Automated Classification of Agricultural Lands Using GIS and NES

  • Authors

    • V. K. Kalichkin
    • A. I. Pavlova
    • A. F. Petrov
    • V. A. Smolyakov
    2018-12-03
    https://doi.org/10.14419/ijet.v7i4.38.27751
  • GIS, NES, Topography, Agricultural Land, Classification, Elementary Surfaces.

  • Abstract

    The article proposes the methodology for the automated classification of uplands using Geographic Information System (GIS) and Neural Expert System (NES). Quantitative indicators of topography are used as the basis of the proposed classification. A database consisting of topographic, soil, and land use maps was created using ArcGIS 10 geographic information system. A topologically correct digital elevation model (DEM) was created by the ANUDEM interpolation method. The DEM contains the following maps: hypsometric, steepness and slopes exposure, plan, profile, common curvature of the ground surface, and cumulative runoff maps. The boundaries of elementary surfaces (ES), which are homogeneous morphological formations, are established. Parameters characterizing the Stream Power Index (SPI) are taken into account. The essence of the proposed classification consists in attributing of ES to a certain group of lands based on aggregate of features. To do this, partial scales were created, containing indicators of topography, soil cover, land drainage conditions, as well as the degree of erosion development. The authors formed knowledge base for traning the NES using GIS database and partial scales of estimates. Teaching of neural network was carried out. The classification and topology of land was carried out by means of the NES. The uplands are distributed in flat and slightly convex areas. They are characterized by the following indicators: the curvature of the ground surface: plan curvature (0 – 0.03), profile curvature (0 – 0.15), common curvature (0 – 0.22); slope angles (less than 1.5о); horizontal dissection in elevation (less than 0.5 km/km2), vertical dissection (less than 5 m); and SPI (from -13.80 to -6.47). Electronic map of uplands of LLC «Salair» land-use area was created in the ArcGIS 10 environment.

     

     

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  • How to Cite

    K. Kalichkin, V., I. Pavlova, A., F. Petrov, A., & A. Smolyakov, V. (2018). Automated Classification of Agricultural Lands Using GIS and NES. International Journal of Engineering & Technology, 7(4.38), 1146-1149. https://doi.org/10.14419/ijet.v7i4.38.27751

    Received date: 2019-02-21

    Accepted date: 2019-02-21

    Published date: 2018-12-03