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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭舒婷(Su-Ting Cheng) | |
| dc.contributor.author | Kai-Chih Yin | en |
| dc.contributor.author | 殷楷智 | zh_TW |
| dc.date.accessioned | 2023-03-19T23:26:38Z | - |
| dc.date.copyright | 2022-10-14 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-09-23 | |
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Analyses of soil water content variations and GPR attribute distributions. Journal of Hydrology, 267(3-4), 217-226. Song, J., & Lyu, M. R. (2005). A Hough transform based line recognition method utilizing both parameter space and image space. Pattern recognition, 38(4), 539-552. Sorgonà, A., Proto, A. R., Abenavoli, L. M., & Di Iorio, A. (2018). Spatial distribution of coarse root biomass and carbon in a high-density olive orchard: effects of mechanical harvesting methods. Trees, 32(4), 919-931. Stover, D. B., Day, F. P., Butnor, J. R., & Drake, B. G. (2007). Effect of elevated CO2 on coarse‐root biomass in Florida scrub detected by ground‐penetrating radar. Ecology, 88(5), 1328-1334. Tardío, G., González-Ollauri, A., & Mickovski, S. B. (2016). A non-invasive preferential root distribution analysis methodology from a slope stability approach. Ecological Engineering, 97, 46-57. Topp, G. C., Davis, J. L., & Annan, A. P. (1980). Electromagnetic determination of soil water content: Measurements in coaxial transmission lines. Water resources research, 16(3), 574-582. Tracy, S. R., Roberts, J. A., Black, C. R., McNeill, A., Davidson, R., & Mooney, S. J. (2010). The X-factor: visualizing undisturbed root architecture in soils using X-ray computed tomography. Journal of experimental botany, 61(2), 311-313. Utsi, E. (2014). Target resolution using very high frequency ground penetrating radar. In Structural Faults and Repair 2014. Wang, X., Allison, R. B., Wang, L., & Ross, R. J. (2007). Acoustic tomography for decay detection in red oak trees. Research Paper FPL-RP-642. Madison, WI: US Department of Agriculture, Forest Service, Forest Products Laboratory. 7 pages., 642. Wu, Y., Guo, L., Cui, X., Chen, J., Cao, X., & Lin, H. (2014). Ground-penetrating radar-based automatic reconstruction of three-dimensional coarse root system architecture. Plant and soil, 383(1), 155-172. Zenone, T., Morelli, G., Teobaldelli, M., Fischanger, F., Matteucci, M., Sordini, M., Armani A., Ferre, C., Chiti, T., & Seufert, G. (2008). Preliminary use of ground-penetrating radar and electrical resistivity tomography to study tree roots in pine forests and poplar plantations. Functional Plant Biology, 35(10), 1047-1058. Zhu, S., Huang, C., Su, Y., & Sato, M. (2014). 3D ground penetrating radar to detect tree roots and estimate root biomass in the field. Remote Sensing, 6(6), 5754-5773. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85857 | - |
| dc.description.abstract | 樹木根系對於林木的生長與安全風險至關重要，亦為植物碳匯重要的地下碳庫。然而，位處地底之樹木根系不易調查。有別於傳統破壞性檢測，透地雷達檢測法可以避免對樹木造成不可逆的傷害。為改良透地雷達資料分析法，以利探討透地雷達訊號與根系生物量之關係，本研究透過砂坑試驗及人造林地實地探測資料，建立透地雷達訊號分析標準流程與參數設定，並分別以振幅及波型發展資料分析方法，以推估施測環境之土壤含水率與根系生物量。 本研究將資料前處理標準程序簡化為四項步驟，包括(1)以初達波位置進行地面校正；(2)以移動平均法進行軌跡平滑；(3)去除背景雜訊；(4)以常態化方式將訊號進行增益處理。接著，本研究透過霍夫轉換自動判釋雙曲線波型，建立推估體積土壤含水率之方法，研究結果顯示此方法於溪頭人造林推估平均誤差約為3.6%。研究結果亦發現，振幅閾值之篩選與土壤含水率有關。利用土壤含水率設立彈性閾值區間，以篩選後之像素數量與根系生物量進行線性迴歸分析，能有效捕捉樹木根系特徵訊號，決定係數(R2)達0.918。透過上述資料分析法之建立，透地雷達檢測法在樹木檢測、生物量推估等相關調查有其發展潛力與應用價值。 | zh_TW |
