The preparation for next-generation Earth Observation missions, such as the European Space Agency’s (ESA) Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) and Land Surface Temperature Monitoring (LSTM), requires robust pre-launch proxy datasets. Because current simulation methodologies frequently rely on isolated, platform-specific approaches, this study proposes a comprehensive, unified multisensor framework capable of dynamically generating operationally realistic CHIME and LSTM datasets from diverse airborne and satellite sources. Three distinct processing pipelines were established. For hyperspectral data simulation, precursor satellite imagery (PRISMA and EnMAP) and high-resolution airborne measurements (HySpex) were harmonized to CHIME’s 30 m specifications utilizing Spectral Response Function (SRF) adjustments, Point Spread Function (PSF) spatial resampling, and 6S atmospheric radiative transfer modeling. For thermal data simulation, archive Landsat 8/9 and ASTER imagery were transformed into LSTM’s target 50 m, 5-band configuration using a synergistic two-step approach: a physics-based Spectral Super-Resolution (SSR) module followed by an AI-driven Spatial Super-Resolution (SpSR) transformer network. Evaluated across highly diverse inland, coastal, and riverine testbeds in Italy, the simulated products demonstrated high spectral, spatial, and radiometric fidelity. While inherently constrained by the native spectral ranges of the input sensors and by the current lack of absolute on-orbit mission data for validation, the downscaled images closely reproduced complex thermal patterns and water-quality gradients. Ultimately, this scalable framework provides the remote sensing community with early access to representative datasets and mission performance assessments, while accelerating pre-launch algorithm development and testing for environmental monitoring applications—particularly those focused on water discharges.

New Space is shifting satellites’ value to the actionable services they can deliver, and their potential for change in our approach to space. An agile mission design enhances data accessibility and innovation, adopting lower budgets and shorter schedules. In this paper we show that New Space entails sustainability for both the upstream and downstream elements of a space mission. We delved into the benefits that such a paradigm shift of space delivers to multi-dimensions of sustainability: economic, socioeconomic, and environmental. We assess how leaner satellite manufacturing allows the acceleration of design, development, and processes. Involving smaller actors and enlarging the horizons to unprecedented jobs deployment. Furthermore, New Space can reduce the environmental footprint of space activities. We demonstrate how Earth Observation (EO) data is transformed into added-value insight, and how it tackles the Sustainable Development Goals (SDGs). Thereby, this article promotes today’s sustainable contribution up to space, thus empowering the next generation to live in a greener future, stemming from space.