This study tries to gain an understanding of the unique spatial patterns of polder areas. Starting from a typical “water-polder-village” combination of spatial elements, our study begins by identifying land use in the polder area using Sentinel-2 data and unsupervised machine learning techniques, taking Gaochun District, Nanjing (China), as an example. Next, we conducted a spatial analysis of change for different years using multiple land-use change indices. Finally, geographically weighted regression (GWR) was developed to account for the heterogeneity of spatial patterns and visualize the spatial distributions of the estimated coefficients. The results, derived from the indices we have constructed, indicate that the water-polder-village is the main subject of spatial pattern changes, with spatial replacement of water and polder and incremental quantitative changes in village areas. Additionally, the main source of existing village land comes from the occupation of polders. Furthermore, the impacts of natural and ecological, development and construction, population, and economic factors on the spatial patterns of the polder area exhibit spatiotemporal heterogeneity. Meanwhile, in rapidly developing areas, population, economy, and construction development may negatively impact the protection of polders. The results provide a reference for the construction and protection of production, living, and ecological spaces in polder areas.