{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T20:06:08Z","timestamp":1779134768553,"version":"3.51.4"},"reference-count":60,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T00:00:00Z","timestamp":1648598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Federal Ministry of Education and Research","doi-asserted-by":"publisher","award":["031B0516F"],"award-info":[{"award-number":["031B0516F"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Grasslands cover one-third of the agricultural area in Germany and play an important economic role by providing fodder for livestock. In addition, they fulfill important ecosystem services, such as carbon storage, water purification, and the provision of habitats. These ecosystem services usually depend on the grassland management. In central Europe, grasslands are grazed and\/or mown, whereby the management type and intensity vary in space and time. Spatial information on the mowing timing and frequency on larger scales are usually not available but would be required in order to assess the ecosystem services, species composition, and grassland yields. Time series of high-resolution satellite remote sensing data can be used to analyze the temporal and spatial dynamics of grasslands. Within this study, we aim to overcome the drawbacks identified by previous studies, such as optical data availability and the lack of comprehensive reference data, by testing the time series of various Sentinel-2 (S2) and Sentinal-1 (S1) parameters and combinations of them in order to detect mowing events in Germany in 2019. We developed a threshold-based algorithm by using information from a comprehensive reference dataset of heterogeneously managed grassland parcels in Germany, obtained by RGB cameras. The developed approach using the enhanced vegetation index (EVI) derived from S2 led to a successful mowing event detection in Germany (60.3% of mowing events detected, F1-Score = 0.64). However, events shortly before, during, or shortly after cloud gaps were missed and in regions with lower S2 orbit coverage fewer mowing events were detected. Therefore, S1-based backscatter, InSAR, and PolSAR features were investigated during S2 data gaps. From these, the PolSAR entropy detected mowing events most reliably. For a focus region, we tested an integrated approach by combining S2 and S1 parameters. This approach detected additional mowing events, but also led to many false positive events, resulting in a reduction in the F1-Score (from 0.65 of S2 to 0.61 of S2 + S1 for the focus region). According to our analysis, a majority of grasslands in Germany are only mown zero to two times (around 84%) and are probably additionally used for grazing. A small proportion is mown more often than four times (3%). Regions with a generally higher grassland mowing frequency are located in southern, south-eastern, and northern Germany.<\/jats:p>","DOI":"10.3390\/rs14071647","type":"journal-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T21:28:39Z","timestamp":1648675719000},"page":"1647","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Detection of Grassland Mowing Events for Germany by Combining Sentinel-1 and Sentinel-2 Time Series"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8950-1746","authenticated-orcid":false,"given":"Sophie","family":"Reinermann","sequence":"first","affiliation":[{"name":"Department of Remote Sensing, Institute of Geography and Geology, University of W\u00fcrzburg, 97074 Wuerzburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ursula","family":"Gessner","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center (DFD), Earth Observation Center (EOC), German Aerospace Center (DLR), 82234 Wessling, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7302-6813","authenticated-orcid":false,"given":"Sarah","family":"Asam","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center (DFD), Earth Observation Center (EOC), German Aerospace Center (DLR), 82234 Wessling, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6626-3052","authenticated-orcid":false,"given":"Tobias","family":"Ullmann","sequence":"additional","affiliation":[{"name":"Department of Physical Geography, Institute of Geography and Geology, University of W\u00fcrzburg, 97074 Wuerzburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anne","family":"Schucknecht","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research\u2014Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Claudia","family":"Kuenzer","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Institute of Geography and Geology, University of W\u00fcrzburg, 97074 Wuerzburg, Germany"},{"name":"German Remote Sensing Data Center (DFD), Earth Observation Center (EOC), German Aerospace Center (DLR), 82234 Wessling, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,30]]},"reference":[{"key":"ref_1","unstructured":"Reynolds, S., and Frame, J. (2005). Grasslands: Developments, Opportunities, Perspectives, Food & Agriculture Organization."