# FORCE--Landsat + Sentinel-2 Analysis Ready Data and Beyond
## 6 Outlook  
Several improvements and new features are being developed or are planned to be implemented. FORCE is open source software, and as such, external contributions are welcome. The Level 2 Processing System is currently undergoing a major overhaul to run more efficiently on weak RAM machines (e.g., common High Performance Computing (HPC) setups). Thus, memory requirements are reduced, and multithreading is implemented. Both will allow hybrid parallelization and thus  
Figure 13: Landsat ARD at original 30 m resolution (**top**), and Landsat ARD with improved spatial resolution at 10 m (**bottom**) for image subsets from North Rhine Westphalia, Germany. Using the FORCE L2 IMP module, the spatial resolution was enhanced using multi-temporal Sentinel-2 A/B prediction targets.  
enable improved flexibility with regards to different hardware architectures. As the Sentinel-2 Global Reference Image for improving geolocation accuracy [70] is still not available, and as ESA has not committed on reprocessing the available archive upon its completion, co-registration functionality is currently being implemented [71]. After having participated in the Atmospheric Correction Inter-comparison Exercise (ACIX) [38], FORCE will undergo further validation and testing in ACIX II, and the accompanying Cloud Masking Inter-comparison Exercise (CMIX) [72]. In order to support coastal aquatic applications [73], the option to output the coastal aerosol band of Landsat 8 and Sentinel-2 will be included. It is planned to implement support for Sentinel-1 data in the higher-level FORCE modules, which will need to be pre-processed similarly to the optical FORCE ARD; a fully integrated Level 2-like preprocessing tool is currently not planned by the developer, but could be contributed by interested third parties. The higher-level FORCE modules are often I/O-bound, thus measures are currently implemented to continuously pre-load data, which will reduce idle CPU times due to sequential reading-processing-writing cycles. Several software utilities are currently developed at the Earth Observation Lab, Humboldt-Universitat zu Berlin: The QGIS plugins 'EO Time Series Viewer' [74], 'Raster Time Series Manager' [75], and 'Raster Data Plotting' [76] are being developed for visualizing mass remote sensing data at spatial, temporal, and spectral scales, and thus facilitate exploring data generated by FORCE.  
The development of FORCE was supported by the Bundesministerium fur Bildung und Forschung under grant number FKZ-01 LG1201C (Southern African Science Service Centre for Climate Change and Adaptive Land Management Project: SASSCAL), the Bundesministerium fur Verkehr und Digitale Infrastruktur under grant number FKZ-50 SFW1605 (Sentinel4 GRIPS), and Geo.X, the Research Network for Geosciences in Berlin and Potsdam under grant number SO.087. Geox (Near-Real Time Derivation of Land Surface Phenology using Sentinel Data: FORCE-NRT). Current development is supported by the European Research Council, grant number 741950 (Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society: MAT_STOCKS). The APC was funded by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universitat zu Berlin.  
Thanks to ESA, USGS, and NASA for free and open access to Sentinel, Landsat, and MODIS data. Thanks to [PERSON], [PERSON] and [PERSON] for providing feedback on the article. I want to thank the three anonymous reviewers for their constructive feedback that greatly improved the quality of this manuscript.  
The author declares no conflict of interest.