Forest Extraction on Semimountainous Rural Area with a Combination of Full Polarimetric SAR Image and LiDAR Data

Yumi Miura, Chinatsu Yonezawa

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

Abstract

We investigate the capability of forest extraction method combining full polarimetric L-band SAR imagery with LiDAR data. The analyzed data are an ALOS2-PALSAR2 image and airborne LiDAR data observed over Osaki city in Japan. In this study, three different types of extraction methods based on an object-oriented classification are compared using a SPOT6 image, the volume scattering component of the PALSAR2 image, and the integrated classification of a volume scattering component of PALSAR2 image and LiDAR data. The accuracy of each method is assessed using the confusion matrix. The results show that method by the integration of volume scattering component image and LiDAR data has a potential to extract forest with high accuracy compared to other two methods.

Original languageEnglish
Title of host publication2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6736-6739
Number of pages4
ISBN (Electronic)9781538691540
DOIs
Publication statusPublished - 2019 Jul
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 2019 Jul 282019 Aug 2

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Country/TerritoryJapan
CityYokohama
Period19/7/2819/8/2

Keywords

  • forestry
  • light detection and ranging (LiDAR)
  • radar scattering
  • synthetic aperture radar (SAR)

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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