Nature-based recreation has become an important activity in contemporary society and a key component of cultural ecosystem services. Although the methods of mapping the outdoor recreation supply have been gradually improved, few studies have carried out multi-temporal evaluations. Based on land use/land cover (LULC), POI, and other web-open data, we mapped the recreational service supply in Shanghai in 2008 and 2018, combining recreation potential and recreation opportunities. We first selected the evaluation indicators, using LULC to measure recreational potential, and POI density and accessibility to measure recreational opportunities. Then, we used principal component analysis (PCA) to determine the weights of the 12 factors that measure recreational opportunities, and made RO and RP maps, respectively. Finally, we overlaid RO and RP maps to obtain the spatial distribution map of recreation service supply. Our results showed that the supply of recreation services in 2008 and 2018 presented a “V-shaped” gradient along the city center areas—the peri-urban areas—the rural areas. Compared with the year 2008, the average recreation value decreased in nine regions, but increased in Chongming District in 2018. The assessment and mapping of recreation service supply value provide a basis for the development of local recreational resources, land use decisions, and the management of recreational cultural ecosystem services.

Rapid urbanization and industrialization have significantly reshaped rural landscapes in metropolitan fringe areas, resulting in “hybridized” characteristics. This study establishes an analytical framework to systematically characterize hybrid rural landscapes, diagnose specific local issues, reveal their spatial differentiation patterns and driving mechanisms, and propose targeted governance strategies. Taking 124 rural units in Baoshan District, Shanghai as a case, multi-source data from the latest available years (2020–2023) were compiled as a cross-sectional snapshot, and a comprehensive indicator system integrating landscape pattern (P), social function (F), and spatial vitality (V) was developed. Utilizing multi-source geospatial data—including land-use maps, points of interest, and mobile signaling data—Gaussian Mixture Models were applied to classify typical hybrid landscape types. Spatial evolution processes and underlying driving forces were further interpreted through remote sensing imagery analysis, field investigations, and policy document reviews. Eleven distinctive hybrid rural landscape types (HTs) were characterized, forming a spatial gradient from urban to rural, encompassing “high-density urbanized” → “ecologically embedded” → “production–living integrated” → “traditional rural landscapes”. Additionally, five representative evolutionary patterns—“urban restructuring”, “ecological orientation”, “industrial-driven transition”, “transitional hybridization”, and “traditional preservation”—were identified, shaped by spatial configuration, planning policies, industrial investments, and demographic dynamics. The framework enhances understanding of the complexity and evolutionary dynamics of rural landscapes, providing theoretical insights and practical guidance for effective typological governance and targeted policy interventions.