A cause-based methodology for semantic analysis of deforestation using multispectral reflectance

Irene Erlyn Wina Rachmawan, Yasushi Kiyoki, Shiori Sasaki

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

1 Citation (Scopus)

Abstract

Nowadays, deforestation activity still occurs despite having huge impact for human being. The different causes of deforestation are relatively brings different effect on nature, while forest fire and illegal logging are two major deforestation activities. In this paper, we proposed a new method to represent semantic analysis of deforestation effect based on its cause. We proposed idea to interpret reflected 'substances (material)' of deforestation area in spectrum domain into human language. The objectives of this paper are to (1) Detect deforestation area, (2) Detect the type activity that cause deforestation (whether it is logging or forest fire), (3) measuring the degree of deforestation effect for soil by considering the soil properties, (4) identify and present important nature changes occurring in soils that affect post deforestation management. Riau has been selected as the study area, where the data was acquired by using Landsat Satellite images between 2013 and 2014; where there is a big forest fire occurs. The experimental result produces new semantic analysis matrices to determining the soil condition after deforestation in different context.

Original languageEnglish
Title of host publication2016 International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages134-140
Number of pages7
ISBN (Electronic)9781509052318
DOIs
Publication statusPublished - 2017 Mar 20
Event5th International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016 - Manado, Indonesia
Duration: 2016 Nov 152016 Nov 17

Other

Other5th International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016
CountryIndonesia
CityManado
Period16/11/1516/11/17

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Keywords

  • deforestation
  • landsat
  • reflectance
  • semantic analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

Cite this

Rachmawan, I. E. W., Kiyoki, Y., & Sasaki, S. (2017). A cause-based methodology for semantic analysis of deforestation using multispectral reflectance. In 2016 International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016 (pp. 134-140). [7883637] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/KCIC.2016.7883637