A semantic multispectral images analysis retrieval method for interpreting deforestation effects in soil degradation

Irene Erlyn Wina Rachmawan, Yasushi Kiyoki

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

Abstract

Deforestation is still a major nature phenomenon in our society. For assessing deforestation effect, satellites remote sensing provides a fundamental data for observation. While new remote-sensing technologies are able to represent high-resolution forest mapping, the application is still limited only for detecting and mapping the deforestation area. In this paper, we proposed a new method for retrieve the information contained on Satellite Multispectral images in order to interpreting deforestation effect in the context of soil degradation. We proposed an idea to interpret reflected “substances (material)” of bare soil in deforested area in spectrum domain into human language. The objectives of this paper are to (1) recognize the deforestation activity automatically. (2) Identify deforestation causes and examines the deforestation effect based on deforestation causes. (3) Scrutinize deforestation effects on soil degradation. (4) Representing nature knowledge of deforestation effect by performing calculation for semantic retrieval, to bring the clear comprehensible knowledge even for people who are not familiar with forestry. Semantic retrieval formed by understanding queries and showing queries result based on semantic calculation. As for experimental study, Riau Tropical Forest has been selected as the study area, where the multispectral data was acquired by using Landsat 8 Satellite between 2013 and 2014; Where forest fire and logging activities are reported, and detected.

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
Pages90-109
Number of pages20
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

  • Computing
  • Deforestation
  • Dimensional database
  • Multispectral image
  • Retrieval
  • Semantic
  • Soil degradation

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint Dive into the research topics of 'A semantic multispectral images analysis retrieval method for interpreting deforestation effects in soil degradation'. Together they form a unique fingerprint.

  • Cite this

    Rachmawan, I. E. W., & Kiyoki, Y. (2018). A semantic multispectral images analysis retrieval method for interpreting deforestation effects in soil degradation. 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. 90-109). (Frontiers in Artificial Intelligence and Applications; Vol. 301). IOS Press. https://doi.org/10.3233/978-1-61499-834-1-90