西部矿区煤矿开采具有浅埋深、薄基岩、多煤层开采、地表环境脆弱等特点，为化解开采地表沉陷传统观测方法覆盖范围小、作业强度高、自动化程度低等难题，引入无人机（Unmanned Aerial Vehicle, UAV）摄影测量技术观测并分析某煤矿工作面地表沉陷规律。结果表明：UAV摄影测量观测开采沉陷的中误差为4.4 cm，满足地表沉陷整体观测需求；获取的2.53 km²测区范围内地表整体沉陷模型可准确反映矿区地表沉陷区域及沉陷幅度；受多煤层开采影响地表沉陷模型呈不均匀盆状，沿工作面走向、倾向沉陷曲线均呈现不对称现象，最大沉陷值3.18 m。

In the western mining area, coal mining is characterized by shallow burial depth, thin bedrock, multi coal seam mining, and a fragile surface environment. To address the limitations of traditional observation methods for mining-induced subsidence, such as small coverage, high operation intensity, and low automation, unmanned aerial vehicle （UAV） photogrammetry technology has been introduced to observe and analyze the surface subsidence patterns of a coal mine working face. The results show that: the UAV photogrammetry method achieves a centimeter-level observation accuracy, with a median error of 4.4 cm, which meets the overall observation requirements for surface subsidence. A surface subsidence model of the entire mining area within a 2.53 km² survey area was obtained using the UAV photogrammetry method. This model accurately reflects the subsidence area and amplitude of the surface in the mining area. Due to the influence of multiple coal seams mining, the surface subsidence model exhibits an uneven basin shape. The subsidence curves along the strike and dip of the working face show asymmetry, with a maximum subsidence value of 3.18 m.