},{"key":"ref_2","unstructured":"White, R.P., Murray, S., and Rohweder, M. (2000). Pilot Analysis of Global Ecosystems\u2014Grassland Ecosystems, World Resources Institute."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e02582","DOI":"10.1002\/ecs2.2582","article-title":"Grasslands-more important for ecosystem services than you might think","volume":"10","author":"Bengtsson","year":"2019","journal-title":"Ecosphere"},{"key":"ref_4","unstructured":"Schoof, N., Luick, R., Ackermann, A., Baum, S., B\u00f6hner, H., R\u00f6der, N., Rudolph, S., Schmidt, T.G., H\u00f6tker, H., and Jeromin, H. (2020). Auswirkungen der Neuen Rahmenbedingungen der Gemeinsamen Agrarpolitik Auf Die Gr\u00fcnland-Bezogene Biodiversit\u00e4t, Bundesamt f\u00fcr Naturschutz. [2nd ed.]. BfN-Skripten."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1002\/jpln.202000113","article-title":"Stocks of organic carbon in German agricultural soils\u2014Key results of the first comprehensive inventory","volume":"183","author":"Poeplau","year":"2020","journal-title":"J. Plant Nutr. Soil Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agee.2013.12.015","article-title":"Biodiversity of Palaearctic grasslands: A synthesis","volume":"182","author":"Dengler","year":"2014","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1111\/1365-2435.12850","article-title":"Mowing exacerbates the loss of ecosystem stability under nitrogen enrichment in a temperate grassland","volume":"31","author":"Zhang","year":"2017","journal-title":"Funct. Ecol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1111\/avsc.12365","article-title":"Annual mowing maintains plant diversity in threatened temperate grasslands","volume":"21","author":"Smith","year":"2018","journal-title":"Appl. Veg. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1111\/j.1365-2664.2011.01968.x","article-title":"Explaining grassland biomass\u2013the contribution of climate, species and functional diversity depends on fertilization and mowing frequency","volume":"48","author":"Sperlich","year":"2011","journal-title":"J. Appl. Ecol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"103701","DOI":"10.1016\/j.apsoil.2020.103701","article-title":"Management of grasslands by mowing versus grazing\u2014impacts on soil organic matter quality and microbial functioning","volume":"156","author":"Gilmullina","year":"2020","journal-title":"Appl. Soil Ecol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1080\/17583004.2014.912863","article-title":"Net carbon storage measured in a mowed and grazed temperate sown grassland shows potential for carbon sequestration under grazed system","volume":"5","author":"Senapati","year":"2014","journal-title":"Carbon Manag."},{"key":"ref_12","unstructured":"Schoof, N., Luick, R., Beaufoy, G., Jones, G., Einarsson, P., Ruiz, J., Stefanova, V., Fuchs, D., Windmai\u00dfer, T., and H\u00f6tker, H. (2020). Gr\u00fcnlandschutz in Deutschland: Treiber der Biodiversit\u00e4t, Einfluss von Agrarumwelt-und Klimama\u00dfnahmen, Ordnungsrecht, Molkereiwirtschaft und Auswirkungen der Klima-und Energiepolitik, Bundesamt f\u00fcr Naturschutz. [2nd ed.]. BfN-Skripten."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1111\/j.1365-2745.2012.02020.x","article-title":"Direct and productivity-mediated indirect effects of fertilization, mowing and grazing on grassland species richness","volume":"100","author":"Socher","year":"2012","journal-title":"J. Ecol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3729","DOI":"10.1007\/s10531-018-1623-x","article-title":"Decline of rare and specialist species across multiple taxonomic groups after grassland intensification and abandonment","volume":"27","author":"Hilpold","year":"2018","journal-title":"Biodivers. Conserv."},{"key":"ref_15","unstructured":"(2013). European Commission Regulation (EU) No 1305\/2013 of the European Parliament and of the Council of 17 December 2013 on support for rural development by the European Agricultural Fund for Rural Development (EAFRD) and repealing Council Regulation (EC) No 1698\/2005. Off. J. Eur. Union L, 347, 487\u2013548."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Reinermann, S., Asam, S., and Kuenzer, C. (2020). Remote Sensing of Grassland Production and Management\u2014A Review. Remote Sens., 12.","DOI":"10.3390\/rs12121949"},{"key":"ref_17","first-page":"112795","article-title":"Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series","volume":"9","author":"Schwieder","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1731","DOI":"10.5194\/hess-14-1731-2010","article-title":"Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region","volume":"14","author":"Courault","year":"2010","journal-title":"Hydrol. Earth Syst. Sci. Discuss."