Recovery plans are key components of government-funded initiatives to halt biodiversity loss. Despite much discussion about the utility of remote sensing for effective conservation, the inclusion of these technologies in species recovery plans remains largely anecdotal. Here we developed a modelling approach for the integration of local, spatially-measured ecosystem functional dynamics into a species distribution modelling (SDM) framework in which other ecologically relevant factors are modelled separately at broad scales. We illustrate use of the approach by the incorporation of intra-seasonal water-vegetation dynamics into a cross-scale SDM for the Common Snipe (Gallinago gallinago). The Common Snipe is an Iberian grassland wader that is highly-dependent on water and vegetation dynamics, and the recovery plan for this wader in Galicia (NW Iberian Peninsula) provides an opportunity to apply our modelling approach. The intra-seasonal dynamics of water content of vegetation were measured using the standard deviation of Normalized Difference Water Index time series computed from bi-monthly images of the Sentinel-2 satellite. Our models, derived by the integration of downscaled climate projections with regional habitat-topographic suitability models, showed a very high predictive accuracy. Local water-vegetation dynamic models, based on Sentinel-2 imagery, also showed a good predictive ability. The predictive power increased (AUC of 0.92 and Boyce's index of 0.98) after local model predictions were restricted to areas identified by the continental and regional models as priority for conservation. Our models also showed high performance (AUC of 0.90 and Boyce's index of 0.93), when projected to updated water-vegetation conditions. This modelling framework (1) enables incorporation of key ecosystem processes closely related to water and carbon cycles, while accounting for other factors ecologically relevant to endangered grassland waders across different scales, (2) enables identification of priority areas for conservation, and (3) provides an excellent opportunity for cost-effective recovery planning by monitoring management effectiveness from space. Article impact statement: Incorporating remotely sensed ecosystem functioning variables, related to water and carbon cycles, informs recovery planning. This article is protected by copyright. All rights reserved.