{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T18:33:31Z","timestamp":1768415611200,"version":"3.49.0"},"reference-count":77,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2024,10,11]],"date-time":"2024-10-11T00:00:00Z","timestamp":1728604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission LIFE Programme","doi-asserted-by":"publisher","award":["LIFE20 GIE\/GR\/001317"],"award-info":[{"award-number":["LIFE20 GIE\/GR\/001317"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, the need to protect and conserve biodiversity has become more critical than ever before, as a prerequisite for both sustainable development and the very survival of the human species. This has made it a priority for the scientific community to develop technological solutions that provide data and information for monitoring, directly or indirectly, biodiversity and the drivers of change. A new era of satellite earth observation upgrades the potential of Remote Sensing (RS) to support, at relatively low cost, but with high accuracy the extraction of information over large areas, at regular intervals, and over extended periods of time. Also, the recent development of the Earth Observation Data Cubes (EODC) framework facilitates EO data management and information extraction, enabling the mapping and monitoring of temporal and spatial patterns on the Earth\u2019s surface. This submission presents the ELBIOS EODC, specifically developed to support the biodiversity management and conservation over Greece. Based on the Open Data Cube (ODC) framework, it exploits multi-spectral optical Copernicus Sentinel-2 data and provides a series of Satellite Earth Observation (SEO) biodiversity products and spectral indices nationwide.<\/jats:p>","DOI":"10.3390\/rs16203771","type":"journal-article","created":{"date-parts":[[2024,10,11]],"date-time":"2024-10-11T08:10:16Z","timestamp":1728634216000},"page":"3771","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The EL-BIOS Earth Observation Data Cube for Supporting Biodiversity Monitoring in Greece"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5017-9371","authenticated-orcid":false,"given":"Vangelis","family":"Fotakidis","sequence":"first","affiliation":[{"name":"Laboratory of Photogrammetry and Remote Sensing (PERS Lab), School of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}]},{"given":"Themistoklis","family":"Roustanis","sequence":"additional","affiliation":[{"name":"Laboratory of Photogrammetry and Remote Sensing (PERS Lab), School of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6407-6205","authenticated-orcid":false,"given":"Konstantinos","family":"Panayiotou","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8611-3257","authenticated-orcid":false,"given":"Irene","family":"Chrysafis","sequence":"additional","affiliation":[{"name":"Laboratory of Photogrammetry and Remote Sensing (PERS Lab), School of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7725-6686","authenticated-orcid":false,"given":"Eleni","family":"Fitoka","sequence":"additional","affiliation":[{"name":"The Goulandris Natural History Museum\u2014Greek Biotope Wetland Centre (EKBY), 57001 Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7123-5358","authenticated-orcid":false,"given":"Giorgos","family":"Mallinis","sequence":"additional","affiliation":[{"name":"Laboratory of Photogrammetry and Remote Sensing (PERS Lab), School of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecoser.2014.12.007","article-title":"Exploring Connections among Nature, Biodiversity, Ecosystem Services, and Human Health and Well-Being: Opportunities to Enhance Health and Biodiversity Conservation","volume":"12","author":"Sandifer","year":"2015","journal-title":"Ecosyst. Serv."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1111\/padr.12283","article-title":"IPBES, 2019. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services","volume":"45","author":"Bongaarts","year":"2019","journal-title":"Popul. Dev. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4211","DOI":"10.1073\/pnas.1913007117","article-title":"Recent Responses to Climate Change Reveal the Drivers of Species Extinction and Survival","volume":"117","author":"Wiens","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","unstructured":"Levin, S.A. (2001). Resource Partitioning. Encyclopedia of Biodiversity, Academic Press. [2nd ed.]