The impact of human activities on terrestrial ecosystems is becoming more intense than ever in history. Human disturbance analyses play important roles in appropriately managing the human–environment relationship. In this study, a human disturbance index (HDI) that uses land use and land cover data from 1980, 2000, 2010, and 2018 is proposed to assess the human disturbance of ecosystems in the Guangdong-Hong Kong-Macao Greater Bay Area. The HDI is first calculated by classifying the human disturbance intensity into seven levels and 13 categories from weak to strong in ecosystems. Then the driving factors of the HDI spatial pattern change are explored using a geographically weighted regression (GWR) model. The results showed that the spatial pattern of the HDI was high in the middle and low in the surrounding areas. The intensity of human disturbance increased, and the medium and high disturbance areas expanded during 1980–2018, especially in Guangzhou, Foshan, Shenzhen, and Dongguan. Human disturbance displayed an obvious spatial heterogeneity. The GWR model had a better explanation effect of the analysis of the HDI change drivers. The driving effect of the socioeconomic conditions was significantly stronger than that of the natural environmental. This study assists in understanding the distribution and change characteristics of the ecological environment in areas with strong human activities and provides a reference for related studies.

人类活动对陆地生态系统的影响比历史上任何时候都更加强烈。人为干扰分析在适当管理人与环境关系方面发挥着重要作用。本研究提出了利用1980年、2000年、2010年和2018年的土地利用和土地覆盖数据的人为干扰指数（HDI）来评估粤港澳大湾区生态系统的人为干扰。HDI首先通过将人为干扰强度分为生态系统中从弱到强的7个等级和13个类别来计算。然后使用地理加权回归 (GWR) 模型探索 HDI 空间格局变化的驱动因素。结果表明，人类发展指数的空间格局呈中高、周边低。1980-2018年人为干扰强度增加，中、高干扰区域扩大，尤其是广州、佛山、深圳和东莞。人为干扰表现出明显的空间异质性。GWR 模型对 HDI 变化驱动因素的分析具有较好的解释效果。社会经济条件的驱动作用明显强于自然环境。本研究有助于了解人类活动强烈地区生态环境的分布和变化特征，为相关研究提供参考。GWR 模型对 HDI 变化驱动因素的分析具有较好的解释效果。社会经济条件的驱动作用明显强于自然环境。本研究有助于了解人类活动强烈地区生态环境的分布和变化特征，为相关研究提供参考。GWR 模型对 HDI 变化驱动因素的分析具有较好的解释效果。社会经济条件的驱动作用明显强于自然环境。本研究有助于了解人类活动强烈地区生态环境的分布和变化特征，为相关研究提供参考。