FPGAs (Field Programmable Gate Array) are an attractive technology for high-speed data processing in space missions due to their unbeatable flexibility and best performance-to-power ratio in comparison to software. However FPGAs suffer from 3 major drawbacks: (1) higher programming effort is required with respect to software; (2) hardware resources need to be allocated for each implemented function in contrast to software functions which can be executed on the same processing hardware; and (3) FPGAs are required to adopt radiation hardening techniques when deployed in a space environment. This paper presents a reconfigurable platform that demonstrates how modern FPGAs can be considered as computing resources like any other, suitable for emerging spatial applications and not subjected to the above-mentioned drawbacks. In particular, we show that large FPGAs can be split in different regions containing concurrently-running accelerators which can support the execution of a single or multiple applications. Then, in the same way as software-based multiprogrammed and multithreaded systems can dynamically create, schedule and execute threads, FPGA-based accelerators can be swapped in and out according to scheduling needs by exploiting their dynamic partial reconfiguration capability. A proof of concept cloud detection algorithm for Sentinel-2 multispectral images has been implemented and tested on our platform to validate the system's design principles and performance.