Open AccessTechnology Development for Detecting Inhomogeneities in Agricultural Fields
Author(s) -
Petr Skobelev,
Vitaliy Travin,
Elena Simonova,
Vladimir Galuzin,
Anastasiya Galitskaya
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a9830.109119
Subject(s) - computer science , field (mathematics) , precision agriculture , software , computation , multispectral image , remote sensing , zoning , data mining , algorithm , agriculture , artificial intelligence , mathematics , engineering , geography , civil engineering , archaeology , pure mathematics , programming language
The paper addresses the relevant problem of identifying inhomogeneities in crop development based on analysis of multispectral images obtained from Earth remote sensing (ERS) satellites and unmanned aerial vehicles. Various techniques for detection of inhomogeneities are considered, which are based on computation of normalized difference vegetation index and its analysis, but do not take into account stages of crop production. The authors propose an original method and new algorithms for detecting inhomogeneities that take into account field zoning at various stages of the plant development cycle: preparing the field for sowing, emergence, and development of seedlings, heading. The paper also describes comparative analysis of results of the algorithms described in this paper and those of system-analogs. This analysis confirms effectiveness of the proposed algorithms. The method and algorithms for detection of inhomogeneities, developed by the authors, are used in the software module of image processing and presentation of ERS results for solving problems of precision farming, providing prompt, flexible, and efficient results for consumers.