Quantifying high spatiotemporal impervious surface change with time series PlanetScope imagery

Monitoring impervious surface change (ISC) at high spatiotemporal resolution is essential for understanding urban expansion and renewal, yet such studies are often limited by the high cost of obtaining high-resolution imagery. Additionally, there is a research gap between remote sensing-based ISC detection and urban topic-driven research, resulting in a lack of systematic methods that integrate spatial and temporal dynamics with quantitative metrics applicable to urban analysis. To address these challenges, we developed a two-component framework. We first detected ISC using low-cost CubeSat, PlanetScope (3 m, near daily) imagery, then aggregated ISC spatially and temporally to recognize urban change patterns. This involved developing a hybrid time series method where change locations and change types were identified with a U-Net model, followed by dating these changes using Continuous Change Detection. Next, we quantified ISC characteristics through four facets: distribution, speed, intensity, and structure within census block groups and across monthly and seasonal scales. We evaluated the framework using two study areas: Buffalo, New York, representing urban renewal, and Buckeye, Arizona, exemplifying urban expansion. Our first component demonstrated high performance in the ISC location (Overall Accuracy (OA) = 0.94) and good performance in change timing (OA = 0.77). Results from the second component highlighted contrasts between the two study areas, with Buffalo showing fragmented, self-motivated, and seasonally sensitive renewal, while Buckeye displayed spatially coherent, large-scale, and consistently expanding suburban growth. Quantitatively, Buckeye exhibited a ISC rate approximately ten times higher than that of Buffalo, whereas Buffalo showed greater seasonal variability in ISC activity, with peaks occurring in spring. In both cities, the majority of construction-related changes were concentrated in residential areas. We developed a two-component framework using PlanetScope imagery that offers a scalable, practical method for supporting high-resolution, time-sensitive urban studies.