【摘要】 为了深入了解我国西南高寒山区InSAR相干性在不同地表覆盖类型下如何随时间和空间变化，以云南省德钦县为例，基于2020年5月—2023年5月期间Sentinel-1影像数据，利用统计分析方法、区间划分方法揭示时序InSAR相干性在不同地表覆盖类型下的时空变化规律；提取植被覆盖度、土壤湿度、降雨量等影响因子，通过建立植被覆盖度、土壤湿度与InSAR相干性之间的定量关系模型，分析各因子对InSAR相干性的驱动机制并量化其影响程度，明确时序InSAR相干性变化的关键驱动因素。研究结果表明：时序InSAR相干性表现出明显时空异质性。在时间上随季节变化呈现周期性波动，冬季最高，春季次之，秋季和夏季最低，在每年1月达到峰值，7月降至谷值。在空间上，高相干区主要分布在城镇区域；偏高相干区多见于裸地；中相干区主要分布在耕地；低相干区则主要集中在林地。季节变化、降雨量对InSAR相干性具有重要影响；植被覆盖度和土壤湿度与InSAR相干性呈负相关关系，随着植被覆盖度和土壤湿度的增加，InSAR相干性呈下降趋势，其中植被覆盖度对InSAR相干性的影响更显著。更多还原

【Abstract】 To gain a deeper understanding of how the InSAR coherence changes with time and space under different surface cover types in this region, this paper takes Deqin County, Yunnan Province as an example. Based on Sentinel-1 image data from May 2020 to May 2023,this paper first uses statistical analysis methods to reveal the spatiotemporal variation patterns of InSAR coherence in different surface cover types over time; then, it extracts influencing factors such as vegetation coverage, soil moisture, and rainfall, and establishes quantitative relationship models between vegetation coverage, soil moisture and InSAR coherence to analyze the driving mechanisms of each factor on InSAR coherence and quantify their influence degrees, and clarify the key driving factors of the temporal variation of InSAR coherence. The research results show that: The temporal and spatial heterogeneity of InSAR coherence is obvious. In terms of time, InSAR coherence shows periodic fluctuations with seasonal variations, with the highest value in winter, followed by spring, and the lowest values in autumn and summer, reaching the peak in January and the trough in July. In terms of space, the distribution characteristics of coherence show a significant dependence on land cover types. The high coherence zone is mainly distributed in urban areas; the moderately high coherence zone is more common in bare land; the medium coherence zone is mainly distributed in cultivated land; and the low coherence zone is mainly concentrated in forest land.Seasonal variations and rainfall amounts have significant impacts on InSAR coherence. Vegetation coverage and soil moisture are negatively correlated with InSAR coherence. As vegetation coverage and soil moisture increase, InSAR coherence decreases. Among them, the influence of vegetation coverage on InSAR coherence is more significant.更多还原