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kolecka, N., Ginzler, C., Pazur, R., Price, B., and Verburg, P.H. (2018). Regional Scale Mapping of Grassland Mowing Frequency with Sentinel-2 Time Series. Remote Sens., 10.","DOI":"10.3390\/rs10081221"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"111124","DOI":"10.1016\/j.rse.2019.03.017","article-title":"Towards national-scale characterization of grassland use intensity from integrated Sentinel-2 and Landsat time series","volume":"238","author":"Griffiths","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1308","DOI":"10.3390\/rs3071308","article-title":"Towards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter","volume":"3","author":"Schuster","year":"2011","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"15","DOI":"10.5194\/isprsarchives-XL-7-W3-15-2015","article-title":"Satellite-based assessment of grassland yields","volume":"40","author":"Grant","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Taravat, A., Wagner, M.P., and Oppelt, N. (2019). Automatic Grassland Cutting Status Detection in the Context of Spatiotemporal Sentinel-1 Imagery Analysis and Artificial Neural Networks. Remote Sens., 11.","DOI":"10.3390\/rs11060711"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"De Vroey, M., Radoux, J., and Defourny, P. (2021). Grassland Mowing Detection Using Sentinel-1 Time Series: Potential and Limitations. Remote Sens., 13.","DOI":"10.3390\/rs13030348"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"8081","DOI":"10.1080\/01431161.2013.829593","article-title":"Towards a detection of grassland cutting practices with dual polarimetric TerraSAR-X data","volume":"34","author":"Voormansik","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zalite, K., Voormansik, K., Praks, J., Antropov, O., and Noorma, M. (2014). Towards Detecting Mowing of Agricultural Grasslands from Multi-Temporal COSMO-SkyMed Data, IEEE Geoscience and Remote Sensing Symposium.","DOI":"10.1109\/IGARSS.2014.6947638"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3687","DOI":"10.1109\/JSTARS.2015.2478120","article-title":"Monitoring of agricultural grasslands with time series of X-band repeat-pass interferometric SAR","volume":"9","author":"Zalite","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1109\/JSTARS.2015.2503773","article-title":"Observations of cutting practices in agricultural grasslands using polarimetric SAR","volume":"9","author":"Voormansik","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3225","DOI":"10.1109\/JSTARS.2017.2679761","article-title":"Application of Repeat-Pass TerraSAR-X staring spotlight interferometric coherence to monitor pasture biophysical parameters: Limitations and sensitivity analysis","volume":"10","author":"Ali","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Tamm, T., Zalite, K., Voormansik, K., and Talgre, L. (2016). Relating Sentinel-1 interferometric coherence to mowing events on grasslands. Remote Sens., 8.","DOI":"10.3390\/rs8100802"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Voormansik, K., Zalite, K., S\u00fcnter, I., Tamm, T., Koppel, K., Verro, T., Brauns, A., Jakovels, D., and Praks, J. (2020). Separability of Mowing and Ploughing Events on Short Temporal Baseline Sentinel-1 Coherence Time Series. Remote Sens., 12.","DOI":"10.3390\/rs12223784"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Stendardi, L., Karlsen, S.R., Niedrist, G., Gerdol, R., Zebisch, M., Rossi, M., and Notarnicola, C. (2019). Exploiting Time Series of Sentinel-1 and Sentinel-2 Imagery to Detect Meadow Phenology in Mountain Regions. Remote Sens., 11.","DOI":"10.3390\/rs11050542"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"112751","DOI":"10.1016\/j.rse.2021.112751","article-title":"Mowing event detection in permanent grasslands: Systematic evaluation of input features from Sentinel-1, Sentinel-2, and Landsat 8 time series","volume":"267","author":"Lobert","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_34","first-page":"349","article-title":"Wirtschaftsgr\u00fcnland","volume":"Volume 94","author":"Kollmann","year":"2019","journal-title":"Renaturierungs\u00f6kologie"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1007\/s11258-016-0607-8","article-title":"Temporal and small-scale spatial variation in grassland productivity, biomass quality, and nutrient limitation","volume":"217","author":"Klaus","year":"2016","journal-title":"Plant Ecol."},{"key":"ref_36","unstructured":"(2019, April 01). Copernicus High Resolution Layer\u2014Grassland 2018. Available online: https:\/\/land.copernicus.eu\/pan-european\/high-resolution-layers\/grassland\/status-maps\/grassland-2018."},{"key":"ref_37","unstructured":"Koeppen, W., and Geiger, R. (1936). Das geographische System der Klimate. Handbuch der Klimatologie, Gebrueder Borntraeger."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"180060","DOI":"10.2136\/vzj2018.03.0060","article-title":"The TERENO Pre-Alpine Observatory: Integrating Meteorological, Hydrological, and Biogeochemical Measurements and Modeling","volume":"17","author":"Kiese","year":"2018","journal-title":"Vadose Zone J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","article-title":"A systematic analysis of performance measures for classification tasks","volume":"45","author":"Sokolova","year":"2009","journal-title":"Inf. Processing Manag."