Optimization of scale and parametrization for terrain segmentation: An application to soil-landscape modeling

  • Authors:

  • Lucian Drgu;Thomas Schauppenlehner;Andreas Muhar;Josef Strobl;Thomas Blaschke

  • Affiliations:

  • Department of Geography and Geology, University of Salzburg, Hellbrunnerstraíe 34, Salzburg 5020, Austria and Department of Geography, West University of Timişoara, V. Pírvan Blv. 4 ...;Institute of Landscape Development, Recreation and Conservation Planning, Department of Landscape, Spatial and Infrastructure Sciences, BOKU University of Natural Resources and Applied Life Scienc ...;Institute of Landscape Development, Recreation and Conservation Planning, Department of Landscape, Spatial and Infrastructure Sciences, BOKU University of Natural Resources and Applied Life Scienc ...;Z_GIS-Centre for Geoinformatics, University of Salzburg, Schillerstraíe 30, Salzburg 5020, Austria and Austrian Academy of Sciences, Schillerstraíe 30, Salzburg 5020, Austria;Z_GIS-Centre for Geoinformatics, University of Salzburg, Schillerstraíe 30, Salzburg 5020, Austria and Research Studio iSpace, Schillerstraíe 25, Salzburg 5020, Austria

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2009

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Abstract

This paper presents a procedure to optimize parametrization and scale for terrain-based environmental modeling. The workflow was exemplified on crop yield data, which is assumed to represent a proxy for soil productivity. Focal mean statistics were used to generate different scale levels of terrain derivatives by increasing the neighborhood size in calculation. The degree of association between each terrain derivative and crop yield values was established iteratively for all scale levels through correlation analysis. The first peak of correlation indicated the scale level to be further retained. To select the best combination of terrain parameters that explains the variation of crop yield, we ran stepwise multiple regressions with appropriately scaled terrain parameters as independent variables. These techniques proved that the mean curvature, filtered over a neighborhood of 55m, together with slope, made up the optimal combination to account for patterns of soil productivity. To illustrate the importance of scale, we compared the regression results of unfiltered and filtered mean curvature vs. crop yield. The comparison shows an improvement of R^2 from a value of 0.01 when the curvature was not filtered, to 0.16 when the curvature was filtered within 55x55m neighborhood size. The results were further used in an object-based image analysis environment to create terrain objects containing aggregated values of both terrain derivatives and crop yield. Hence, we introduce terrain segmentation as an alternative method for generating scale levels in terrain-based environmental modeling, besides existing per-cell methods. At the level of segments, R^2 improved up to a value of 0.47.