环鄱阳湖城市群作为江西省一个重要的经济和生态区域，其土地利用变化不仅影响当地的经济和社会发展，也对生态环境具有深远的影响。探讨环鄱阳湖城市群土地利用／覆盖变化及其驱动因素，对于该区域的土地管理和可持续发展具有重要意义。基于环鄱阳湖城市群2003年、2009年、2013年、2018年和2022年5期Landsat遥感影像数据，首先对遥感影像进行土地利用分类，其次运用土地利用动态度、土地利用转移矩阵及土地利用综合程度指数等方法研究该区域的土地利用时空变化特征，最后利用地理探测器探讨研究区土地利用变化的驱动因素。结果表明：2003—2022年，研究区以耕地和林地为主，建设用地面积单调增加，其他地类非单调性变化，但整体上地类面积在减少；耕地、林地面积的增减是研究区最主要的土地变化类型，各地类之间的转换频繁，建设用地增加以耕地和林地转出为主；研究区中部的土地利用强度高于其他地区，东北部的土地利用强度较低；因子探测表明自然因子的解释度对土地利用变化的影响较高，后期社会经济因子的解释度对土地利用的影响也在逐渐上升；交互探测结果显示，各个因子之间存在显著的交互作用，双因子交互的解释度高于单因子的解释度。可见，土地利用变化受多种因素共同影响。

The urban agglomeration around Poyang Lake is considered a vital economic and ecological region in Jiangxi Province, and its land use/land cover change is believed to impact both local economic and social development, as well as the ecological environment. Exploring this land use/land cover change and its driving factors are regarded as significant for land management and sustainable development. Based on the Landsat remote sensing image data of five periods in 2003, 2009, 2013, 2018, and 2022 of the urban agglomeration around Poyang Lake, the land use of remote sensing images was firstly classified, and then the spatial-temporal characteristics of land use change in this region were studied using the methods of land use dynamics, land use transfer matrix, and land use comprehensive degree index. Finally, the driving factors of land use change in the study area were investigated using the geographical detector. The results reveal that the study area is primarily cultivated land and forest land, the area of construction land increases steadily, while other land types change irregularly, but the overall land type area decreases. The increase and decrease of cultivated land and forest land area are the main types of land change in the study area, and the conversion between different classes is frequent. The land use intensity in the middle of the study area is higher than that in other areas, while the land use intensity in the northeast is lower. Factor detection shows that the explanation degree of natural factors has a higher impact on land use change, and the explanation degree of social and economic factors has a higher impact on land use in the later stages. The results of interaction detection show that a significant interaction exists between the factors, and the interpretation of the two-factor interaction is higher than that of the single factor. It can be seen that land use change is affected by many factors.