[目的] 结合不透水面对新型城镇化水平进行分析，探究江西省各市新型城镇化发展的规律及趋势，为江西省新型城镇化的发展提供科学参考。[方法] 从人口、经济、社会、空间4个方面构建新型城镇化的指标体系，在分析江西省1988-2017年各市新型城镇化水平的同时，基于不透水面数据，研究城镇化水平与不透水面不同阶段的相关性变化，构建二者的线性关系模型。[结果] ①30 a间江西省城镇不透水面扩张明显，整体呈现高-较高-中-较低-低密度圈层分布的空间格局。②江西省城镇化发展水平呈现出"北高南低"的空间分布特征，区域间发展不均衡；③2006年为该区城镇化水平增长的突变点，前后城镇化水平与不透水面相关性存在差异；④各市不透水面与新型城镇化水平线性拟合决定系数R2均大于0.9，拟合效果较好。[结论] 不透水面与新型城镇化水平存在较强相关性，利用不透水面数据能较好地反映各市新型城镇化水平，这有助于分析城镇化发展趋势，促进区域城镇化研究。
[Objective] The new urbanization level of Jiangxi Province was analyzed based on the impervious surface data, the pattern and trend of the new urbanization development in cities were studied in order to provide scientific support for the development of the new urbanization of Jiangxi Province.[Methods] By constructing a comprehensive index system according to population, economic and social development, urban space, the new urbanization level of each city in Jiangxi Province was analyzed during the period from 1988 to 2017, and then based on the data of urban impervious surface, the correlation changes between new urbanization level and impervious surface in different stages were studied, and a linear relationship model between them were built.[Results] Over the past 30 years, the urban impervious surface expanded significantly, and it presented a spatial pattern of "high-slightly high-middle-slightly low-low" density circle distribution. The level of new-type urbanization in Jiangxi Province exhibited a general trend of "high in the north and low in the south". The regional development of urbanization was uneven. The year of 2006 marked an abrupt change point of new-type urbanization level growth. Before and after the abrupt change point, the correlation between new-type urbanization level and impervious surface was different. The R2 value of linear fitting between the impervious surface and the new-type urbanization were both above 0.9, which showed that the data of impervious surface could better reflect the new urbanization level of each city.[Conclusion] There is a strong correlation between the impervious surface and the new-type urbanization level, so the new-type urbanization level of each city can be well reflected by using the impervious surface data, it may finally help to analyze the development trend of urbanization and promote regional urbanization research.