研究者詳細 - 西山　哲

論文 - 西山　哲

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Interchangeability of Cross-Platform Orthophotographic and LiDAR Data in DeepLabV3+-Based Land Cover Classification Method 査読

Shijun Pan, Keisuke Yoshida, Satoshi Nishiyama, Takashi Kojima, Yutaro Hashimoto

Land 14 ( 2 ) 217 - 217 2025年1月

掲載種別：研究論文（学術雑誌）出版者・発行元：MDPI AG

Riverine environmental information includes important data to collect, and the data collection still requires personnel’s field surveys. These on-site tasks still face significant limitations (i.e., hard or danger to entry). In recent years, as one of the efficient approaches for data collection, air-vehicle-based Light Detection and Ranging technologies have already been applied in global environmental research, i.e., land cover classification (LCC) or environmental monitoring. For this study, the authors specifically focused on seven types of LCC (i.e., bamboo, tree, grass, bare ground, water, road, and clutter) that can be parameterized for flood simulation. A validated airborne LiDAR bathymetry system (ALB) and a UAV-borne green LiDAR System (GLS) were applied in this study for cross-platform analysis of LCC. Furthermore, LiDAR data were visualized using high-contrast color scales to improve the accuracy of land cover classification methods through image fusion techniques. If high-resolution aerial imagery is available, then it must be downscaled to match the resolution of low-resolution point clouds. Cross-platform data interchangeability was assessed by comparing the interchangeability, which measures the absolute difference in overall accuracy (OA) or macro-F1 by comparing the cross-platform interchangeability. It is noteworthy that relying solely on aerial photographs is inadequate for achieving precise labeling, particularly under limited sunlight conditions that can lead to misclassification. In such cases, LiDAR plays a crucial role in facilitating target recognition. All the approaches (i.e., low-resolution digital imagery, LiDAR-derived imagery and image fusion) present results of over 0.65 OA and of around 0.6 macro-F1. The authors found that the vegetation (bamboo, tree, grass) and road species have comparatively better performance compared with clutter and bare ground species. Given the stated conditions, differences in the species derived from different years (ALB from year 2017 and GLS from year 2020) are the main reason. Because the identification of clutter species includes all the items except for the relative species in this research, RGB-based features of the clutter species cannot be substituted easily because of the 3-year gap compared with other species. Derived from on-site reconstruction, the bare ground species also has a further color change between ALB and GLS that leads to decreased interchangeability. In the case of individual species, without considering seasons and platforms, image fusion can classify bamboo and trees with higher F1 scores compared to low-resolution digital imagery and LiDAR-derived imagery, which has especially proved the cross-platform interchangeability in the high vegetation types. In recent years, high-resolution photography (UAV), high-precision LiDAR measurement (ALB, GLS), and satellite imagery have been used. LiDAR measurement equipment is expensive, and measurement opportunities are limited. Based on this, it would be desirable if ALB and GLS could be continuously classified by Artificial Intelligence, and in this study, the authors investigated such data interchangeability. A unique and crucial aspect of this study is exploring the interchangeability of land cover classification models across different LiDAR platforms.

DOI： 10.3390/land14020217

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APPLICATION OF IMAGE GENERATION AI IN MODEL FOR DETECTING PLASTIC BOTTLES DURING RIVER PATROL USING UAV

Daichi SHIMOE, Shijun PAN, Keisuke YOSHIDA, Satoshi NISHIYAMA, Takashi KOJIMA

Japanese Journal of JSCE 81 ( 16 ) n/a - n/a 2025年

長時間航行ドローンの開発と3次元グリーンレーザ計測技術の研究査読

佐野ひかる, 西山哲, 冨井隆春, 間野耕司

土木学会 AI・データサイエンス論文集 5 ( 3 ) 697 - 705 2024年11月

UAVを利用した浚渫土砂処分場のモニタリング技術の実用化査読

照屋市朗, 西山哲

土木学会論文集 80 ( 18 ) 24-18101 2024年10月

Generating 3D Models for UAV-Based Detection of Riparian PET Plastic Bottle Waste: Integrating Local Social Media and InstantMesh 査読

Shijun Pan, Keisuke Yoshida, Daichi Shimoe, Takashi Kojima, Satoshi Nishiyama

Drones 8 ( 9 ) 471 - 471 2024年9月

掲載種別：研究論文（学術雑誌）出版者・発行元：MDPI AG

In recent years, waste pollution has become a severe threat to riparian environments worldwide. Along with the advancement of deep learning (DL) algorithms (i.e., object detection models), related techniques have become useful for practical applications. This work attempts to develop a data generation approach to generate datasets for small target recognition, especially for recognition in remote sensing images. A relevant point is that similarity between data used for model training and data used for testing is crucially important for object detection model performance. Therefore, obtaining training data with high similarity to the monitored objects is a key objective of this study. Currently, Artificial Intelligence Generated Content (AIGC), such as single target objects generated by Luma AI, is a promising data source for DL-based object detection models. However, most of the training data supporting the generated results are not from Japan. Consequently, the generated data are less similar to monitored objects in Japan, having, for example, different label colors, shapes, and designs. For this study, the authors developed a data generation approach by combining social media (Clean-Up Okayama) and single-image-based 3D model generation algorithms (e.g., InstantMesh) to provide a reliable reference for future generations of localized data. The trained YOLOv8 model in this research, obtained from the S2PS (Similar to Practical Situation) AIGC dataset, produced encouraging results (high F1 scores, approximately 0.9) in scenario-controlled UAV-based riparian PET bottle waste identification tasks. The results of this study show the potential of AIGC to supplement or replace real-world data collection and reduce the on-site work load.

