Title of article :
Landscape similarity, retrieval, and machine mapping of physiographic units
Author/Authors :
Jasiewicz، نويسنده , , Jaroslaw and Netzel، نويسنده , , Pawel and Stepinski، نويسنده , , Tomasz F.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Pages :
9
From page :
104
To page :
112
Abstract :
We introduce landscape similarity — a numerical measure that assesses affinity between two landscapes on the basis of similarity between the patterns of their constituent landform elements. Such a similarity function provides core technology for a landscape search engine — an algorithm that parses the topography of a study area and finds all places with landscapes broadly similar to a landscape template. A landscape search can yield answers to a query in real time, enabling a highly effective means to explore large topographic datasets. In turn, a landscape search facilitates auto-mapping of physiographic units within a study area. The country of Poland serves as a test bed for these novel concepts. The topography of Poland is given by a 30 m resolution DEM. The geomorphons method is applied to this DEM to classify the topography into ten common types of landform elements. A local landscape is represented by a square tile cut out of a map of landform elements. A histogram of cell-pair features is used to succinctly encode the composition and texture of a pattern within a local landscape. The affinity between two local landscapes is assessed using the Wave-Hedges similarity function applied to the two corresponding histograms. For a landscape search the study area is organized into a lattice of local landscapes. During the search the algorithm calculates the similarity between each local landscape and a given query. Our landscape search for Poland is implemented as a GeoWeb application called TerraEx-Pl and is available at http://sil.uc.edu/. Given a sample, or a number of samples, from a target physiographic unit the landscape search delineates this unit using the principles of supervised machine learning. Repeating this procedure for all units yields a complete physiographic map. The application of this methodology to topographic data of Poland results in the delineation of nine physiographic units. The resultant map bears a close resemblance to a conventional physiographic map of Poland; differences can be attributed to geological and paleogeographical input used in drawing the conventional map but not utilized by the mapping algorithm.
Keywords :
Landscape search , web application , Landscape similarity , Supervised classification , Physiographic mapping , Pattern recognition
Journal title :
Geomorphology
Serial Year :
2014
Journal title :
Geomorphology
Record number :
2367323
Link To Document :
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