Understanding the net ecosystem productivity (NEP) is essential for understanding ecosystem functioning and the global carbon cycle. Utilizing meteorological and The Advanced Very High Resolution Radiometer (AVHRR) remote sensing data, this study employed the Carnegie–Ames–Stanford Approach (CASA) and the Geostatistical Model of Soil Respiration (GSMSR) to map a monthly vegetation NEP in China from 1982 to 2020. Then, we examined the spatiotemporal trends of NEP and identified the drivers of NEP changes using the Geodetector model. The mean NEP over the 39-year period amounted to 265.38 gC·m⁻². Additionally, the average annual carbon sequestration amounted to 1.89 PgC, indicating a large carbon sink effect. From 1982 to 2020, there was a general fluctuating increasing trend observed in the annual mean NEP, exhibiting an overall average growth rate of 4.69 gC·m⁻²·a⁻¹. The analysis revealed that the majority of the vegetation region in China, accounting for 93.45% of the entirety, exhibited increasing trends in NEP. According to the Geodetector analysis, precipitation change rate, solar radiation change rate, and altitude were the key driving factors in NEP change rate. Furthermore, the interaction between the precipitation change rate and altitude demonstrated the most significant effect.

Achieving equitable and harmonized socio-economic development is a vital gauge of national progress, particularly in geographically extensive nations such as China. This study, employing nighttime lights as a socio-economic development indicator and remote sensing vegetation indices, investigates spatial variations in wealth distribution across China’s eastern and western regions, delineated by the Hu Huanyong Line. It uncovers the balance between economic growth and green space preservation and discrepancies in development and green space allocation. A thorough county-level analysis using this nighttime light (NTL) and vegetation index exposes the dynamic shifts in socio-economic focal points. The Gini coefficient, assessing inequality and spatial autocorrelation within the index ratio, enriches our regional development understanding. The findings depict a heterogeneous yet rapid economic expansion, primarily within a 30 km coastal buffer zone. Despite a decrease in Gini coefficients in both eastern and western regions, the potential for inland development escalates as coastal illumination approaches saturation. This study unveils enduring, yet lessening, economic disparities between eastern and western China, underscoring the necessity for green preservation in eastern development plans. Moreover, inland regions emerge as potential areas for accelerated development. This study offers crucial insights for formulating balanced, sustainable regional development strategies in China.