."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1126\/science.1257484","article-title":"A Mid-Term Analysis of Progress toward International Biodiversity Targets","volume":"346","author":"Tittensor","year":"2014","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1002\/rse2.4","article-title":"Earth Observation as a Tool for Tracking Progress towards the Aichi Biodiversity Targets","volume":"1","author":"Secades","year":"2015","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"110773","DOI":"10.1016\/j.ecolind.2023.110773","article-title":"Advancing Terrestrial Biodiversity Monitoring with Satellite Remote Sensing in the Context of the Kunming-Montreal Global Biodiversity Framework","volume":"154","author":"Timmermans","year":"2023","journal-title":"Ecol. Indic."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1007\/s10531-021-02216-5","article-title":"Remote Sensing of Biodiversity: What to Measure and Monitor from Space to Species?","volume":"30","author":"Reddy","year":"2021","journal-title":"Biodivers. Conserv."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1126\/science.1229931","article-title":"Essential Biodiversity Variables","volume":"339","author":"Pereira","year":"2013","journal-title":"Science"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1038\/523403a","article-title":"Environmental Science: Agree on Biodiversity Metrics to Track from Space","volume":"523","author":"Skidmore","year":"2015","journal-title":"Nature"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1002\/rse2.15","article-title":"Framing the Concept of Satellite Remote Sensing Essential Biodiversity Variables: Challenges and Future Directions","volume":"2","author":"Pettorelli","year":"2016","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kacic, P., and Kuenzer, C. (2022). Forest Biodiversity Monitoring Based on Remotely Sensed Spectral Diversity\u2014A Review. Remote Sens., 14.","DOI":"10.3390\/rs14215363"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.jnc.2018.06.004","article-title":"How to Include the Impact of Climate Change in the Extinction Risk Assessment of Policy Plant Species?","volume":"44","author":"Attorre","year":"2018","journal-title":"J. Nat. Conserv."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1007\/s11356-021-15702-8","article-title":"Impact of Climate Change on Biodiversity Loss: Global Evidence","volume":"29","author":"Habibullah","year":"2022","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"312","DOI":"10.46505\/IJBI.2021.3210","article-title":"Impact of climate change on aquatic ecosystem and its biodiversity: An overview","volume":"3","author":"Prakash","year":"2021","journal-title":"Int. J. Biol. Innov."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.future.2017.11.007","article-title":"A Versatile Data-Intensive Computing Platform for Information Retrieval from Big Geospatial Data","volume":"81","author":"Soille","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.rse.2011.09.022","article-title":"Landsat: Building a Strong Future","volume":"122","author":"Loveland","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.rse.2011.07.023","article-title":"ESA\u2019s Sentinel Missions in Support of Earth System Science","volume":"120","author":"Berger","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Giuliani, G., Camara, G., Killough, B., and Minchin, S. (2019). Earth Observation Open Science: Enhancing Reproducible Science Using Data Cubes. Data, 4.","DOI":"10.3390\/data4040147"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yao, X., Liu, Y., Cao, Q., Li, J., Huang, R., Woodcock, R., Paget, M., Wang, J., and Li, G. (2018, January 22\u201323). China Data Cube (CDC) for Big Earth Observation Data: Lessons Learned from the Design and Implementation. Proceedings of the BGDDS 2018\u20142018 International Workshop on Big Geospatial Data and Data Science, Wuhan, China.","DOI":"10.1109\/BGDDS.2018.8626825"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"691","DOI":"10.5194\/isprsarchives-XL-7-W3-691-2015","article-title":"Big Data Breaking Barriers\u2014First Steps on a Long