地表形變動態與都市基礎設施之安全及穩定密切相關。桃園地區工程建設密集且都市發展快速，因此有必要建立長時序且空間連續之地表形變監測成果。本研究使用2017年6月至2026年2月之Sentinel-1雷達影像，結合SBAS-InSAR時序分析與升、降軌2.5D形變解算，重建桃園地區垂直向地表形變時間序列，並探討其時空演化特徵。
在資料解析上，藉由導入兩階段時序分群法（Time Series Clustering），針對形變曲線特徵與方向性累積程度進行細緻化分類。分析指出，桃園地區的地表位移型態涵蓋正向累積、顯著負向累積、緩慢負向累積、波動型以及近穩定型等五大類別。
空間分布上，中北部以正向累積為主，第一時段強正向累積區期末約達+14 mm，第二時段強正向累積區於2025年下半年曾接近+25 mm，期末約為+18 mm，且由中壢核心向蘆竹、龜山與桃園北部擴展。西側則為主要負向形變區，第一時段顯著負向累積型期末約為-20至-26 mm，第二時段強顯著負向累積區曾達約-20 mm，期末約為-18 mm，並於新屋、觀音及部分楊梅周邊形成較連續之負向累積帶。南側與東南側主要表現為緩慢負向累積，兩時段期末多介於約-5至-10 mm，反映較弱但具潛在轉變意義之下降區。北部至西北部之波動型於第一時段約介於-6至+5 mm，第二時段則多位於零位移以上但未形成穩定單向累積；近穩定型主要分布於中南部與部分東側內陸，第一時段約介於-4至+1 mm，第二時段最高約達+4 mm後回落至零位移附近。
本研究透過長時序InSAR資料與時序分群方法，同時辨識累積、波動、近穩定與潛在轉變區，有助於建立區域尺度之地表形變監測架構，並可作為後續地質、水文、工程防災與土地規劃之參考依據。

Continuous surface deformation monitoring is crucial for urban infrastructure safety, particularly in rapidly developing areas like Taoyuan. This study reconstructs the region's vertical deformation from June 2017 to February 2026 using Sentinel-1 imagery, SBAS-InSAR analysis, and 2.5D geometric resolution.
A two-stage time series clustering approach was applied to classify deformation behaviors into five types: positive, significant negative, and slow negative accumulations, alongside fluctuating and near-stable states.
Spatially, central-northern areas exhibited positive accumulation, expanding from Zhongli toward Luzhu, Guishan, and northern Taoyuan. Displacements here reached +14 mm in the first phase; the second phase peaked near +25 mm in late 2025 before ending at +18 mm. Conversely, the western sector (Xinwu, Guanyin, Yangmei) formed a continuous subsidence belt with significant negative accumulations of -20 to -26 mm in Phase 1. In Phase 2, this area reached -20 mm before ending at -18 mm. Southern and southeastern fringes showed slow negative accumulation (-5 to -10 mm across both phase ends). For the fluctuating type in the north and northwest, Phase 1 ranged from -6 to +5 mm, while Phase 2 stayed mostly above zero without directional buildup. The central-southern and eastern inland areas remained near-stable, ranging from -4 to +1 mm in Phase 1, and peaking at +4 mm before returning near zero in Phase 2.
Integrating long-term InSAR data with time series clustering effectively differentiates surface dynamics, offering a concise framework for future geological, hydrological, and infrastructural planning.

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