An application of multispectral semantic-image space for global farming analysis and crop condition comparisons

Jinmika Wijitdechakul, Yasushi Kiyoki, Shiori Sasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This system aims to realize and interpret environmental phenomena and changes occurring that happening in world wide scope. Semantic computing is important and promising approach to multispectral semantic-image analysis for various environmental aspects and contexts in physical world. In the previous study, we proposed a new system of agricultural monitoring and analysis based on semantic computing concept that it realizes the interpretation of agricultural health condition as human-level interpretation. In this paper, we propose a new analytical method for agriculture global comparisons to realize and recognize crop condition with several places in global scale. Multispectral semantic-image space for agricultural analysis can be utilized for global crop health monitoring by comparing crop conditions among different places. Our method applies semantic distance calculation to measure similarity among multispectral image data to realize the crop health condition as a ranking. According to our new proposed analytical method, we demonstrate a prototype implementation in the case of rye farm in Latvia and Finland. This prototype implementation shows an analysis in the case that image data have same crop type and conditions.

Original languageEnglish
Title of host publicationInformation Modelling and Knowledge Bases XXIX
EditorsNaofumi Yoshida, Chawan Koopipat, Yasushi Kiyoki, Petchporn Chawakitchareon, Aran Hansuebsai, Virach Sornlertlamvanich, Bernhard Thalheim, Hannu Jaakkola
PublisherIOS Press
Pages176-187
Number of pages12
ISBN (Electronic)9781614998334
DOIs
Publication statusPublished - 2018 Jan 1
Event27th International Conference on Information Modelling and Knowledge Bases, EJC 2017 - Krabi, Thailand
Duration: 2017 Jun 52017 Jun 9

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume301
ISSN (Print)0922-6389

Conference

Conference27th International Conference on Information Modelling and Knowledge Bases, EJC 2017
CountryThailand
CityKrabi
Period17/6/517/6/9

Keywords

  • Agricultural monitoring
  • Global farming analysis
  • Semantic computing
  • UAV-multispectral sensor

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Wijitdechakul, J., Kiyoki, Y., & Sasaki, S. (2018). An application of multispectral semantic-image space for global farming analysis and crop condition comparisons. In N. Yoshida, C. Koopipat, Y. Kiyoki, P. Chawakitchareon, A. Hansuebsai, V. Sornlertlamvanich, B. Thalheim, & H. Jaakkola (Eds.), Information Modelling and Knowledge Bases XXIX (pp. 176-187). (Frontiers in Artificial Intelligence and Applications; Vol. 301). IOS Press. https://doi.org/10.3233/978-1-61499-834-1-176