DOI： 10.3390/drones8090471

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Unveiling Deep-Seated Gravitational Slope Deformations via Aerial Photo Interpretation and Statistical Analysis in an Accretionary Complex in Japan 査読

Teruyuki Kikuchi, Satoshi Nishiyama, Teruyoshi Hatano

SUSTAINABILITY 16 ( 13 ) 2024年7月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：MDPI

The objective of this study was to identify the locations of deep-seated gravitational slope deformations (DGSDs) and define the numerical characteristics of these deformations to contribute to the sustainable management of social infrastructure in the event of an increased disaster. The topographic features of the DGSDs were quantitatively characterized based on their surface morphologies. Topographic features indicative of gravitational deformation in pre-slide topographic maps, such as terminal cliff failures, irregular undulations, and gullies, suggest that progressive deformation occurred over a prolonged period. To track the gravitational deformation over time, we interpreted aerial photographs of DGSDs from 1948 and 2012 associated with deep-seated landslides on the Kii Peninsula induced by Typhoon Talas on 2-5 August 2011. Corresponding numerical analysis of the gravitational deformations using 1 m digital elevation models reveals that landslide areas exhibit eight characteristic influencing factors, demonstrating that characteristic morphologies exist in areas that eventually experience landslides. One such morphological feature is the existence of a gently sloping area in the upper section of the deep-seated landslide mass, which comprises a catchment basin without a corresponding valley or gully. These findings suggest that rainwater penetrates the ground, and degrades and deforms the rock within the landslide mass, causing the slope to fail after torrential rainfall. This study holds great significance for advancing sustainable infrastructure development and management and mitigating environmental changes.

DOI： 10.3390/su16135328

Web of Science

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河川災害地調査および災害復旧支援のためのドローン測量技術の構築査読

富田紀子, 西山哲, 間野耕司

土木学会 AI・データサイエンス論文集 5 ( 1 ) 230 - 238 2024年5月

落石発生源抽出に適したウェーブレット解析条件と可視化方法に関する検討査読

中村公一, 今西将文, 西山哲

地盤工学ジャーナル 19 ( 1 ) 69 - 77 2024年3月

記述言語：日本語出版者・発行元：公益社団法人地盤工学会

微地形表現図を航空レーザ（LP）測量データより作成する方法のひとつとして，ウェーブレット解析図がある。本検討では，落石発生源となる地物（露岩・転石・小崖）の抽出を目的とし，ウェーブレット解析条件であるスケールファクター（s）の設定と，ウェーブレット係数の可視化方法について検討を行った。検討には航測 LP データより作成したグリッドサイズ 0.5m のグリッドデータと踏査結果を用いた。地物の比高差1.0m～3.0m と正のウェーブレット係数には相関関係があることがわかった。この結果と模擬地形に対する検討結果を用いて，ウェーブレット係数の可視化方法を提案した。s =1.0 とs =0.5 とした検討を行い，落石発生源となる地物の抽出にs =0.5 が有用であることを示した。

DOI： 10.3208/jgs.19.69

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地物の大きさとウェーブレット係数の関係に関する検討査読

中村公一, 今西将文, 西山哲

土木学会論文集 80 ( 2 ) ID: 23-00046 2024年2月

航空レーザ計測と洪水解析による植生抗力の３次元分布推定と竹林倒伏・木本流失の再現計算査読

古谷崚, 吉田圭介, 岡田拓巳, 梶川勇樹, 西山哲

80 ( 16 ) ID: 23-16161 2024年

Detection of Deep-Seated Gravitational Slope Deformations by Aerial Photo Interpretation and Statistical Analysis in an Accretionary Complex in Japan 査読

Teruyuki Kikuchi, Satoshi Nishiyama

ENGINEERING GEOLOGY FOR A HABITABLE EARTH, VOL 2, IAEG XIV CONGRESS 2023 263 - 278 2024年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：SPRINGER-VERLAG SINGAPORE PTE LTD

