Image profiles show the spectral response of a selected feature along a user-specified cross-section. You can generate a spectral plot and a numeric values table from RGB or grayscale input channels along a user-defined vector.
There are several instances where you can use an image profile. Your work will determine when and where you should use one. Following are examples where profiles have been used effectively.
Profiling can give you an idea of the spectral homogeneity for a feature. If profiles taken across a feature are all relatively flat, the feature is considered homogeneous for the particular wavelength in which the profile is taken. Relatively flat profiles indicate that a particular wavelength channel is a good input for a subsequent supervised classification where the extracted features are being investigated.
As another example, you may want to establish a potential correlation between a characteristic of a feature in the scene and its spectral response. Such a correlation could be used in an image from the Coastal Zone Color Scanner (CZCS) satellite.
The CZCS satellite measures important ocean properties from space. It was designed specifically to measure the temperature and color of the coastal zones of the oceans. The CZCS operates in six wavelength regions (bands), including bands in the visible, near-infrared, and thermal regions of the electromagnetic spectrum. The four visible bands are used to map phytoplankton concentrations and inorganic suspended matter, such as silt. The near-infrared channel can be used to map surface vegetation, while the thermal channel can be used to measure sea surface temperatures.
You can use the Image Profile to examine changes in ocean properties as a function of distance from the coastline or along the perimeter of a coastline. You can demonstrate graphically how chlorophyll, temperature, suspended sediment, and gelbstoff (the yellow substance of interest to marine researchers) vary along the coastal waters in a CZCS image.
Drawn across a DEM, a profile will give information on how the elevation changes from one point to another, giving a cross-sectional perspective of the terrain.
The vector profile is normally interpreted from left to right; however, if the end points of the vector occupy the same X position, the profile is interpreted from top to bottom. In the event of a closed shape, the profile is interpreted in a clockwise direction from the start/end node of the closed shape.
The graph is a profile of the image layer and shows the input channels plotted with the gray values on the y-axis, and the distance along the vector on the x-axis. The graph demonstrates how the gray values change with distance.
In the case of an 8-bit RGB image layer, the range of the y-axis is 0 to 255 and represents the 256 possible gray-level values for each pixel of the red, green, and blue input channels.
The x-axis is measured in meters and represents the distance between the end points of the vector. The range of the x-axis depends on the length of the vector and the scale of the area or the ground distance covered by the image.
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