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Mapping of topsoil texture in Hungary using classification trees

Author

Listed:
  • Annamária Laborczi
  • Gábor Szatmári
  • Katalin Takács
  • László Pásztor

Abstract

Spatial information about physical soil properties is in great demand, being basic input data in numerous applications. Soil texture can be characterized by different approaches, such as particle size distribution, plasticity index or soil texture classification. In accordance with the increasing demands for spatial soil texture information, our aim was to compile a topsoil texture class map for Hungary with an appropriate spatial resolution, using the United States Department of Agriculture soil texture classes. The ‘Classification and Regression Trees’ method was applied because it is widely used in Digital Soil Mapping, and has numerous advantages. Primary soil data were provided by the Hungarian Soil Information and Monitoring System. A digital elevation model and its derived components, geological and land cover map, and appropriate remotely sensed products together with the soil map featuring overall physical properties provided by the Digital Kreybig Soil Information System were used as auxiliary environmental co-variables. The resulting map can be used as direct input data in meteorological and hydrological modelling as well as in spatial planning.

Suggested Citation

  • Annamária Laborczi & Gábor Szatmári & Katalin Takács & László Pásztor, 2016. "Mapping of topsoil texture in Hungary using classification trees," Journal of Maps, Taylor & Francis Journals, vol. 12(5), pages 999-1009, October.
  • Handle: RePEc:taf:tjomxx:v:12:y:2016:i:5:p:999-1009
    DOI: 10.1080/17445647.2015.1113896
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    Cited by:

    1. Mohamed Ali Mohamed, 2020. "Classification of Landforms for Digital Soil Mapping in Urban Areas Using LiDAR Data Derived Terrain Attributes: A Case Study from Berlin, Germany," Land, MDPI, vol. 9(9), pages 1-26, September.

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