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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