Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development.

Driven by the “dual-carbon” strategy, the development of zero- and low-carbon parks has become a crucial approach to resolving the conflict between urban expansion and ecological limits. Using urban functional zoning and land use data, this study estimates carbon emissions in Xiamen and examines their spatial distribution at the functional zone level, along with an assessment of carbon balance zoning. The results indicate that (1) Carbon sources far exceed sinks, with spatial concentrations in southern and northern areas, respectively. Commercial, transportation, and industrial zones are major emission sources. (2) A significant negative spatial correlation in carbon emissions exists among functional zones, manifesting as an alternating pattern of high- and low-carbon zones. (3) 72% of the zones have an ecological support coefficient below one, indicating severe carbon imbalance. (4) Xiamen can be categorized into four carbon balance functional zones, with carbon-source regulation zones accounting for 70%, core carbon-source zones accounting for 5%, and carbon-sink stressed zones accounting for 25%. No core carbon sink zones are identified. Based on these findings, targeted strategies are proposed: ecological restoration in northern Xiamen, carbon emission regulation in central areas, and source reduction in the south. These measures provide a scientific foundation for supporting Xiamen’s low-carbon transition and sustainable development.