Dr. Tomohisa Konishi Profile

Dr. Tomohisa Konishi

Associate Professor at Hiroshima Institute of Technology

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Publications (12)

Proceedings Article | 12 September 2021 Poster + Paper

Landslide extraction with COSMO-SkyMed imageries using U-Net

Tomohisa Konishi, Seiji Ito, Yoshinari Oguro

Proceedings Volume 11861, 118610H (2021) https://doi.org/10.1117/12.2598144

KEYWORDS: Landslide (networking), Synthetic aperture radar, Earthquakes, Feature extraction, Data modeling, Calibration, X band, Visualization

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Proceedings Article | 8 October 2019 Paper

Landslide detection with ALOS-2/PALSAR-2 data using convolutional neural networks: a case study of 2018 Hokkaido Eastern Iburi earthquake

Tomohisa Konishi, Yuzo Suga

Proceedings Volume 11154, 111540H (2019) https://doi.org/10.1117/12.2531695

KEYWORDS: Landslide (networking), Synthetic aperture radar, Earthquakes, Convolutional neural networks, Image segmentation, Calibration, Backscatter, Remote sensing, Satellites

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Proceedings Article | 3 October 2019 Paper

Development of snowplow operation support system using GNSS and QZSS

Yuzo Suga, Tomohisa Konishi, Nobuyuki Fujii

Proceedings Volume 11156, 111561P (2019) https://doi.org/10.1117/12.2533135

KEYWORDS: Satellite navigation systems, Roads, Kinematics, Satellites, Data conversion, Control systems, 3D metrology, Navigation systems

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Proceedings Article | 9 October 2018 Paper

Landslide detection using polarimetric ALOS-2/PALSAR-2 data: a case study of 2016 Kumamoto earthquake in Japan

Tomohisa Konishi, Yuzo Suga

Proceedings Volume 10788, 107880P (2018) https://doi.org/10.1117/12.2324030

KEYWORDS: Landslide (networking), Polarimetry, Synthetic aperture radar, Earthquakes, Polarization, Earth observing sensors, Satellites

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Proceedings Article | 3 October 2017 Paper

Building damage mapping of 2016 Kumamoto, Japan, earthquake using ALOS-2/PALSAR-2 interferometric coherence

Tomohisa Konishi, Yuzo Suga

Proceedings Volume 10426, 104260F (2017) https://doi.org/10.1117/12.2277832

KEYWORDS: Interferometry, Synthetic aperture radar, Buildings, Earthquakes, Coherence (optics), Neodymium, L band, Meteorology, Natural disasters, Surgery

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Proceedings Article | 3 October 2017 Paper

Extraction of damaged area caused by debris flows in Hiroshima using COSMO-SkyMed images

Tomohisa Konishi, Yuzo Suga

Proceedings Volume 10426, 1042604 (2017) https://doi.org/10.1117/12.2277679

KEYWORDS: Interferometry, Synthetic aperture radar, Neodymium, Image resolution, Coherence (optics), Meteorology, Satellites, Natural disasters, Remote sensing, Optical resolution

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Proceedings Article | 21 November 2012 Paper

Landslide detection using very high-resolution satellite imageries

Yuzo Suga, Tomohisa Konishi

Proceedings Volume 8524, 852428 (2012) https://doi.org/10.1117/12.976033

KEYWORDS: Landslide (networking), Synthetic aperture radar, Satellites, Earth observing sensors, 3D image processing, 3D vision, Satellite imaging, Data modeling, Image resolution, Backscatter

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Proceedings Article | 2 October 2008 Paper

Rice crop monitoring using X, C and L band SAR data

Yuzo Suga, Tomohisa Konishi

Proceedings Volume 7104, 710410 (2008) https://doi.org/10.1117/12.800051

KEYWORDS: Synthetic aperture radar, Backscatter, Polarization, L band, Spatial resolution, Satellites, Vegetation, Photography, X band, Agriculture

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SPIE Journal Paper | 1 August 2008

