Intelligent remote sensing and governmental environmental governance: A supply-side information capability perspective

Although digital technologies such as big data and artificial intelligence (AI) have been widely studied for their role in enhancing information processing, governance research has largely overlooked the more fundamental challenge of information generation. This study conceptualizes intelligent remote sensing (IRS) as a supply-side information capability—an institutionalized capacity for continuous, spatially comprehensive, and quality-screened environmental signal generation that can be embedded into governance routines. Using panel data from 31 Chinese provinces between 2012 and 2023, we construct novel indicators of IRS capability and governmental environmental governance performance (GovPerf). Empirical analyses show that IRS is positively associated with GovPerf through a detection-to-decision chain encompassing risk monitoring, information processing and risk management. In addition, AI capability acts as an absorptive capacity that strengthens the relationship between IRS and GovPerf. Heterogeneity analysis reveals that the governance value of IRS is conditional on institutional readiness, with weaker associations where institutional constraints limit the translation of sensing signals into enforcement and regulatory action. Overall, this study advances digital governance theory by shifting the focus from information use to information generation, highlighting the contextual nature of technological value in governance, and developing the transformation of remote sensing data into quantifiable management indicators. These insights provide both theoretical enrichment and practical guidance for improving environmental governance.