URBAN GROWTH DETECTION USING TEXTURE ANALYSIS ON MERGED LANDSAT TM AND SPOT-P DATA

This paper develops a texture analysis procedure to distinguish "built" from "non-built" pixels at a meaningful scale of resolution to serve planning needs, and applies the technique to imagery from two dates in order to monitor and measure urban growth patterns accurately. The methodology used digitally merged Landsat thematic mapping and SPOT-P data, resampled to 10 meters, for 1990 and 1995. For each date, a two-step texturing analysis resulted in a binary "built/non-built" map defining urban versus non-urban super pixels. Results from the study clearly defined "growth" pixels for the five-year time interval, with an accuracy of 92 percent. These growth pixels were then compared to a growth potential map produced by a geographic information systems analysis based on environmental inducements and constraints to growth. Results showed that the portions of the study area that were rated highest in growth potential did in fact experience the largest amount of urban expansion. Application of this technique over time is shown to provide an effective tool to identify, map, monitor and quantify patterns of urban growth and change.

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