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題名 合成孔徑雷達干涉產製數值高程模型影響因素評估 - 以季節像對與多視處理為例
Evaluation of the Factors Influencing InSAR Digital Elevation Model - Case Study on Image Selection and Multi-look Processing
作者 林士淵
Lin,  Shih-Yuan
貢獻者 地政系
關鍵詞 合成孔徑雷達干涉技術 ; 數值高程模型 ; 季節像對 ; 多視處理
Synthetic Aperture Radar Technique ; Digital Elevation Model ; Seasonal Image Pair ; Multi-Look Processing
日期 2020-06
上傳時間 24-May-2021 14:46:02 (UTC+8)
摘要 合成孔徑雷達干涉(Interferometric Synthetic Aperture Radar, InSAR)技術可以利用雷達資料的相位資 訊取得三維的地表訊息。InSAR 技術常應用於產製數值高程模型(Digital Elevation Model, DEM),然而,雖然此項技術雖已被建立許久且發展成熟,其在應用上仍受到許多限制。本研究之宗旨有二,其一為針對不同季節的像對產製的數值地形模型做探討,其二為觀察多視步驟(Multi-look processing)在不同情況下採用的必要性。研究結果顯示,不論是否採用多視步驟,使用冬季像對可以提升結果精度,其比例最高達66.57%;在多視處理的部分,夏季像對若採用多視處理,精度可以提高15.14%~31.59%,然冬季像對若採用多視處理,精度則普遍降低,最差為-23.17%。
Interferometric Synthetic Aperture Radar (InSAR) is one of the techniques used to extract three-dimensional ground surface information from the phase data recorded in radar images. InSAR technique is often applied to generate digital elevation models (DEMs). Although this technique has been developed maturely for a long time, it is found that the capability to produce high-accuracy DEM is limited. There are two aims in our research: the first is the discussion of using different seasonal dataset to generate DEMs, and the second is the observation the necessity of using multi-look processing in InSAR processing procedure. The result has shown that no matter if the multi-look processing is applied, using winter image pair is helpful to improve the accuracy up to 66.57%. For summer image pair, the accuracy could be enhanced by 15.14% to 31.59% if multi-look processing is applied, while for winter pair, the accuracy is degraded up to 23.17% if multi-look processing is applied.
關聯 航測及遙測學刊, Vol.25, No.2, pp.115-128
資料類型 article
DOI https://doi.org/ 10.6574/JPRS.202006_25(2).0004
dc.contributor 地政系
dc.creator (作者) 林士淵
dc.creator (作者) Lin,  Shih-Yuan
dc.date (日期) 2020-06
dc.date.accessioned 24-May-2021 14:46:02 (UTC+8)-
dc.date.available 24-May-2021 14:46:02 (UTC+8)-
dc.date.issued (上傳時間) 24-May-2021 14:46:02 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/135060-
dc.description.abstract (摘要) 合成孔徑雷達干涉(Interferometric Synthetic Aperture Radar, InSAR)技術可以利用雷達資料的相位資 訊取得三維的地表訊息。InSAR 技術常應用於產製數值高程模型(Digital Elevation Model, DEM),然而,雖然此項技術雖已被建立許久且發展成熟,其在應用上仍受到許多限制。本研究之宗旨有二,其一為針對不同季節的像對產製的數值地形模型做探討,其二為觀察多視步驟(Multi-look processing)在不同情況下採用的必要性。研究結果顯示,不論是否採用多視步驟,使用冬季像對可以提升結果精度,其比例最高達66.57%;在多視處理的部分,夏季像對若採用多視處理,精度可以提高15.14%~31.59%,然冬季像對若採用多視處理,精度則普遍降低,最差為-23.17%。
dc.description.abstract (摘要) Interferometric Synthetic Aperture Radar (InSAR) is one of the techniques used to extract three-dimensional ground surface information from the phase data recorded in radar images. InSAR technique is often applied to generate digital elevation models (DEMs). Although this technique has been developed maturely for a long time, it is found that the capability to produce high-accuracy DEM is limited. There are two aims in our research: the first is the discussion of using different seasonal dataset to generate DEMs, and the second is the observation the necessity of using multi-look processing in InSAR processing procedure. The result has shown that no matter if the multi-look processing is applied, using winter image pair is helpful to improve the accuracy up to 66.57%. For summer image pair, the accuracy could be enhanced by 15.14% to 31.59% if multi-look processing is applied, while for winter pair, the accuracy is degraded up to 23.17% if multi-look processing is applied.
dc.format.extent 316518 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) 航測及遙測學刊, Vol.25, No.2, pp.115-128
dc.subject (關鍵詞) 合成孔徑雷達干涉技術 ; 數值高程模型 ; 季節像對 ; 多視處理
dc.subject (關鍵詞) Synthetic Aperture Radar Technique ; Digital Elevation Model ; Seasonal Image Pair ; Multi-Look Processing
dc.title (題名) 合成孔徑雷達干涉產製數值高程模型影響因素評估 - 以季節像對與多視處理為例
dc.title (題名) Evaluation of the Factors Influencing InSAR Digital Elevation Model - Case Study on Image Selection and Multi-look Processing
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.6574%2fJPRS.202006_25(2).0004
dc.doi.uri (DOI) https://doi.org/ 10.6574/JPRS.202006_25(2).0004