Farm surveys as the primary source of agricultural statistics are increasingly complemented by other data sources to provide a much richer picture of the situation of countries’ rural economy. This session explores how the integration of administrative registries, parcel-level spatial data, and satellite-based earth observation is redefining what national statistical systems can achieve even under extreme conditions. Presentations from Eurostat, Ukraine's Ministry of Economy, and the World Bank will examine the methodological foundations of this transition, with particular attention to EU frameworks such as the Statistics on Agricultural Input and Output (SAIO) regulation, the Land Parcel Identification System (LPIS), and the Earth Observation for Statistics (EO4S) initiative. Ukraine's wartime experience offers a uniquely demanding test case: with large territories inaccessible to conventional enumeration, multi-source data integration has shifted from a modernization aspiration to an operational necessity. World Bank research demonstrates that freely available Sentinel-2 imagery, combined with machine learning and panel econometric methods, can generate conflict damage indicators of greater spatial granularity than traditional sources. Together, the presentations make the case that pre-crisis investment in digital infrastructure and alignment with EU statistical standards is what makes agricultural data systems resilient — and ultimately, indispensable for recovery planning.