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

Irene Erlyn Wina Rachmawan, Yasushi Kiyoki

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルInformation Modelling and Knowledge Bases XXIX
編集者Petchporn Chawakitchareon, Aran Hansuebsai, Hannu Jaakkola, Yasushi Kiyoki, Naofumi Yoshida, Chawan Koopipat, Virach Sornlertlamvanich, Bernhard Thalheim
出版社IOS Press
ページ90-109
ページ数20
ISBN(電子版)9781614998334
DOI
出版ステータスPublished - 2018
イベント27th International Conference on Information Modelling and Knowledge Bases, EJC 2017 - Krabi, Thailand
継続期間: 2017 6 52017 6 9

出版物シリーズ

名前Frontiers in Artificial Intelligence and Applications
301
ISSN(印刷版)0922-6389

Conference

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

ASJC Scopus subject areas

  • 人工知能

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