FORCE is intended to be an all-in-one solution for the mass-processing of selected medium-resolution satellite image archives to enable large area + time series applications. Currently supported are Landsat 4/5 TM, Landsat 7 ETM+, Landsat 8 OLI and Sentinel-2 A/B MSI. The software is capable of processing Level 1 products as obtained from the space agencies to Level 2–4 products.
FORCE may be used and downloaded for free; please fill out the form below to obtain a download link.
The main features are
- Integration of Landsat 4–8, and Sentinel-2 A/B as Virtual Constellation.
- Data management of Landsat and Sentinel-2 Level 1 data + Download of Sentinel-2 data.
- Near-realtime (NRT) processing capability.
- Generation of Analysis Ready Data (ARD). Advanced cloud and cloud shadow detection. Quality screening. Integrated atmospheric and topographic correction: one algorithm for all sensors. Adjacency effect correction. BRDF reduction. Resolution merge of Sentinel-2 bands: 20m à 10m. Data cubing: reprojection / gridding.
- Generation of highly Analysis Ready Data (hARD). Large area. Gap free. Best Available Pixel (BAP) composites. Phenology Adaptive Composites (PAC). Spectral Temporal Metrics (STM). Ideal input for your Machine Learners!
- Generation of highly Analysis Ready Data plus (hARD+). Time Series generation: spectral bands, spectral indices, Spectral Mixture Analysis (SMA). Time series folding. Time series interpolation. Time series statistics. Trend analysis. Change, Aftereffect, Trend (CAT) analysis. Land Surface Phenology (LSP).
- Detailed data mining of the Clear Sky Observation (CSO) availability.
- Data Fusion. Improving spatial resolution of coarse continuous fields: MODIS LSP à medium resolution LSP. Improving spatial resolution of lower resolution ARD using higher resolution ARD: 30m Landsat à 10m using Sentinel-2 targets
For further information about our General Data Protection, please click https://www.uni-trier.de/index.php?id=22091
D. Frantz, E. Haß, A. Uhl, J. Stoffels & J. Hill (2018): Improvement of the Fmask algorithm for Sentinel-2 images: Separating clouds from bright surfaces based on parallax effects. Remote Sensing of Environment, 215, 471-481. DOI
D. Frantz, A. Röder, M. Stellmes & J. Hill (2017): Phenology-adaptive pixel-based compositing using optical earth observation imagery. Remote Sensing of Environment, 190, 331-347. DOI
D. Frantz (2017). Generation of Higher Level Earth Observation Satellite Products for Regional Environmental Monitoring. Ph.D. dissertation. Faculty of Regional and Environmental Sciences, Trier University, Trier, Germany, p. 194. Online available
D. Frantz, A. Röder, M. Stellmes, and J. Hill (2016): An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications. IEEE Transactions on Geoscience and Remote Sensing, 54 (7): 3928-3943. DOI
D. Frantz, A. Röder, M. Stellmes, and J. Hill (2015): On the derivation of a spatially distributed aerosol climatology for its incorporation in a radiometric Landsat pre-processing framework.Remote Sensing Letters, 6 (8): 647-656. DOI
D. Frantz, A. Röder, T. Udelhoven & M. Schmidt (2015): Enhancing the Detectability of Clouds and Their Shadows in Multitemporal Dryland Landsat Imagery: Extending Fmask. IEEE Geoscience and Remote Sensing Letters, 12 (6): 1242–1246. DOI
D. Frantz, A. Röder, M. Stellmes, and J. Hill (2017): Phenology-adaptive pixel-based compositing using optical earth observation imagery.Remote Sensing of Environment, 190,331-347. DOI
D. Frantz, M. Stellmes, A. Röder, T. Udelhoven, S. Mader, and J. Hill (2016): Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs.IEEE Transactions on Geoscience and Remote Sensing, 54 (7): 4153-4164. DOI
Registration for FORCE download
FORCE is free software under the terms of the GNU General Public License v. >= 3. Please complete the form below to track the use of the service we are providing and to help improve our product. A download link will be sent to the e-mail address provided.