Trail","volume":"XL-7-W3","author":"Schade","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1080\/17538947.2019.1585976","article-title":"Big Earth Data: Disruptive Changes in Earth Observation Data Management and Analysis?","volume":"13","author":"Sudmanns","year":"2020","journal-title":"Int. J. Digit. Earth"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2294","DOI":"10.1109\/JPROC.2019.2948454","article-title":"Remotely Sensed Big Data: Evolution in Model Development for Information Extraction [Point of View]","volume":"107","author":"Zhang","year":"2019","journal-title":"Proc. IEEE"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Camara, G., Assis, L.F., Ribeiro, G., Ferreira, K.R., Llapa, E., and Vinhas, L. (2016, January 31). Big Earth Observation Data Analytics: Matching Requirements to System Architectures. Proceedings of the 5th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, Burlingame, CA, USA.","DOI":"10.1145\/3006386.3006393"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1080\/17538947.2022.2115567","article-title":"Cloud-Based Storage and Computing for Remote Sensing Big Data: A Technical Review","volume":"15","author":"Xu","year":"2022","journal-title":"Int. J. Digit. Earth"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Appel, M., and Pebesma, E. (2019). On-Demand Processing of Data Cubes from Satellite Image Collections with the Gdalcubes Library. Data, 4.","DOI":"10.32614\/CRAN.package.gdalcubes"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.rse.2017.03.015","article-title":"The Australian Geoscience Data Cube\u2014Foundations and Lessons Learned","volume":"202","author":"Lewis","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Killough, B. (August, January 28). The Impact of Analysis Ready Data in the Africa Regional Data Cube. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898321"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1080\/20964471.2017.1398903","article-title":"Building an Earth Observations Data Cube: Lessons Learned from the Swiss Data Cube (SDC) on Generating Analysis Ready Data (ARD)","volume":"1","author":"Giuliani","year":"2017","journal-title":"Big Earth Data"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ferreira, K.R., Queiroz, G.R., Vinhas, L., Marujo, R.F.B., Simoes, R.E.O., Picoli, M.C.A., Camara, G., Cartaxo, R., Gomes, V.C.F., and Santos, L.A. (2020). Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. Remote Sens., 12.","DOI":"10.3390\/rs12244033"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Sudmanns, M., Augustin, H., van der Meer, L., Baraldi, A., and Tiede, D. (2021). The Austrian Semantic EO Data Cube Infrastructure. Remote Sens., 13.","DOI":"10.3390\/rs13234807"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/978-3-319-66562-7_7","article-title":"CDCol: A Geoscience Data Cube That Meets Colombian Needs","volume":"Volume 735","author":"Solano","year":"2017","journal-title":"Advances in Computing"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wagner, W., Bauer-Marschallinger, B., Navacchi, C., Reu\u00df, F., Cao, S., Reimer, C., Schramm, M., and Briese, C. (2021). A Sentinel-1 Backscatter Datacube for Global Land Monitoring Applications. Remote Sens., 13.","DOI":"10.3390\/rs13224622"},{"key":"ref_34","unstructured":"D\u00f6llner, J., Jobst, M., and Schmitz, P. (2019). Datacubes: Towards Space\/Time Analysis-Ready Data. Service-Oriented Mapping: Changing Paradigm in Map Production and Geoinformation Management, Springer International Publishing."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Giuliani, G., Mas\u00f3, J., Mazzetti, P., Nativi, S., and Zabala, A. (2019). Paving the Way to Increased Interoperability of Earth Observations Data Cubes. Data, 4.","DOI":"10.3390\/data4030113"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Killough, B. (2018, January 22\u201327). Overview of the Open Data Cube Initiative. