Journal of the Japan society of photogrammetry and remote sensing
Online ISSN : 1883-9061
Print ISSN : 0285-5844
ISSN-L : 0285-5844
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Volume 54, Issue 4
Displaying 1-10 of 10 articles from this issue
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  • The application of Mobile Mapping System to river embankment measurement
    Kikuo TACHIBANA, Koji MANO, Hideki SHIMAMURA, Satoshi NISHIYAMA
    2015 Volume 54 Issue 4 Pages 166-177
    Published: 2015
    Released on J-STAGE: September 01, 2016
    DOIhttps://doi.org/10.4287/jsprs.54.166
    JOURNAL FREE ACCESS
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    Recently Mobile Mapping System (MMS) is used for variety applications such as three-dimensional road facility mapping, road maintenance and disaster risk management. The application of MMS to maintenance and management of river embankments has also been studied so far. The three-dimensional coordinates of the laser point cloud data obtained from MMS are calculated based on the position and orientation of MMS that are measured by GNSS, IMU and odometer. Analysis of the position of MMS is carried out by RTK method or networked RTK method such as FKP (Flächen Korrektur Parameter) method and VRS (Virtual Reference Station) method. In the GNSS analysis, longer base line decreased accuracy due to ionospheric and tropospheric delay. In this study, we verified the difference of positioning accuracy depending on the GNSS analysis method and considered the optimal measurement conditions to apply MMS to monitoring the river embankment. In addition, based on the three-dimensional laser point cloud, we investigated the accuracy of the height of the embankment crest and the profile of the river embankment by using our proposed methods. In this paper, we demonstrate the required measurement conditions and the effective data processing for the river embankment measurement by MMS.
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  • The development of stand volume estimation model using airborne LiDAR for Hinoki (Chamaecyparis obutsusa) and Sugi (Cryptomeria japonica)
    Kiyoshi TAKEJIMA
    2015 Volume 54 Issue 4 Pages 178-188
    Published: 2015
    Released on J-STAGE: September 01, 2016
    DOIhttps://doi.org/10.4287/jsprs.54.178
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    I developed a model to estimate stand volumes using LiDAR data. Stand volumes (v) are often estimated by linear regression model using spatial volume (V), v＝aV or v＝aV＋b, where a and b as constant. This method is easy to apply, but its accuracy is known to be low. Belief of taking “a” as constant may worth for reconsideration. The concept of “Stock Ratio (s)” -defined as s＝v/V is newly proposed in this study. I focused on five representative stand characters-species, diameter of breath height, slope, height to diameter ratio and Hart-Becking index and examined the relation between these factors and Stock Ratio using 6,000 trees data obtained in field measurements. The results strongly suggested that species and Hart-Becking index have an apparent relation with Stock Ratio. Hence, it is clear that Stock Ratio will differ among species and Hart-Becking index. The relation can be modeled as s＝Bse(－As×Sr) where Sr is Hart-Becking index and, As and Bs are the constant by species. Introducing the estimation of Stock Ratio with above two factors which is proposed in this study will improve the accuracy of the estimation for the stand volume (i.e. v＝sV＝Bse(－As×Sr)V) than conventional methods.
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  • Examination of Comparative Advantage of ALOS World 3D Topographic Data for the Analysis of Locational Condition of Agriculture
    Satoshi UCHIDA
    2015 Volume 54 Issue 4 Pages 189-193
    Published: 2015
    Released on J-STAGE: September 01, 2016
    DOIhttps://doi.org/10.4287/jsprs.54.189
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    We examined the newly published high spatial resolution digital elevation data, ALOS 3D World Topographic Data (AW3D), for application of the analysis of locational condition of agriculture mainly compared with ASTER Global Digital Elevation Model (GDEM). The study site was selected in the middle part of Burkina Faso, where topographic condition was consisted of gentle slopes even around watershed boundaries and bottom of valleys. Examination was focused on sloping features and river/watershed systems as comparing elevation profile along transect line measured by handy GPS. As a result, GDEM contained random deviations with amplitude of several meters, which might induce apparent high degree of slopes. On the other hand, AW3D was proved to fit optimally with profile of GPS measured data and did not show large deviation as appeared in GDEM profile. River course and watershed boundary obtained from AW3D and GDEM were not identical and GDEM might produce unrealistic river course in close up scale map. However in regional scale, both AW3D and GDEM produced river course and watershed boundary with similar morphological pattern.
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  • Ground Point Extraction from Airborn Laser Scanner Data by Using Bilateral Down/Top Envelope Filters
    Toru HIRAOKA, Atsushi RIKIMARU
    2015 Volume 54 Issue 4 Pages 194-198
    Published: 2015
    Released on J-STAGE: September 01, 2016
    DOIhttps://doi.org/10.4287/jsprs.54.194
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    We propose a ground point extraction method from airborn laser scanner data by using bilateral down/top envelope filters. Our method can improve the accuracy and calculation time than a conventional method (hiraoka et al., 2014). Through experiments which is used airborn laser scanner data of area with inclination, slope, buildings, and plants, we verify the effectiveness of oure method. Finally we comment on the respects in which our method is improved and on future prospects.
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  • Evaluation of Speckle Noise Reduction of TerraSAR Intensity Imagery
    Lin ZHU, Yi ZHAO, Kan-ichiro MOCHIZUKI
    2015 Volume 54 Issue 4 Pages 199-205
    Published: 2015
    Released on J-STAGE: September 01, 2016
    DOIhttps://doi.org/10.4287/jsprs.54.199
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    In this study, the effect of speckle noise reduction was evaluated with high resolution satellite TerraSAR intensity data. Multi-temporal polarization imagery (HH & VV) was acquired on different growth stages of rice plant. Three kinds of filters, i.e. Lee, Frost, Gamma Map, were applied for speckle noise filtering with different window sizes. Six indices, i.e. Standard deviation, Equivalent number of looks, Speckle suppression index, Edge preservation index, Image sharpness, and Image detail preservation index, were used in order to compare and assess the effect of speckle noise reduction of different filters. Based on the evaluation results, the most appropriate window size was determined for speckle noise filtering of utilized data.
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