By using a land cover map, normalized difference vegetation index (NDVI) data sets, monthly meteorological data and observed net primary productivity (NPP) data, we have improved the method of estimating light use efficiency (LUE) for different biomes and soil moisture coefficients in the Carnegie–Ames–Stanford Approach (CASA) ecosystem model. Based on this improved model we produced an annual NPP map (in 1999) for the East Asia region located at 10–70° N, 70–170° E (about 19.66% of the terrestrial surface of the Earth). The results show that the mean NPP for the study area in 1999 was 374.12 g carbon (C) m⁻² year⁻¹ and the total NPP was 1.096 × 10¹⁴ kg C year⁻¹, making up 17.51–18.39% of the global NPP. Comparison between the estimated NPP obtained from this improved CASA ecosystem model and the observed NPP obtained from two NPP databases indicates that the estimated NPP is close to the observed NPP, with an average error of 5.15% for the study region. We used two different land cover maps of China to drive the improved CASA model by keeping other inputs unchanged to determine how the classification accuracy of the land cover map affects the estimated NPP, and the results indicate that an accurate land cover map is important for obtaining an accurate and reliable estimate of NPP for some regions, especially for a particular biome.

Human activities affect the Earth System with an unprecedented magnitude, causing undesirable irreversible degradation. The United Nation’s Sustainable Development Goals (SDGs) provide an integrated global action plan for sustainable development. However, it remains a great challenge to develop actionable strategies to achieve regional sustainability within social-environmental constraints. Here we proposed a framework, integrating safe and just operating space (SJOS) with SDGs, to assess regional sustainability and interactions between environmental performance and human well-being across scales. Despite China has not fully achieved sustainable development from 2000 to 2018, most provinces have shown significant improvements. Our analyses further delineated four development patterns (i.e., coupled and developed, coupled and underdeveloped, uncoupled and underdeveloped, and coupled and underdeveloped), and developed targeted strategies and pathways for each pattern to transition towards sustainability. Our operationalizable framework is broadly applicable to other regions or nations to actualize sustainable development.