Conservation planning and action critically relies on information about dynamics in ecosystems, habitats, and species’ populations in order to define baselines, set conservation targets, and to identify areas for protection and restoration activities. Following the opening of the Landsat archives, remote sensing became a key technology for providing information to conservation, but many world regions experienced widespread changes in habitats and species populations prior to the Landsat history (1980s). In EcoSpy we propose to pioneer the broad-scale use of recently declassified historical, global, high-resolution spy satellite photographs from the Cold War era (Corona) to extend the temporal scale of ecological and conservation remote sensing studies as far back as the 1960s. We will integrate Corona with Landsat and GoogleEarth Images in three proof-of-concept studies to test the usability of Corona for conservation research and applications. We will assess changes in (1) ecosystems of conservation concern, by identifying long-undisturbed forests and their fragmentation in Romania, (2) endangered species habitats, by analyzing saiga antelope habitat in Kazakhstan, and (3) keystone species’ population dynamics, by analyzing population density of steppe marmots in Kazakhstan. Additionally, we will carry out a synthesis study on uses and benefits of Corona imagery for ecology and conservation worldwide. EcoSpy is deeply interdisciplinary, located at the intersection of ecology, conservation science and remote sensing. Scientifically, EcoSpy will enhance the long-term understanding of ecological processes such as fragmentation, range shifts and population dynamics, and will extend availability of high resolution remotely sensed data by two decades prior to Landsat. EcoSpy will inform conservation action such as identifying priority conservation areas and defining conservation baselines for vulnerable habitats and species, advancing conservation and ecology worldwide.