| dc.description.abstract | Tree root systems are critical to the stand growth and safety of trees, and are also an important part of belowground carbon storage for forest carbon sink. However, tree root systems are mostly underground making them difficult to investigate. Different from traditional destructive testing method, Ground penetrating radar (GPR) detection method can avoid irreversible damage to trees. In order to improve the analysis method of GPR data, explore the relationship between ground-penetrating radar signal and root biomass. In this study, I conducted a sandbox experiment and field detection in artificial plantation in Shuili and Xitou to develop standard operating procedures (SOPs) for GPR data analysis and parameter setting, and to improve GPR data analysis method with amplitude and wave pattern respectively for estimating the soil water content in detecting environment, and for exploring the relationship between signal and root biomass. In this study, the SOPs of data preprocessing is simplified into four steps, including (1) ground level calibration by the position of the first arrival wave; (2) smoothing each trace by moving average method; (3) background noise removal; (4) In the normalization method, the signal is subjected to gain processing. This study established a method for estimating volumetric soil moisture content (SMC) by automatically interpreting the hyperbolic wave pattern through Hough transform. The results show that the average error of this method is about 3.6% in the estimation of planted forests in Xitou. This study also found that the selection of the amplitude threshold was related to the SMC. The elastic threshold intervals were established by SMC, and linear regression analysis was performed on the number of pixels and root biomass after the amplitude threshold filtering method, which could effectively capture the characteristic signal of tree root system, and the coefficient of determination (R2) reached 0.918. Based on the data analysis method of this study, the GPR detection method has its potential in related investigations about tree detection and root biomass estimation. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T23:26:38Z (GMT). No. of bitstreams: 1 U0001-2209202223091400.pdf: 3192877 bytes, checksum: 7098663445e0b5aedf55d075c420d545 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 謝誌 i 摘要 iii Abstract iv 目錄 vi 圖目錄 viii 表目錄 x 第壹章 緒論 1 第一節 研究背景與動機 1 第二節 根系調查檢測法之介紹 2 第三節 透地雷達兩大研究類型 4 第四節 透地雷達應用於臺灣林業研究之困境 9 第五節 研究目的 10 第貳章 材料與方法 12 第一節 軟硬體設備 12 第二節 試驗設計與資料蒐集 13 第三節 分析方法 16 第參章 結果 23 第一節 透地雷達訊號前處裡 23 第二節 雙曲線擬合參數設立與驗證 24 第三節 應用透地雷達推估林地之土壤含水率 27 第四節 應用雷達波振幅數值推估樹木根系生物量 29 第肆章 討論 36 第一節 影響雷達回波圖成像之物理意義 36 第二節 土壤含水率推估誤差探討 37 第三節 像素閾值篩選法無法應用於臺灣森林 38 第四節 土壤含水率對樹木根系生物量推估之影響 40 第五節 透地雷達根系生物量研究之未來展望 41 第伍章 結論 43 第陸章 參考文獻 44 附錄 50 | |
| dc.language.iso | zh-TW | |
| dc.subject | 非破壞性檢測 | zh_TW |
| dc.subject | 透地雷達 | zh_TW |
| dc.subject | 霍夫轉換 | zh_TW |
| dc.subject | 土壤含水率推估 | zh_TW |
| dc.subject | 彈性閾值區間 | zh_TW |
| dc.subject | 振幅閾值篩選法 | zh_TW |
| dc.subject | amplitude threshold filtering method | en |
| dc.subject | estimation of soil moisture content | en |
| dc.subject | ground penetrating radar (GPR) | en |
| dc.subject | elastic threshold intervals | en |
| dc.subject | Hough transform | en |
| dc.subject | non-destructed testing (NDT) | en |
| dc.title | 改良透地雷達訊號分析法於林業科學之應用 | zh_TW |
| dc.title | Improvement of Ground Penetrating Radar Signal Analysis Methods for Applications in Forest Science | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 王素芬(Su-Fen Wang),王建凱(Chien-Kai Wang),吳孟玲(Meing-Ling Wu) | |
| dc.subject.keyword | 透地雷達,非破壞性檢測,霍夫轉換,土壤含水率推估,彈性閾值區間,振幅閾值篩選法, | zh_TW |
| dc.subject.keyword | ground penetrating radar (GPR),non-destructed testing (NDT),Hough transform,estimation of soil moisture content,elastic threshold intervals,amplitude threshold filtering method, | en |
| dc.relation.page | 69 | |
| dc.identifier.doi | 10.6342/NTU202203862 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2022-09-26 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 森林環境暨資源學研究所 | zh_TW |
| dc.date.embargo-lift | 2027-09-15 | - |
| 顯示於系所單位： | 森林環境暨資源學系 | |
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