衛星和無人機技術進行河川疏濬多時相遙測監管分析

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林莉珊(Li-Shan Lin) 查詢紙本館藏

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土木工程學系

論文名稱

衛星和無人機技術進行河川疏濬多時相遙測監管分析
(River Dredging Oversight through Multi-Temporal Remote Sensing Analysis Using Satellite and UAV Technologies)

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至系統瀏覽論文 (2029-7-30以後開放)

摘要(中)

為避免河道砂石堆積導致水災並影響河川周邊安全，河川疏濬是目前梳理河川的主要方式。然而，河川過度疏濬易影響河川平衡，導致下游砂石補充不足引發災害，因此須對河川疏濬的過程進行監測。近年來，遙測科技的不斷提升，加上可長時間及大範圍的紀錄空間的特性，已有許多研究利用無人機及超高解析度衛星立體對影像產製的數值地表模型(Digital Surface Model, DSM)廣泛使用在不同的地形上。本研究使用法國Airbus公司的Pléiades 1A/1B超高解析度衛星影像產製DSM (〖DSM〗_pla)、無人飛行載具系統(Unmanned Aerial Vehicle, UAV)產製之DSM (〖DSM〗_uav)及地面高程測量所提供之獨立數據，對疏濬過程中的河床變化進行監測。將三組資料進行多時序遙測分析法套合比對，以可靠地偵測主要地形變化。然而，因影像拍攝設備及拍攝條件影響，三維資訊有系統誤差及潛在變形等問題。為此本研究使用DSMs與地面高程測量點擬合三階三維多項式曲面進行全局高程套合，再將點雲以迭代最近點算法(Iterative closest point, ICP)局部套合，減少潛在變形所產生的問題。在三階三維多項式曲面修正後，Pléiades與UAV相對精度為0.7公尺，Pléiades及UAV與主管機關提供的地面檢測，在河道斷面平均高程的相對精度分別為0.47–0.84公尺及0.51-0.76公尺。在局部套合後，顯著補償〖DSM〗_pla 和〖DSM〗_uav 之間的潛在局部變形，進一步提高相對高程精度。遙測方式可提供有效率的面狀地形，彌補地面測量空間密度不足問題並可初步估算疏濬土方，故建議針對各大型疏濬區可辦理遙測方式配合地面測量，而達到實際監測之目的。

摘要(英)

River dredging is essential for preventing flooding by removing excess sediment. However, excessive upstream dredging can cause downstream hazards due to sediment depletion, requiring process monitoring. With the advancement in remote sensing and the capability for monitoring land changes with wide spatiotemporal coverage, many studies have utilized the digital surface model (DSM) derived by Unmanned Aircraft Vehicle (UAV) and the very high resolution (VHR) satellite stereo images for various terrains. This study employs DSMs produced by UAV images (DSM_uav) and Pléiades 1A/1B satellite imagery (DSM_pla) to monitor riverbed changes during dredging. DSM_pla, DSM_uav and field survey data are compared to verify accuracy using multi-temporal remote sensing analysis. Deformations and systematic errors may exist in DSMs due to different acquisition equipment and conditions. Therefore, a 3rd-order 3D polynomial surface is fitted for consistent vertical datum alignment on a global scale using DSMs and the field survey points. Then, the DSMs are converted into point clouds (PC) and the iterative closest point algorithm (ICP) is used for local registration to reduce the problems caused by systematic errors. The accuracy of DSM_pla is improved to 0.7 meters after the 3rd order 3D polynomial surface correction. Further, refinement through local fine alignment of the point clouds significantly reduced minor misalignments between the DSM_pla and the DSM_uav, enhancing the relative elevation accuracy even more. Remote sensing methods can efficiently provide detailed surface terrain data, compensating for insufficient spatial density in ground measurements and enabling initial estimation of excavation volumes. Therefore, it is recommended to combine remote sensing methods with ground surveys in large-scale excavation areas to achieve effective monitoring objectives.