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s Optical High-Resolution Mission for GMES Operational Services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"GMES Sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_42","unstructured":"Hagolle, O., Huc, M., Desjardins, C., Auer, S., and Richter, R. (2022, March 01). Maja Algorithm Theoretical Basis Document; V1.0. Available online: https:\/\/zenodo.org\/record\/1209633#.YkFuyvlByUk."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and Differentiation of Data by Simplified Least Squares Procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_45","unstructured":"(2022, February 08). Copernicus EU-DEM: v1.1 2016. Available online: https:\/\/land.copernicus.eu\/imagery-in-situ\/eu-dem\/eu-dem-v1.1."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.isprsjprs.2015.01.007","article-title":"The Kennaugh element framework for multi-scale, multi-polarized, multi-temporal and multi-frequency SAR image preparation","volume":"102","author":"Schmitt","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Ullmann, T., Banks, S.N., Schmitt, A., and Jagdhuber, T. (2017). Scattering Characteristics of X-, C- and L-Band PolSAR Data Examined for the Tundra Environment of the Tuktoyaktuk Peninsula, Canada. Appl. Sci., 7.","DOI":"10.3390\/app7060595"},{"key":"ref_48","first-page":"2","article-title":"The dual polarization entropy\/alpha decomposition: A PALSAR case study","volume":"644","author":"Cloude","year":"2007","journal-title":"Sci. Appl. SAR Polarim. Polarim. Interferom."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"L\u00f6w, J., Ullmann, T., and Conrad, C. (2021). The Impact of Phenological Developments on Interferometric and Polarimetric Crop Signatures Derived from Sentinel-1: Examples from the DEMMIN Study Site (Germany). Remote Sens., 13.","DOI":"10.3390\/rs13152951"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1127\/zfg_suppl\/2019\/0524","article-title":"Data Processing, Feature Extraction, and Time-Series Analysis of Sentinel-1 Synthetic Aperture Radar (SAR) Imagery: Examples from Damghan and Bajestan Playa (Iran)","volume":"62","author":"Ullmann","year":"2019","journal-title":"Z. Geomorphol. Suppl. Issues"},{"key":"ref_51","first-page":"1","article-title":"Change detection using high resolution TerraSAR-X data: Preliminary results","volume":"38","author":"Scheuchl","year":"2009","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Others Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/36.739146","article-title":"Coherence estimation for SAR imagery","volume":"37","author":"Touzi","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","unstructured":"(2020). Deutschland\u2014Klimaregionen 2021. Diercke Weltatlas, Westermann Bildungsmedien Verlag GmbH."},{"key":"ref_55","unstructured":"Grant, K., Wagner, M., Siegmund, R., and Hartmann, S. (2015, January 14\u201317). The use of radar images for detecting when grass is harvested and thereby improve grassland yield estimates: Grassland Science in Europe, Grassland and Forages in High Output Dairy Farming Systems. Proceedings of the Grassland Science in Europe, Grassland Science Federation, Wageningen, The Netherlands."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"525","DOI":"10.5589\/m03-069","article-title":"The application of C-band polarimetric SAR for agriculture: A review","volume":"30","author":"McNairn","year":"2004","journal-title":"Can. J. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/36.551930","article-title":"Retrieval of vegetation parameters with SAR interferometry","volume":"35","author":"Wegmuller","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","unstructured":"(2021, December 04). Annual Precipitation Germany 2020, German Weather Service (DWD). Available online: https:\/\/www.dwd.de\/DE\/leistungen\/klimakartendeutschland\/klimakartendeutschland.html?nn=16102."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.rse.2017.06.003","article-title":"Determination of grassland use intensity based on multi-temporal remote sensing data and ecological indicators","volume":"198","author":"Peruta","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1080\/22797254.2019.1596757","article-title":"Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps","volume":"53","author":"Manakos","year":"2020","journal-title":"Eur. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1647\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:46:19Z","timestamp":1760136379000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1647"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,30]]},"references-count":60,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071647"],"URL":"https:\/\/doi.org\/10.3390\/rs14071647","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,30]]}}}