Case studies of automatic change detection using AVNIR-2 onboard alos

Shutaro Hashimoto*, Masahiko Onosato, Takeo Tadono, Masahiro Hori, Takashi Moriyama

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper suggests a new automatic change detection approach using image-object-based contextual inference. The approach first detects changed areas, and then infers what happened there. The inference process uses knowledge based on a change detection process performed by humans. It enables flexible and intuitive description of the change detection process. In this paper, we describe the results of case studies on automatic change detection using the Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2) onboard the Advanced Land Observing Satellite (ALOS, nicknamed "Daichi").

Original languageEnglish
Title of host publication2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3644-3647
Number of pages4
ISBN (Print)9781424495658, 9781424495665
DOIs
StatePublished - 2010
Event2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 - Honolulu, United States
Duration: 2010/07/252010/07/30

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Country/TerritoryUnited States
CityHonolulu
Period2010/07/252010/07/30

Keywords

  • Artificial intelligence
  • Object-oriented methods
  • Production systems
  • Remote sensing

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences

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