Journal of The Remote Sensing Society of Japan
Online ISSN : 1883-1184
Print ISSN : 0289-7911
ISSN-L : 0289-7911
Current issue
Displaying 1-13 of 13 articles from this issue
Special Issue on Remote Sensing of Volcanic Activity: Preface
Special Issue on Remote Sensing of Volcanic Activity: Case Examination
  • Shoichiro Kojima
    2024 Volume 44 Issue 1 Pages 2-8
    Published: March 19, 2024
    Released on J-STAGE: April 13, 2024

    In order to facilitate smooth and effective evacuation and rescue operations in the event of a volcanic disaster, NICT has been researching observation and analysis methods for volcanoes using Pi-SAR X3, which has advanced performance and functions. In this report, we present the results of our study on the advantages and disadvantages of volcano observation by Pi- SAR X3 using three images data obtained from observations of Mt. Fuji, Mt. Asama, and Mt. Kusatsu-Shirane. In addition, this report presents the results of our study on the observation and analysis methods necessary to use Pi-SAR X3 data for evacuation and rescue in volcanic disasters.

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  • Tetsuya Jitsufuchi
    2024 Volume 44 Issue 1 Pages 9-20
    Published: March 19, 2024
    Released on J-STAGE: April 13, 2024

    The National Research Institute for Earth Science and Disaster Resilience (NIED) has been developing and operating airborne optical sensors for volcano observation since the 1980s. Four such devices have been developed. The first three instruments, developed between 1990 and 2015, were spectral imaging scanners mounted on special fixed-wing aircraft to observe the nadir. These sensors allowed the acquisition of temperature distributions, gas concentration distributions, spectral information, and the topography of the volcano. A fourth instrument was developed in 2020. This portable device does not require a dedicated aircraft, and allows oblique observation of volcanoes from the air outside the area covered by the eruption alert level. We present an overview of these devices and their performance in this paper.

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  • Haruma Ishida, Kozo Okamoto, Yoshifumi Ota
    2024 Volume 44 Issue 1 Pages 21-32
    Published: March 19, 2024
    Released on J-STAGE: April 13, 2024
    Advance online publication: December 12, 2023

    Recent studies on the application of principal component analysis (PCA) to infrared hyperspectral sounder (HSS) data are reviewed in order to promote the utilization of infrared HSS data in remote sensing of the atmosphere and data assimilation for numerical weather forecasting. Infrared HSS sensors are contained in some earth observational and geostationary/polar-orbiting meteorological satellites, primarily to observe the vertical profile of the atmospheric temperature and water vapor content. Because of the large number of channels, the volume of HSS data is enormous and is expected to increase, however, this volume makes data transfer and processing difficult. Data compression techniques, including PCA, are expected to be an effective in reducing the volume of HSS data while maintaining as much observation information as possible. Near real-time spectral data of some HSSs are or will be disseminated in the format of principal component scores (PCS). This article summarizes research examples of the usage of PCA for infrared HSS data and examines the issues involved in developing schemes for it.

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Engineering Report
  • Hiroki Murata, Hiroki Sato, Chinatsu Yonezawa
    2024 Volume 44 Issue 1 Pages 33-40
    Published: March 19, 2024
    Released on J-STAGE: April 13, 2024
    Advance online publication: December 26, 2023

    Seagrass and seaweed beds, tidal flats, and biosymbiotic port structures are considered blue infrastructure, and the Japanese government is promoting their development. On the other hand, existing port structures could also function as blue infrastructure as a result of their construction. Remote sensing is used for blue infrastructure surveys. In recent years, with drones becoming commercially available at relatively affordable prices, they are being introduced into field surveys. While drones have the advantage of high-resolution aerial imaging, they have the drawback of limited coverage. To compensate for this, orthomosaic synthesis using structure from motion (SfM) image processing technology is effective. In this study, we created ground truth data from the orthomosaic image and applied for satellite image analysis to examine a wider area than that of the drone survey. As a result of the supervised classification of the satellite Planet SuperDove image, the overall accuracy was 90.7%. Ground truth data is generally acquired by field surveys using underwater cameras or diving from a ship, but there is a limit to the amount of data that can be acquired in a single survey due to cost and time constraints. Application of drones can acquire more ground truth data in a shorter time and lower cost, and perform image classification with the same accuracy as field surveys. On the other hand, remote sensing surveys have their limitations. To obtain more detailed information such as identification of habitat species and estimation of prevalence, it is necessary to deploy underwater cameras, drones, diving surveys, etc., from a ship. In future, we expect citizen science involving local groups and citizens, including diving shops and fishermen, will take the lead in blue infrastructure surveys in various regions of Japan.

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Laboratory Introduction
Q&A in Remote Sensing