Monitoring rice-crop growth with ENVISAT-1/ASAR alternating polarization mode

Tomohisa Konishi, Yuzo Suga, Sigeru Omatu, Shoji Takeuchi, Kazuyoshi Asonuma

JARS, Vol. 2, Issue 01, 023535, (August 2008) https://doi.org/10.1117/12.10.1117/1.2977791

KEYWORDS: Backscatter, Polarization, Synthetic aperture radar, Statistical analysis, Vegetation, Radar, Data acquisition, Earth observing sensors, Satellites, Image processing

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Proceedings Article | 29 October 2007 Paper

Comparison of the performances of middle-resolution multi-spectral images for vegetation cover rate extraction based on mixture analyses

Yuzo Suga, Tomohisa Konishi, Shoji Takeuchi

Proceedings Volume 6749, 67491R (2007) https://doi.org/10.1117/12.736607

KEYWORDS: Vegetation, Image resolution, Earth observing sensors, Satellites, Statistical analysis, Data modeling, Short wave infrared radiation, Image analysis, Sensors, Landsat

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This study aims to establish a practical image analysis method for the use of middle-scale resolution images acquired by the multi-spectral sensors such as Landsat-7/ETM+, Terra/ASTER and ALOS/AVNIR-2 as the complementary data sources of higher resolution images such as Quickbird for the purpose of environmental monitoring of wide-range areas. For this purpose, an image analysis based on mixture is investigated as one of the effective approaches. As the information target, we selected vegetation cover rate (VCR) in urban area because it is one of the important environmental factors to affect urban environment issue such as heat island phenomena. In order to realize easy and efficient computation for estimating the mixture rate of vegetation categories, the linear mixture model using two main categories including vegetation and non-vegetation, is applied in combination with the least square estimation of multi-regressive coefficients for vegetation cover rate (VCR) and non-vegetation cover rate (non-VCR) with several bands data by multi-spectral sensors. In addition, two sub-categories for both of vegetation and non-vegetation categories are considered to specify representative pixel values as correct as possible, that is, trees and grasses for vegetation, and buildings and bare-soils for non-vegetation respectively, and their optical mixture rates are estimated as well as the mixture rate of vegetation and non-vegetation categories. For this purpose, an iterative procedure is adopted, in which each mixture rate of two sub-categories for vegetation and non-vegetation is varied by ten percent steps and the least square estimation is applied with all combinations of mixture rates of sub-categories for vegetation and non-vegetation. The experiments for VCR extraction were conducted in the test site of Hiroshima-city and by using multi-spectral data acquired by Landsat-7/ETM+, Terra/ASTER, and ALOS/AVNIR-2. The accuracy for VCR extraction was evaluated based on the comparison with the VCRs obtained by means of pixel-wise vegetation/non-vegetation classification of a Quickbird multi-spectral image. The result shows that the number of bands is one of the important parameters in general. However, it was verified that the combination of wavelength regions is more important than the number of bands. The result of this study suggests that the combination of wavelength regions is essential in middle-resolution multi-spectral images for vegetation cover rate estimation based on mixture analyses.

Proceedings Article | 29 October 2007 Paper

Rice crop growth monitoring using ENVISAT-1/ASAR AP mode

Tomohisa Konishi, Yuzo Suga, Shigeru Omatu, Shoji Takeuchi, Kazuyoshi Asonuma

Proceedings Volume 6749, 674920 (2007) https://doi.org/10.1117/12.737255

KEYWORDS: Backscatter, Polarization, Synthetic aperture radar, Vegetation, Data acquisition, Earth observing sensors, Radar, Microwave radiation, Satellites, Image processing

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Proceedings Article | 3 October 2006 Paper

Extraction of vegetation cover rate in urban areas based on mixel analyses of Landsat data

Shoji Takeuchi, Tomohisa Konishi

Proceedings Volume 6366, 63660N (2006) https://doi.org/10.1117/12.684369

KEYWORDS: Vegetation, Landsat, Data acquisition, Image resolution, Data modeling, Earth observing sensors, Satellites, Satellite imaging, Photography, Statistical analysis

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Showing 5 of 12 publications

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