關鍵字(中)

★ 河川疏濬
★ 數值地表模型
★ 點雲套合
★ Pleiades衛星
★ 無人機

關鍵字(英)

★ River Dredging
★ DSM
★ Point Cloud Registration
★ Pleiades Satellite
★ UAV

論文目次

摘要 i
Abstract ii
Table of Contents iv
List of Figures v
Chapter 1 Introduction 1
1.1 River Gravel Mining and Dredging Management 2
1.2 River Dredged Monitoring Method in Taiwan 4
1.3 Satellite Remote Sensing Technique Monitors River Dredging 6
1.4 Multi-Source and Multi-Temporal Analysis and Alignment Issues 8
1.5 Objectives 12
Chapter 2 Study Area and Datasets 14
2.1 Study Area 14
2.2 Pléiades Satellite Materials 17
2.2.1 3D Capabilities of Pléiades Satellite 20
2.2.2 Pléiades Images 23
2.3 UAV Materials 27
2.3.1 Instruments Information 29
2.3.2 UAV Route Planning and Image Shooting 30
2.3.3 Ground Control Points (GCPs) 35
2.3.4 SfM Processing 38
2.3.5 Large-Scale Deformations in UAV Imaging Systems 39
2.4 Field Survey Data 42
Chapter 3 Methodology 44
3.1 Workflow 44
3.2 Least Squares Fitting for 3D Polynomial Surface 47
3.3 Fine Surface Registration of Point Cloud Data 50
3.4 Point Cloud Data Preprocessing 51
3.4.1 CloudCompare Software 51
3.4.2 Denoise 52
3.4.3 Segmentation 54
3.5 Fine Registration of Cross-Source Multi-Temporal DSMs through ICP Optimization Method 57
3.5.1 Initialization 57
3.5.2 Identifying Corresponding Points Between Two Point Clouds: 58
3.5.3 The Calculation of a Transformation Matrix 58
Chapter 4 Results 64
4.1 3D Polynomial Surface Correction 64
4.1.1 Comparative Analysis of DSMs Generated by Pléiades and UAV 64
4.1.2 Comparison of Elevation Measurements: Pléiades, UAV, and Ground Survey 73
4.2 Fine Surface Registration of Point Cloud Data 78
4.2.1 Comparison of Registration Result of Multi-Temporal Surveys 80
4.2.2 Accuracy Assessment after Point Cloud Registration 89
Chapter 5 Discussion 93
5.1 Discussion on Elevation Accuracy 93
5.2 Limitations on mathbit{DSMpla} 96
Chapter 6 Conclusions 99
Chapter 7 Reference 102