The objective of this study was to identify the locations of deep-seated gravitational slope deformations (DGSDs), which are precursors of future deep-seated landslides, and to characterize the numerical characteristics of these deformations in order to theoretically elucidate observed phenomena. To this end, we attempted to characterize quantitatively the topographic features of DGSDs, focusing on surface morphology. Signs of gravitational deformation that are frequently observed in pre-slide topographic maps include terminal cliff failures, irregular undulations, and gullies. The presence of these topographic features suggest that progressive deformation has occurred over a prolonged period of time. In order to track gravitational deformation over time, in this study, we interpreted aerial photographs of DGSDs that were associated with deep-seated landslides (DLs) on the Kii Peninsula that had been induced by Typhoon Talas, which occurred from 2 to 5 August 2011. We were able to observe the deformations that are considered to be caused by gravitational deformation over time. Numerical analysis using 1-m digital elevation models (DEM) revealed that the landslide areas exhibited characteristic eigenvalue ratios, slope angles, topographic wetness indices, and underground openness, demonstrating that characteristic morphologies exist in the areas that eventually experience landslides. One such morphological feature is the existence of a gentle sloping area in the upper section of the mass comprising a catchment basin, but without the corresponding valley and gully. The findings suggest that rainwater penetrates into the ground, degrading and deforming the rock within the landslide mass, and ultimately causes the slope to fail after torrential rainfall.

DOI： 10.1007/978-981-99-9061-0_20

Web of Science

Scopus

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Mutual validation of remote hydraulic estimates and flow model simulations using UAV-borne LiDAR and deep learning-based imaging techniques 査読

Md Touhidul Islam, Keisuke Yoshida, Satoshi Nishiyama, Koichi Sakai

Results in Engineering 20 101415 2023年12月

Detection and Segmentation of Riparian Asphalt Paved Cracks Using Drone and Computer Vision Algorithms 査読

Shijun PAN, Keisuke YOSHIDA, Satoshi NISHIYAMA

Intelligence, Informatics and Infrastructure 4 ( 2 ) 35 - 49 2023年11月

STUDY OF A METHOD FOR EXTRACTING SMALL-SCALE TOPOGRAPHIC IRREGULARITIES USING WAVELET ANALYSIS MAPS 査読

Masafumi Imanishi, Koichi Nakamura, Satoshi Nishiyama

International Journal of GEOMATE 25 ( 110 ) 148 - 158 2023年9月

破堤における復旧作業へのUAVグリーンレーザ計測の適用査読

井関禎之, 間野耕司, 堺浩一, 西山哲

応用測量論文集 34 67 - 78 2023年8月

Landslide susceptibility mapping using automatically constructed CNN architectures with pre-slide topographic DEM of deep-seated catastrophic landslides caused by Typhoon Talas 査読

Teruyuki Kikuchi, Koki Sakita, Satoshi Nishiyama, Kenichi Takahashi

Natural Hazards 117 339 - 364 2023年5月

掲載種別：研究論文（学術雑誌）

There has been an increasing demand for detailed and accurate landslide maps and inventories in disaster-prone areas of subtropical and temperate zones, particularly in Asia as they can mitigate the impacts of landslides on social infrastructure and economic losses. Hence, in this study, models using automatically constructed high-performing convolutional neural network (CNN) architectures for landslide detection were applied and their outcomes were compared for landslide susceptibility mapping at the Kii peninsula, Japan. First, a total of 38 landslide and 63 non-landslide points were identified and divided into 70% and 30% of training and validation datasets, respectively. Eight landslide influence factors were used: slope angle, eigenvalue ratio, curvature, underground openness, overground openness, topographic witness index, wavelet, and elevation. These factors were selected using a 1-m DEM, which is easy to acquire and process data. Experimental results of model evaluation using receiver operating characteristics (ROC), area under the curve (AUC), and accuracy showed that the optimal models (ROC = 96.0%, accuracy = 88.7%) were more accurate than initial models (ROC = 91.1%, accuracy = 80.7%) in predicting landslides spatially. Furthermore, the landslide susceptibility mapping is consistent with the trends in the distribution of gentle slopes and knick lines unique to the study area and can be used as a powerful method for predicting landslides in future.

DOI： 10.1007/s11069-023-05862-w

Scopus

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Application of three-dimensional laser point cloud technology to river management 査読

Nanoka Akiyama, Satoshi Nishiyama, Junsheng Song

Rock Dynamics: Progress and Prospect 2 235 - 239 2023年5月

Three-dimensional monitoring of slope deformation using digital photogrammetry 査読

A. Boney, S. Nishiyama, T. Kikuchi

Rock Dynamics: Progress and Prospect, Volume 2 412 - 417 2023年5月

Automatic extraction of rockfall source based on terrain analysis map using support vector machine 査読

Naoko Sakamoto, Koki Sakita, Satoshi Nishiyama, Teruyuki Kikuchi, Junsheng Song, Yuzo Ohnishi

Rock Dynamics: Progress and Prospect, Volume 2 240 - 245 2023年5月

Chapter Consideration of countermeasures using rockfall simulation by discontinuous deformation analysis 査読

Hiroaki Kitauchi, Satoshi Nishiyama, Junsheng Song

Rock Dynamics: Progress and Prospect, Volume 2 252 - 257 2023年5月

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