Application of the semivariogram textural classifier (STC) for vegetation discrimination using SIR‐B data of the guiana shield, northwestern brazil

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Abstract
In 1984, the Shuttle Imaging Radar‐B (SIR‐B) acquired digital data over an inaccessible, heavily‐vegetated and generally cloud‐covered region of the Guiana Shield in northwestern Brazil. Available natural resource information in this area is limited to a reconnaissance survey conducted by the RADAMBRASIL Project at a 1:1,000,000 scale. Classification of this SIR‐B data set is performed using image texture. The algorithm used is the semivariogram textural classifier (STC). This is a deterministic, supervised parallelepiped type classifier which provides the option of combining textural and radiometric information. Textural information is expressed by the semivariogram function. Radiometric information is conveyed by the mean digital number (DN) value. Results have shown that the SIR‐B image representation of each cover type in the study area has a distinctive semivariogram, making feasible the discrimination of vegetation types and water bodies by means of STC.

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