參考文獻

Agüera-Vega, F., Carvajal-Ramírez, F., & Martínez-Carricondo, P. (2017). Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry. Journal of Surveying Engineering, 143(2), 04016025.
Almeida, L. P., Almar, R., Bergsma, E. W. J., Berthier, E., Baptista, P., Garel, E., Dada, O. A., & Alves, B. (2019). Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery. Remote Sensing, 11(5), 590. https://doi.org/ARTN 590
10.3390/rs11050590
Arun, K. S., Huang, T. S., & Blostein, S. D. (1987). Least-squares fitting of two 3-d point sets. IEEE Trans Pattern Anal Mach Intell, 9(5), 698-700. https://doi.org/10.1109/tpami.1987.4767965
Bagnardi, M., Gonzalez, P. J., & Hooper, A. (2016). High-resolution digital elevation model from tri-stereo Pleiades-1 satellite imagery for lava flow volume estimates at Fogo Volcano. Geophysical Research Letters, 43(12), 6267-6275. https://doi.org/10.1002/2016gl069457
Beiser, V. (2019). Why the world is running out of sand. BBC Future.
Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9), 509-517.
Berthier, E., Vincent, C., Magnusson, E., Gunnlaugsson, A. T., Pitte, P., Le Meur, E., Masiokas, M., Ruiz, L., Palsson, F., Belart, J. M. C., & Wagnon, P. (2014). Glacier topography and elevation changes derived from Pleiades sub-meter stereo images. Cryosphere, 8(6), 2275-2291. https://doi.org/10.5194/tc-8-2275-2014
Besl, P. J., & McKay, N. D. (1992). Method for registration of 3-D shapes. Sensor fusion IV: control paradigms and data structures,
Bisson, M., Spinetti, C., Andronico, D., Palaseanu-Lovejoy, M., Buongiorno, M. F., Alexandrov, O., & Cecere, T. (2021). Ten years of volcanic activity at Mt Etna: High-resolution mapping and accurate quantification of the morphological changes by Pleiades and Lidar data. International Journal of Applied Earth Observation and Geoinformation, 102, 102369. https://doi.org/ARTN 102369
10.1016/j.jag.2021.102369
Bravard, J.-P., Goichot, M., & Gaillot, S. (2013). Geography of sand and gravel mining in the Lower Mekong River. First survey and impact assessment. EchoGéo(26).
Brunier, G., Anthony, E. J., Goichot, M., Provansal, M., & Dussouillez, P. (2014). Recent morphological changes in the Mekong and Bassac river channels, Mekong delta: The marked impact of river-bed mining and implications for delta destabilisation. Geomorphology, 224, 177-191. https://doi.org/10.1016/j.geomorph.2014.07.009
Bureau of Mine, M. o. E. A., R.O.C.,. (2015-2020). Marketing Report of Sand and Gravel. https://amis.mine.gov.tw/chain/stati
Çelik, M. Ö., Alptekin, A., Ünel, F. B., Kuşak, L., & Kanun, E. (2020). The effect of different flight heights on generated digital products: DSM and Orthophoto. Mersin Photogrammetry Journal, 2(1), 1-9.
Central Geological Survey, M. (2000). 1:50000 Geologic Map of Taiwan in 2000. https://gis3.moeacgs.gov.tw/gsb108-1/list_service.cfm
Chen, C. T. A., Liu, J. T., & Tsuang, B. J. (2004). Island-based catchment-The Taiwan example. Regional Environmental Change, 4(1), 39-48. https://doi.org/10.1007/s10113-003-0058-3
Chen, H., & Hawkins, A. B. (2009). Relationship between earthquake disturbance, tropical rainstorms and debris movement: an overview from Taiwan. Bulletin of Engineering Geology and the Environment, 68(2), 161-186. https://doi.org/10.1007/s10064-009-0209-y
Coeurdevey, L., & Fernandez, K. (2012). Defence and space intelligence pléiades imagery user guide. Available at: https://www.intelligence-airbusds.com/automne/api/docs/v1.0/document/download/ZG9jdXRoZXF1ZS1kb2N1bWVudC01NTY0Mw==/ZG9jdXRoZXF1ZS1maWxlLTU1NjQy/airbus-pleiades-imagery-user-guide-15042021.pdf.
Coeurdevey, L., & Fernandez, K. (2012). Pléiades Imagery—User Guide. Airbus Defense and Space Intelligence, France CNES, Tech. Rep. Report No. USRPHR-DT-125-SPOT-2.0.
Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of photogrammetry and remote sensing, 92, 79-97. https://doi.org/10.1016/j.isprsjprs.2014.02.013
Croke, J., Todd, P., Thompson, C., Watson, F., Denham, R., & Khanal, G. (2013). The use of multi temporal LiDAR to assess basin-scale erosion and deposition following the catastrophic January 2011 Lockyer flood, SE Queensland, Australia. Geomorphology, 184, 111-126. https://doi.org/10.1016/j.geomorph.2012.11.023
