Contributors: Jason Karl

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The Tasseled-Cap Transformation is a conversion of the original bands of an image into a new set of bands with defined interpretations that are useful for vegetation mapping. A tasseled-cap transform is performed by taking “linear combinations” of the original image bands - similar in concept to principal components analysis. So each tasseled-cap band is created by the sum of image band 1 times a constant plus image band 2 times a constant, etc… The coefficients used to create the tasseled-cap bands are derived statistically from images and empirical observations and are specific to each imaging sensor.

The first tasseled-cap band corresponds to the overall brightness of the image. The second tasseled-cap band corresponds to “greenness” and is typically used as an index of photosynthetically-active vegetation. The third tasseled-cap band is often interpreted as an index of “wetness” (e.g., soil or surface moisture) or “yellowness” (e.g., amount of dead/dried vegetation).

A tasseled-cap transformation produces the same number of output bands as input bands, but not all of the tasseled-cap output bands will be useful. Because of the similarity between tasseled-cap and principal components, the first tasseled cap contains the most information from the image and each subsequent band contains less of the original image information. Generally, the first three tasseled-cap bands contain useful information and the rest contain much of the image's “noise” and are not used.

The tasseled-cap transformation was originally defined by Kauth and Thomas (1976) based on a spectral analysis of the growth of wheat in fields. The transformation got it's name from the way that a graph looked when the red band values of pixels were plotted against the near infra-red pixel values. The tasseled-cap transformation coefficients were defined against this graph to maximize the separation of the different growth stages of wheat.

_{Image source: Kauth and Thomas (1976), axis labels added.}

The tasseled cap is a type of data transformation. Another commonly applied transformation similar to the tasseled cap is Principal Components Analysis. Other data transformations are used to calculate indices that are related to specific ecosystem attributes. Examples of these are the Normalized Difference Vegetation Index, the Enhanced Vegetation Index, and the Normalized Burn Ratio.

The output of a Tasseled-cap transformation is a new set of image bands that have specific interpretations. You will get the same number of bands out of a Tasseled-cap transformation as you put into it, but not all of them will be useful. In general, the majority of the information in an image will be contained in the first three Tasseled Cap bands. Band 4 is typically a “noise” band and contains little useful information. With a Tasseled-cap transformation on Landsat data, Tasseled-cap Band 5 may contain useful information, but Tasseled-Cap Band 6 will be another noise band.

• The Tasseled-cap transform is a commonly used technique in land cover mapping or other classification projects.
• Karl and Maurer (2009) and Karl and Maurer (in press) used Tasseled-cap transformations of Ikonos and Landsat data to look for optimal scales for deriving percent cover estimates in Idaho sagebrush ecosystems comparing object-based image segmentation and pixel aggregation.
• Karl (in press) demonstrated how Tasseled-cap transformed Landsat imagery could be used with the Regression Kriging technique

• Karl, J.W. and B.A. Maurer. 2009. Multivariate correlations between imagery and field measurements across scales: comparing pixel aggregation and image segmentation. Landscape Ecology.
• Karl, J.W. in press. Spatial predictions of cover attributes of rangeland ecosystems using regression kriging and remote sensing. Rangeland Ecology and Management.
• Karl, J.W. and B.A. Maurer. in review. Spatial dependence of predictions from image segmentation: a variogram-based method to determine appropriate scales for producing land-management information. Ecological Informatics.

• Crist, E.P., R. Laurin, and R.C. Cicone. 1986. Vegetation and soils information contained in transformed Thematic Mapper data. Pages 1465-1470 Ref. ESA SP-254. European Space Agency, Paris, France. http://www.ciesin.org/docs/005-419/005-419.html.
• Crist, E.P. and R.J. Kauth. 1986. The tasseled Cap De-Mystified. Photogrammetric Engineering and Remote Sensing 52:81-86.
• Crist, E.P. and R.C. Cicone. 1984. Application of the tasseled Cap Concept to Simulated Thematic Mapper Data. Photogrammetric Engineering and Remote Sensing 50:343-352.
• Crist, E.P. and R.C. Cicone. 1984. A Physically-Based Transformation of Thematic Mapper Data–The TM Tasseled Cap. IEEE Transactions on Geoscience and Remote Sensing 22:256-263.
• Horne, J. H. 2003. A tasseled cap transformation for IKONOS images. ASPRS 2003 Annual Conference Proceedings. ASPRS. http://www.geoeye.com/CorpSite/assets/docs/technical-papers/2003/E_HorneJamesH_2003.pdf.
• Ivits, E., A. Lamb, F. Langar, S. Hemphill, and B. Koch. 2008. Orthogonal transformation of segmented SPOTS images: seasonal and geographical dependence of the tasseled cap parameters. Photogrammetric Engineering and Remote Sensing 74:1351-1364.
• Jensen, J. R. 1996. Introductory digital image processing. Prentice-Hall, Inc., Upper Saddle River, NJ.
• Lobser, S.E. and W.B. Cohen. 2007. MODIS tasseled cap: land cover characteristics expressed through transformed MODIS data. International Journal of Remote Sensing 28:5079-5101.
• Kauth, R.J. and G.S. Thomas. 1976. The tasseled Cap – A Graphic Description of the Spectral-Temporal Development of Agricultural Crops as Seen by LANDSAT. Proceedings of the Symposium on Machine Processing of Remotely Sensed Data, Purdue University of West Lafayette, Indiana. pp. 4B-41 to 4B-51.
• Wang, Y. and D. Sun. 2005. The ASTER tasseled cap interactive transformation using Gramm-Schmidt method. pp 184-195 in L. Zhang, J. Zhang, and M. Liao (eds). Proceedings of the SPIE, Volume 6043.
• Yarborough, Easson, and Kuszmaul. 2004. ASTER sensor tasseled-cap coefficients for fused VNIR/SWIR L1-B data. ASPRS 2004 Annual Conference.

One of the biggest limitations to the Tasseled-cap Transformation is that it can only be applied to sensors for which transformation coefficients have already been developed. Currently, this includes Landsat,MODIS, ASTER, Ikonos, and SPOT. There are several instances of Tasseled-cap coefficients that were derived from one sensor being applied to another one (e.g., Landsat coefficients applied to Quickbird data), but this is generally not recommended.

Performing a Tasseled-cap transformation requires two things: 1) an input satellite image, and 2) a set of transformation coefficients specific to the sensor that acquired the image. Transformation coefficients can be defined to work with either radiance or reflectance, and it is important to know which the transformation coefficients have been defined for (and which your image is using!).

There are no special hardware requirements to perform a tasseled-cap transformation. In terms of software requirements, some sort of program that can perform image/raster operations on a cell-by-cell basis is needed. Most remote sensing packages have the ability to do simple image arithmetic (i.e., multiply bands by a constant value and add the results together on a cell-by-cell basis). Some remote sensing packages, like ERDAS Imagine, have Tasseled-cap functions. Tasseled-cap transformation, however, can be done in other programs like ArcGIS, R, SAS, or even some photo-manipulation programs (e.g., Photoshop, GIMP).

Example of the Tasseled-Cap transformation as applied to a 2007 Ikonos image in Craters of the Moon National Monument, Idaho.

• The Tasseled Cap Transformation in Remote Sensing by T Watkins. http://www.sjsu.edu/faculty/watkins/tassel.htm

• Organization information and/or project info
• Contact information (i.e., email, phone):

• Tasseled-cap transformations are computed from imagery on an as-need basis for specific application. No source is known to distribute pre-made tasseled-cap images.

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