We revisit the international spillover effects of US monetary policy using a new nighttime light (NTL) big data as a high-frequency, granular proxy for real economic activity. By merging this data with firm-level and transaction-level datasets on land auction and bond issuance by Chinese firms, we find that an unexpected U.S. monetary tightening significantly reduces its output via a novel construction channel—across cities, NTL fluctuations are primarily driven by non-built-up areas rather than city centers or suburbs, suggesting construction-related activities as a main driver for U.S. monetary policy spillovers. Furthermore, the adverse effects on NTL of land parcels purchased by real estate developers are more pronounced for highly leveraged firms, those facing tighter liquidity constraints, and those with greater reliance on foreign bond financing. We show that such a pattern of NTL response to U.S. monetary policy tightening applies to other emerging economies.