Dadson, S. J., Hovius, N., Chen, H. G., Dade, W. B., Hsieh, M. L., Willett, S. D., Hu, J. C., Horng, M. J., Chen, M. C., Stark, C. P., Lague, D., & Lin, J. C. (2003). Links between erosion, runoff variability and seismicity in the Taiwan orogen. Nature, 426(6967), 648-651. https://doi.org/10.1038/nature02150
Dall’Asta, E., Forlani, G., Roncella, R., Santise, M., Diotri, F., & di Cella, U. M. (2017). Unmanned Aerial Systems and DSM matching for rock glacier monitoring. ISPRS Journal of photogrammetry and remote sensing, 127, 102-114.
DJI. (2022). Product Information. https://www.dji.com/
Eslami, S., Hoekstra, P., Nguyen Trung, N., Ahmed Kantoush, S., Van Binh, D., Duc Dung, D., Tran Quang, T., & van der Vegt, M. (2019). Tidal amplification and salt intrusion in the Mekong Delta driven by anthropogenic sediment starvation. Sci Rep, 9(1), 18746. https://doi.org/10.1038/s41598-019-55018-9
Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen, J. L., & Carbonneau, P. E. (2013). Topographic structure from motion: a new development in photogrammetric measurement. Earth surface processes and Landforms, 38(4), 421-430. https://doi.org/10.1002/esp.3366
Forsmoo, J., Anderson, K., Macleod, C. J. A., Wilkinson, M. E., & Brazier, R. (2018). Drone-based structure-from-motion photogrammetry captures grassland sward height variability. Journal of Applied Ecology, 55(6), 2587-2599. https://doi.org/10.1111/1365-2664.13148
Furukawa, Y., & Ponce, J. (2009). Accurate, dense, and robust multiview stereopsis. IEEE transactions on pattern analysis and machine intelligence, 32(8), 1362-1376.
Gallagher, L., & Peduzzi, P. (2019). Sand and sustainability: Finding new solutions for environmental governance of global sand resources.
Giles, P. T. (2001). Remote sensing and cast shadows in mountainous terrain. Photogrammetric Engineering and Remote Sensing, 67(7), 833-839. <Go to ISI>://WOS:000169495400007
Gindraux, S., Boesch, R., & Farinotti, D. (2017). Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles ′ Imagery on Glaciers. Remote Sensing, 9(2), 186. https://doi.org/ARTN 186
10.3390/rs9020186
Gleyzes, M. A., Perret, L., & Kubik, P. (2012). Pleiades system architecture and main performances. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39, 537-542.
Hackney, C. R., Darby, S. E., Parsons, D. R., Leyland, J., Best, J. L., Aalto, R., Nicholas, A. P., & Houseago, R. C. (2020). River bank instability from unsustainable sand mining in the lower Mekong River. Nature Sustainability, 3(3), 217-+. https://doi.org/10.1038/s41893-019-0455-3
Hartley, R., & Zisserman, A. (2003). Multiple view geometry in computer vision. Cambridge university press.
Hsu, T. W., Lin, T. Y., & Tseng, I. F. (2007). Human impact on coastal erosion in Taiwan. Journal of Coastal Research, 23(4), 961-+. https://doi.org/10.2112/04-0353r.1
James, M. R., & Robson, S. (2014). Mitigating systematic error in topographic models derived from UAV and ground-based image networks. Earth surface processes and Landforms, 39(10), 1413-1420. https://doi.org/10.1002/esp.3609
Jaud, M., Passot, S., Allemand, P., Le Dantec, N., Grandjean, P., & Delacourt, C. (2018). Suggestions to limit geometric distortions in the reconstruction of linear coastal landforms by SfM photogrammetry with PhotoScan® and MicMac® for UAV surveys with restricted GCPs pattern. Drones, 3(1), 2.
Javernick, L., Brasington, J., & Caruso, B. (2014). Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry. Geomorphology, 213, 166-182.
Jiménez-Jiménez, S. I., Ojeda-Bustamante, W., Marcial-Pablo, M. d. J., & Enciso, J. (2021). Digital terrain models generated with low-cost UAV photogrammetry: Methodology and accuracy. ISPRS International Journal of Geo-Information, 10(5), 285.
Kapustina, L., Izakova, N., Makovkina, E., & Khmelkov, M. (2021). The global drone market: Main development trends. SHS Web of Conferences,
Koehnken, L., & Rintoul, M. (2018). Impacts of sand mining on ecosystem structure, process and biodiversity in rivers. World Wildlife Fund International.