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517694"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Dhu, T., Giuliani, G., Ju\u00e1rez, J., Kavvada, A., Killough, B., Merodio, P., Minchin, S., and Ramage, S. (2019). National Open Data Cubes and Their Contribution to Country-Level Development Policies and Practices. Data, 4.","DOI":"10.3390\/data4040144"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Wang, P., Woodcock, R., Taib, R., Paget, M., and Held, A. (2022). A Data Cube Architecture for Cloud-Based Earth Observation Analytics. Big Data Analytics in Earth, Atmospheric, and Ocean Sciences, American Geophysical Union (AGU).","DOI":"10.1002\/9781119467557.ch5"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1080\/20964471.2017.1402490","article-title":"Digital Earth Australia\u2014Unlocking New Value from Earth Observation Data","volume":"1","author":"Dhu","year":"2017","journal-title":"Big Earth Data"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1080\/20964471.2022.2099236","article-title":"Think Global, Cube Local: An Earth Observation Data Cube\u2019s Contribution to the Digital Earth Vision","volume":"7","author":"Sudmanns","year":"2023","journal-title":"Big Earth Data"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Maso, J., Zabala, A., Serral, I., and Pons, X. (2019). A Portal Offering Standard Visualization and Analysis on Top of an Open Data Cube for Sub-National Regions: The Catalan Data Cube Example. Data, 4.","DOI":"10.3390\/data4030096"},{"key":"ref_42","unstructured":"(2024, April 10). VMASC Virginia Data Cube. Available online: https:\/\/datacube.vmasc.org\/."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Fotakidis, V., Panayiotou, K., Fitoka, E., Roustanis, T., Chrysafis, I., Patias, P., Georgiadis, H., Botzorlos, V., and Mallinis, G. (2024, January 7\u201312). EL-BIOS Data Cube: National-Scale Biodiversity Monitoring in Greece Through EO Indicators. Proceedings of the IGARSS 2024\u20132024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece.","DOI":"10.1109\/IGARSS53475.2024.10641017"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1080\/17538947.2011.638500","article-title":"Digital Earth 2020: Towards the Vision for the next Decade","volume":"5","author":"Craglia","year":"2012","journal-title":"Int. J. Digit. Earth"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/17538947.2016.1264490","article-title":"Big Earth Data: A New Challenge and Opportunity for Digital Earth\u2019s Development","volume":"10","author":"Guo","year":"2017","journal-title":"Int. J. Digit. Earth"},{"key":"ref_46","first-page":"500","article-title":"EO-Based Indicators for Biodiversity Monitoring at National Scale in Greece: Framework Development for the Hellenic Biodiversity Information System (EL-BIOS)","volume":"Volume 13212","author":"Mallinis","year":"2024","journal-title":"Proceedings of the Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024)"},{"key":"ref_47","unstructured":"Legakis, A., and Maragos, P. (2009). The Red Book of Endangered Animals of Greece, Greek Zoological Society."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"De Jong, Y., Verbeek, M., Michelsen, V., Bj\u00f8rn, P.d.P., Los, W., Steeman, F., Bailly, N., Basire, C., Chylarecki, P., and Stloukal, E. (2014). Fauna Europaea\u2014All European Animal Species on the Web. Biodivers. Data J., 2.","DOI":"10.3897\/BDJ.2.e4034"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Legakis, A., Constantinidis, T., and Petrakis, P.V. (2018). Biodiversity in Greece. Global Biodiversity, Apple Academic Press.","DOI":"10.1201\/9780429487750-4"},{"key":"ref_50","unstructured":"Lee, W., McGlone, M., and Wright, E. (2005). Biodiversity Inventory and Monitoring: A Review of National and International Systems and a Proposed Framework for Future Biodiversity Monitoring by the Department of Conservation, Landcare Research New Zealand Ltd.. Landcare Research Contract Report LC0405\/122."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"e12025","DOI":"10.1002\/2688-8319.12025","article-title":"Implementing Integrated Measurements of Essential Biodiversity Variables at a National Scale","volume":"1","author":"Bellingham","year":"2020","journal-title":"Ecol. Solut. Evid."},{"key":"ref_52","first-page":"125","article-title":"Monitoring the Sustainable Intensification of Arable Agriculture: The Potential Role of Earth Observation","volume":"81","author":"Hunt","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.ecoser.2015.10.023","article-title":"An Indicator Framework for Assessing Ecosystem Services in Support of the EU Biodiversity Strategy to 2020","volume":"17","author":"Maes","year":"2016","journal-title":"Ecosyst. Serv."