Landform classification using terrain primitive signatures

Mark B. Lazaroff; Nancy J. DeFeo

doi:10.1117/12.21412

1 November 1990 Landform classification using terrain primitive signatures

Mark B. Lazaroff, Nancy J. DeFeo

Proceedings Volume 1301, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences; (1990) https://doi.org/10.1117/12.21412
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

A pattern recognition technique for terrain analysis is described which uses image processing and statistical inference techniques to classify landforms from an input Digital Elevation Model (DEM) and a database of previously stored patterns. The methodology involves the development of landform signatures from topographic primitives calculated from training areas in the DEM. Local statistical properties of characteristic distributions of primitives are calculated from spatial cooccurrence matrices. Unknown terrain in DEMS can then be classified using an associative memory technique. The method is easily scaled in terms of the number of patterns that can be stored in the database as well as the amount of generalization performed by the associative memory.

Citation Download Citation

Mark B. Lazaroff and Nancy J. DeFeo "Landform classification using terrain primitive signatures", Proc. SPIE 1301, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences, (1 November 1990); https://doi.org/10.1117/12.21412

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