Kondolf, G. M. (1994). Geomorphic and Environmental-Effects of Instream Gravel Mining. Landscape and Urban planning, 28(2-3), 225-243. <Go to ISI>://WOS:A1994NL91600010
Kondolf, G. M. (1997). PROFILE: Hungry Water: Effects of Dams and Gravel Mining on River Channels. Environ Manage, 21(4), 533-551. https://doi.org/10.1007/s002679900048
Koschitzki, R., Schwalbe, E., Cardenas, C., & Maas, H.-G. (2017). Photogrammetric monitoring concept for remote landslide endangered areas using multi-temporal aerial imagery. 2017 First IEEE International Symposium of Geoscience and Remote Sensing (GRSS-CHILE),
Kuo, Y. C., & Chen, C. F. (2012, October 10-12). Satellite Image Change Detection Based on Iterative Histogram Matching Method The International Symposium of Remote Sensing 2012, Incheon, S. Korea.
Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.
Liu, S. J., Tong, X. H., Chen, J., Liu, X. F., Sun, W. Z., Xie, H., Chen, P., Jin, Y. M., & Ye, Z. (2016). A Linear Feature-Based Approach for the Registration of Unmanned Aerial Vehicle Remotely-Sensed Images and Airborne LiDAR Data. Remote Sensing, 8(2), 82. https://doi.org/ARTN 82
10.3390/rs8020082
Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60(2), 91-110. https://doi.org/Doi 10.1023/B:Visi.0000029664.99615.94
Maini, A. K., & Agrawal, V. (2011). Satellite technology: principles and applications. John Wiley & Sons.
Nesbit, P. R., & Hugenholtz, C. H. (2019). Enhancing UAV-SfM 3D Model Accuracy in High-Relief Landscapes by Incorporating Oblique Images. Remote Sensing, 11(3), 239. https://doi.org/ARTN 239
10.3390/rs11030239
Nguyen, Q., Goyal, R., Luyen, B. K., Le VAN, C., Cuong, C. X., Van Chung, P., Bui, N., & Xuan-Nam, B. (2020). Influence of Flight Height on The Accuracy of UAV Derived Digital Elevation Model at Complex Terrain. Inżynieria Mineralna, 1(1), 179–186-179–186.
Padmalal, D., & Maya, K. (2014). Sand mining: environmental impacts and selected case studies. Springer.
Palaseanu-Lovejoy, M., Bisson, M., Spinetti, C., Buongiorno, M. F., Alexandrov, O., & Cecere, T. (2019). High-Resolution and Accurate Topography Reconstruction of Mount Etna from Pleiades Satellite Data. Remote Sensing, 11(24), 2983. https://doi.org/ARTN 2983
10.3390/rs11242983
Peduzzi, P. (2014). Sand, rarer than one thinks. Environmental Development, 11, 208-218.
Persad, R. A., & Armenakis, C. (2017a). Automatic 3D Surface Co-Registration Using Keypoint Matching. Photogrammetric Engineering and Remote Sensing, 83(2), 137-151. https://doi.org/10.14358/Pers.83.2.137
Persad, R. A., & Armenakis, C. (2017b). Automatic co-registration of 3D multi-sensor point clouds. ISPRS Journal of photogrammetry and remote sensing, 130, 162-186. https://doi.org/10.1016/j.isprsjprs.2017.05.014
Peterson, L. E. (2009). K-nearest neighbor. Scholarpedia, 4(2), 1883.
Public Construction Commission, E. Y. (2000). 高屏大橋斷橋事件報告.
Rosnell, T., & Honkavaara, E. (2012). Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera. Sensors (Basel), 12(1), 453-480. https://doi.org/10.3390/s120100453
Rossi, P., Mancini, F., Dubbini, M., Mazzone, F., & Capra, A. (2017). Combining nadir and oblique UAV imagery to reconstruct quarry topography: methodology and feasibility analysis. European Journal of Remote Sensing, 50(1), 211-221. https://doi.org/10.1080/22797254.2017.1313097
Rusu, R. B., Marton, Z. C., Blodow, N., Dolha, M., & Beetz, M. (2008). Towards 3D Point cloud based object maps for household environments. Robotics and Autonomous Systems, 56(11), 927-941. https://doi.org/10.1016/j.robot.2008.08.005
Segal, A., Haehnel, D., & Thrun, S. (2009). Generalized-icp. Robotics: science and systems,
Sims, A. J., & Rutherfurd, I. D. (2017). Management responses to pulses of bedload sediment in rivers. Geomorphology, 294, 70-86. https://doi.org/10.1016/j.geomorph.2017.04.010
Sui, H. G., Xu, C., Liu, J. Y., & Hua, F. (2015). Automatic Optical-to-SAR Image Registration by Iterative Line Extraction and Voronoi Integrated Spectral Point Matching. IEEE Transactions on geoscience and remote sensing, 53(11), 6058-6072. https://doi.org/10.1109/Tgrs.2015.2431498
