Data is the basis for the effective implementation of environmental policies. However, the traditional monitoring, reporting, and verification system (MRV) requires significant human and material resources and control over subjective data manipulation. Satellite data, or Big Data in general, can provide important complements with objective observations and much lower monitoring costs per polluting source, but their accuracy has not reached a level to replace the MRV system. This study established a theoretical model for integrating these informative yet imperfect data to screen for possible violations, and then using MRV or environmental inspections to target those suspicious polluters or regions for confirming environmental compliance statuses before issuing penalty. This integrated system can improve overall effectiveness and efficiency, making compliance more likely to become the norm. Based on this theory, this presentation will examine two case studies. The first one used carbon and nightlight satellite data to screen the attainment of China's CO2 mitigation goals at national and subnational levels in the 13th Five-Year Plan (2016-2020). Those provinces with poorer compliance could be targeted by the central government in environmental inspection. The second case adopted satellite SO2 vertical column density data to track the spatial and temporal patterns of compliance statuses with SO2 mitigation policies in coal-fired power plants since 2005. Furthermore, prominent features of China's environmental enforcement will also be discussed.