for your needs.

Transforming the raster

When you've created plenty control points, you tin can transform the raster dataset to the map coordinates of the target data. You take the choice of using several types of transformations, such as polynomial, spline, adjust, projective, or similarity, to make up one's mind the correct map coordinate location for each cell in the raster.

The polynomial transformation uses a polynomial built on command points and a least-squares fitting (LSF) algorithm. It is optimized for global accurateness but does not guarantee local accurateness. The polynomial transformation yields two formulas: i for computing the output x-coordinate for an input (x,y) location and one for calculating the y-coordinate for an input (x,y) location. The goal of the least-squares fitting algorithm is to derive a general formula that tin can exist applied to all points, usually at the expense of slight move of the to positions of the control points. The number of the noncorrelated control points required for this method must be ane for a zero-order shift, 3 for a first society affine, half dozen for a 2d order, and x for a tertiary order. The lower order polynomials tend to give a random blazon error, while the higher order polynomials tend to give an extrapolation error.

A zero-order polynomial is used to shift your data. This is usually used when your data is already georeferenced, but a small shift will better line upwards your data. Only one control point is required to perform a nix-society polynomial shift. Information technology may be a adept idea to create a few control points, then choose the i that looks the nearly accurate.

The get-go-order polynomial transformation is unremarkably used to georeference an image. Use a kickoff-order or affine transformation to shift, scale, and rotate a raster dataset. This mostly results in straight lines on the raster dataset mapped as direct lines in the warped raster dataset. Thus, squares and rectangles on the raster dataset are normally changed into parallelograms of arbitrary scaling and angle orientation. Below is the equation to transform a raster dataset using the affine (offset order) polynomial transformation. You can encounter how six parameters define how a raster'south rows and columns transform into map coordinates.

With a minimum of three command points, the mathematical equation used with a first-gild transformation can exactly map each raster point to the target location. Any more than iii command points introduces errors, or residuals, that are distributed throughout all the control points. However, you lot should add more than three control points, because if one command is inaccurate, it has a much greater impact on the transformation. Thus, even though the mathematical transformation fault may increase equally you create more links, the overall accurateness of the transformation will increase as well.

The higher the transformation lodge, the more circuitous the baloney that tin can be corrected. Even so, transformations higher than 3rd order are rarely needed. College-order transformations require more than links and, thus, volition involve progressively more processing fourth dimension. In general, if your raster dataset needs to be stretched, scaled, and rotated, use a starting time-lodge transformation. If, however, the raster dataset must exist bent or curved, employ a 2nd- or 3rd-society transformation.

The conform transformation optimizes for both global LSF and local accuracy. It is built on an algorithm that combines a polynomial transformation and triangulated irregular network (TIN) interpolation techniques. The accommodate transformation performs a polynomial transformation using two sets of control points and adjusts the command points locally to better friction match the target control points using a TIN interpolation technique. Arrange requires a minimum of three command points.

The similarity transformation is a first order transformation which tries to preserve the shape of the original raster. The RMS error tends to be higher than other polynomial transformations since the preservation of shape is more important than the best fit. Similarity requires a minimum of iii command points.

The projective transformation can warp lines so that they remain straight. In doing and so, lines which were in one case parallel may no longer remain parallel. The projective transformation is especially useful for oblique imagery, scanned maps, and for some imagery products such equally Landsat and Digital World. A minimum of 4 links are required to perform a projective transformation. When only four links are used, the RMS error volition be nothing. When more points are used, the RMS fault will be slightly above zero. Projective requires a minimum of iv control points.

The spline transformation is a true safety sheeting method and optimizes for local accuracy but not global accuracy. It is based on a spline function, a piecewise polynomial that maintains continuity and smoothness between adjacent polynomials. Spline transforms the source control points exactly to target control points; the pixels that are a distance from the command points are not guaranteed to be accurate. This transformation is useful when the command points are important, and it is required that they exist registered precisely. Adding more control points tin increase overall accurateness of the spline transformation. Spline requires a minimum of 10 control points.

Interpret the root hateful foursquare error

When the general formula is derived and applied to the control point, a measure of the residual mistake is returned. The mistake is the difference between where the from point ended up as opposed to the actual location that was specified. The total error is computed by taking the root hateful square (RMS) sum of all the residuals to compute the RMS mistake. This value describes how consequent the transformation is between the different control points. When the fault is especially large, you can remove and add control points to adjust the error.

Although the RMS error is a skilful assessment of the transformation's accurateness, don't misfile a depression RMS error with an accurate registration. For example, the transformation may withal contain pregnant errors due to a poorly entered control betoken. The more control points of equal quality used, the more accurately the polynomial can catechumen the input data to output coordinates. Typically, the adjust and spline transformations requite an RMS of nearly zero; withal, this does not hateful that the prototype will be perfectly georeferenced.

The forward residual shows you lot the error in the aforementioned units equally the data frame spatial reference. The inverse rest shows you the error in the pixels units. The forrard-inverse residual is a mensurate of how shut your accuracy is, measured in pixels. All residuals closer to zero are considered more accurate.

Persist the georeferencing information

Y'all can permanently transform your raster dataset later georeferencing it by using the Save to New command on the Georeference tab or by using the Warp tool. You can as well store the transformation data in the auxiliary files using the Save control on the Georeference tab.

Salvage to New or the Warp geoprocessing tool will create a new raster dataset that is georeferenced using the map coordinates and the spatial reference. ArcGIS doesn't require y'all to permanently transform your raster dataset to display it with other spatial data; however, you should do so if yous plan to perform analysis with it or want to use it with some other software package that doesn't recognize the external georeferencing data created in the world file.

Saving the georeferencing volition store the transformation data in external files-it will not create a new raster dataset, which happens when you permanently transform your raster dataset. For a raster dataset that is file based, such as a TIFF, the transformation will generally be stored in an external XML file that has an .aux.xml extension. If the raster dataset is a raw image, such as BMP, and the transformation is affine, information technology volition be written to a world file. For a raster dataset in a geodatabase, Salvage will store the geodata transformation to an internal auxiliary file of the raster dataset.

Related topics

• Georeferencing tools
• Warp
• Warp From File
• Auxiliary files
• World files for raster datasets

---

Feedback on this topic?

madigantwoured.blogspot.com

Source: https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/overview-of-georeferencing.htm

Share this post