Tonkin, T. N., & Midgley, N. G. (2016). Ground-Control Networks for Image Based Surface Reconstruction: An Investigation of Optimum Survey Designs Using UAV Derived Imagery and Structure-from-Motion Photogrammetry. Remote Sensing, 8(9), 786. https://doi.org/ARTN 786
10.3390/rs8090786
Toutin, T. (2001). Elevation modelling from satellite visible and infrared (VIR) data. International Journal of Remote Sensing, 22(6), 1097-1125. https://doi.org/Doi 10.1080/01431160117862
Udin, W., & Ahmad, A. (2014). Assessment of photogrammetric mapping accuracy based on variation flying altitude using unmanned aerial vehicle. IOP conference series: earth and environmental science,
Uysal, M., Toprak, A. S., & Polat, N. (2015). DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill. Measurement, 73, 539-543. https://doi.org/10.1016/j.measurement.2015.06.010
Wang, S. Y., Ren, Z. K., Wu, C. Y., Lei, Q. Y., Gong, W. Y., Ou, Q., Zhang, H. P., Ren, G. X., & Li, C. Y. (2019). DEM generation from Worldview-2 stereo imagery and vertical accuracy assessment for its application in active tectonics. Geomorphology, 336, 107-118. https://doi.org/10.1016/j.geomorph.2019.03.016
Water Resources Agency, M. O. E. A., . (2021). Introduction to the history of dredging. https://iriver.wra.gov.tw/Dredge/Mileage
Westaway, R. M., Lane, S. N., & Hicks, D. M. (2001). Remote sensing of clear-water, shallow, gravel-bed rivers using digital photogrammetry. Photogrammetric Engineering and Remote Sensing, 67(11), 1271-1281. <Go to ISI>://WOS:000171928500007
Xu, Z. H., Xu, E. S., Wu, L. X., Liu, S. J., & Mao, Y. C. (2019). Registration of Terrestrial Laser Scanning Surveys Using Terrain-Invariant Regions for Measuring Exploitative Volumes over Open-Pit Mines. Remote Sensing, 11(6), 606. https://doi.org/ARTN 606
10.3390/rs11060606
Yu, L., Zhang, D. R., & Holden, E. J. (2008). A fast and fully automatic registration approach based on point features for multi-source remote-sensing images. Computers & Geosciences, 34(7), 838-848. https://doi.org/10.1016/j.cageo.2007.10.005
Yu, S. B., Chen, H. Y., & Kuo, L. C. (1997). Velocity field of GPS stations in the Taiwan area. Tectonophysics, 274(1-3), 41-59. https://doi.org/Doi 10.1016/S0040-1951(96)00297-1
Yurtseven, H. (2019). Comparison of GNSS-, TLS- and Different Altitude UAV-Generated Datasets on the Basis of Spatial Differences. ISPRS International Journal of Geo-Information, 8(4), 175. https://doi.org/ARTN 175
10.3390/ijgi8040175
Yusoff, A., Darwin, N., Majid, Z., Ariff, M., & Idris, K. (2018). Comprehensive analysis of flying altitude for high resolution slope mapping using UAV technology. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42(3/W4), 583-589.
Zhang, W. M., Qi, J. B., Wan, P., Wang, H. T., Xie, D. H., Wang, X. Y., & Yan, G. J. (2016). An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing, 8(6), 501. https://doi.org/ARTN 501
10.3390/rs8060501
Zhang, Z. Y. (1994). Iterative Point Matching for Registration of Free-Form Curves and Surfaces. International journal of computer vision, 13(2), 119-152. https://doi.org/Doi 10.1007/Bf01427149
Zhou, Y., Parsons, B., Elliott, J. R., Barisin, I., & Walker, R. T. (2015). Assessing the ability of Pleiades stereo imagery to determine height changes in earthquakes: A case study for the El Mayor-Cucapah epicentral area. Journal of Geophysical Research-Solid Earth, 120(12), 8793-8808. https://doi.org/10.1002/2015jb012358
Zhuo, X. Y., Koch, T., Kurz, F., Fraundorfer, F., & Reinartz, P. (2017). Automatic UAV Image Geo-Registration by Matching UAV Images to Georeferenced Image Data. Remote Sensing, 9(4), 376. https://doi.org/ARTN 376
10.3390/rs9040376
Zimmerman, T., Jansen, K., & Miller, J. (2020). Analysis of UAS Flight Altitude and Ground Control Point Parameters on DEM Accuracy along a Complex, Developed Coastline. Remote Sensing, 12(14), 2305. https://doi.org/ARTN 2305
10.3390/rs12142305
Zitová, B., & Flusser, J. (2003). Image registration methods:: a survey. Image and vision computing, 21(11), 977-1000. https://doi.org/10.1016/S0262-8856(03)00137-9
何春蓀. (1986). 台灣地質概論-台灣地質圖說明書. 增訂二版, 經濟部中央地質調查所, 共, 164.

指導教授

曾國欣(Kuo-Hsin Tseng)

審核日期

2024-7-31

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