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  • Automatic clod detection and boundary estimation from Digital Elevation Model images using different approaches
  • The aim of this study is to propose and discuss some methods dedicated to the automatic localization of clods (or big aggregates) on Digital Elevation Model images of soil. Two new image processing methods are introduced. The first one deals
  • in an agricultural field. Results show that the proposed methods outperformed previously published methods. The implications are the automatic analysis of DEM images that is a step towards micro-topography statistical characterization.
  • 2014
  • ), and Oolitic (IN, USA). Five types of landform entities were defined : isolated hill (IH), clustered hills (CHs), isolated sinkhole (IS), clustered sinkholes (CSs), and clustered hills with sinkholes (CHSs). An algorithm was developed to automatically identify
  • 2014
  • The AA. developed a semi-automatic method to derive a chain-like directional network from images that represent the multi-channel river and to connect individual network elements through time. The Jamuna River was taken as an example with a series
  • 2014
  • mapped on different landscape units using very high-resolution (0.5 m/pixel) satellite imagery (WorldView-1 and GeoEye-1). In a geographic information system (GIS) environment, Thiessen polygons were automatically created to reconstruct relict ice-wedge
  • 2014