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3. Image classification. The objective of these operations is to replace visual analysis of the image data with quantitative techniques for automating the identification of features in a scene. This normally involves the analysis of multispectral image data and the application of statistically based decision rules for determining the land cover identity of each pixel in an image. When these decision rules are based solely on the spectral radiances observed in the data, we refer to the classification process as spectral pattern recognition. In contrast, the decision rules may be based on the geometric shapes, sizes, and patterns present in the image data. These procedures fall into the domain of spatial pattern recognition. In either case, the intent of the classification process is to categorize all pixels in a digital image into one of several land cover classes, or "themes." These categorized data may then be used to produce thematic Inaps of the land cover present in an image and/or produce summary statistics on the areas covered by each land cover type. Due to their importance, image classification procedures comprise the subject of more than one-third of the material in this chapter (Sections 7.7 to 7.16). We emphasize spectral pattern recognition procedures because the current state-of-the-art for these procedures is more advanced than for spatial pattern recognition approaches. (Substantial research is ongoing in the development of spatial and combined spectral/spatial image classification.) We emphasize "supervised," "unsupervised," and "hybrid" approaches to spectrally based image classification. We also describe various procedures for assessing the accuracy of image classification results

Georeferencing is crucial to making aerial and satellite imagery, usually raster images, useful for mapping as it explains how other data, such as the above GPS points, relate to the imagery.

Very essential information may be contained in data or images that were produced at a different point of time. It may be desired either to combine or compare this data with that currently available. The latter can be used to analyze the changes in the features under study over a period of time.

Different maps may use different projection systems. Georeferencing tools contain methods to combine and overlay these maps with minimum distortion.

Using georeferencing methods, data obtained from surveying tools like total stations may be given a point of reference from topographic maps already available.

It may be required to establish the relationship between social survey results which have been coded with postal codes or street addresses and other geographic areas such as census zones or other areas used in public administration or service planning.

Methods[edit]