This dataset contains the data, documentation, and scripts that compose the SPATIAL SCALING CHALLENGE organized in the framework of the SENSECO COST Action CA17143 “Optical synergies for spatiotemporal SENsing of Scalable ECOphysiological traits” (https://www.senseco.eu/), by the Working Group 1. “Closing the scaling gap: from leaf measurements to satellite images” (https://www.senseco.eu/working-groups/wg1-scaling-gap/). The SPATIAL SCALING CHALLENGE is an open exercise where we challenge the remote sensing community to retrieve relevant vegetation biophysical and physiological variables such as leaf chlorophyll content (Cab), leaf area index (LAI), maximal carboxylation rate (Vcmax,25), and non-photochemical quenching (NPQ) from simulated (hyperspectral reflectance (HDRF), sun-induced chlorophyll fluorescence (F) and land surface temperature (LST)) imagery. The dataset contains the simulated remote sensing and field data, their description, and scripts in Matlab, Python, and R languages to facilitate importing and handling the data and producing the standardized outputs necessary to participate. IMPORTANT: Additional data that can be used at the discretion of the participants have been released in https://doi.org/10.5281/zenodo.6530187 The SPATIAL SCALING CHALLENGE aims at gathering the community’s expertise and knowledge to tackle the scaling problems posed by variables of different nature. These experiences will be summarized in a journal article where all the participants are invited to contribute. The exercise is internationally open. Ph.D. students, early career and senior researchers, spin-offs, and companies working in the field of remote sensing of vegetation ecophysiology are welcome to participate. STILL OPEN FOR PARTICIPATION! New deadline 31st of October 2022. Follow all the communications and updates of the SPATIAL SCALING CHALLENGE in the RG site: https://www.researchgate.net/project/Spatial-Scaling-Challenge-COST-Action-CA17134-SENSECO-Working-Group-1.