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"e32704","DOI":"10.3897\/oneeco.4.e32704","article-title":"Indicators for Mapping and Assessment of Ecosystem Condition and of the Ecosystem Service Habitat Maintenance in Support of the EU Biodiversity Strategy to 2020","volume":"4","author":"Hatziiordanou","year":"2019","journal-title":"One Ecosyst."},{"key":"ref_55","unstructured":"(2024, October 10). Open Data Cube Core. Available online: https:\/\/github.com\/opendatacube\/datacube-core."},{"key":"ref_56","unstructured":"(2024, April 13). Sentinel-2 Cloud-Optimized GeoTIFFs\u2014Registry of Open Data on AWS. Available online: https:\/\/registry.opendata.aws\/sentinel-2-l2a-cogs\/."},{"key":"ref_57","unstructured":"(2024, October 10). Datacube Open Web Services. Available online: https:\/\/github.com\/opendatacube\/datacube-ows."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"10","DOI":"10.5334\/jors.148","article-title":"Xarray: N-D Labeled Arrays and Datasets in Python","volume":"5","author":"Hoyer","year":"2017","journal-title":"J. Open Res. Softw."},{"key":"ref_59","first-page":"37","article-title":"Sen2Cor for Sentinel-2","volume":"Volume 10427","author":"Pflug","year":"2017","journal-title":"Image and Signal Processing for Remote Sensing XXIII"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"e453","DOI":"10.7717\/peerj.453","article-title":"Scikit-Image: Image Processing in Python","volume":"2","author":"Boulogne","year":"2014","journal-title":"PeerJ"},{"key":"ref_61","unstructured":"Krause, C., Dunn, B., and Bishop-Taylor, R. (2021). Digital Earth Australia Notebooks and Tools Repository, Geoscience Australia."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2018.12.011","article-title":"Development of a Sentinel-2 Burned Area Algorithm: Generation of a Small Fire Database for Sub-Saharan Africa","volume":"222","author":"Roteta","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2096","DOI":"10.1109\/TGRS.2012.2223475","article-title":"Monitoring Vegetation Dynamics Inferred by Satellite Data Using the PhenoSat Tool","volume":"51","author":"Rodrigues","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_64","first-page":"102862","article-title":"Assessing Land Surface Phenology in Araucaria-Nothofagus Forests in Chile with Landsat 8\/Sentinel-2 Time Series","volume":"112","author":"Kosczor","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_65","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_66","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A Simple Method for Reconstructing a High-Quality NDVI Time-Series Data Set Based on the Savitzky\u2013Golay Filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Zhao, A.-X., Tang, X.-J., Zhang, Z.-H., and Liu, J.-H. (2014, January 9\u201311). The Parameters Optimization Selection of Savitzky-Golay Filter and Its Application in Smoothing Pretreatment for FTIR Spectra. Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications, Hangzhou, China.","DOI":"10.1109\/ICIEA.2014.6931218"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Rocklin, M. (2015, January 6\u201312). Dask: Parallel Computation with Blocked Algorithms and Task Scheduling. Proceedings of the SciPy 2015, Austin, TX, USA.","DOI":"10.25080\/Majora-7b98e3ed-013"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.tree.2005.05.011","article-title":"Using the Satellite-Derived NDVI to Assess Ecological Responses to Environmental Change","volume":"20","author":"Pettorelli","year":"2005","journal-title":"Trends Ecol. Evol."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S0034-4257(01)00342-X","article-title":"Airborne Multispectral Data for Quantifying Leaf Area Index, Nitrogen Concentration, and Photosynthetic Efficiency in Agriculture","volume":"81","author":"Boegh","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.rse.2014.07.010","article-title":"A Physically Based Vegetation Index for Improved Monitoring of Plant Phenology","volume":"152","author":"Jin","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_72","unstructured":"Smets, B., Cai, Z., Eklundh, L., Tian, F., Bonte, K., Van Hoost, R., Van De Kerchove, R., Adriaensen, S., De Roo, B., and Jacobs, T. (2023). Copernicus Land Monitoring Service High Resolution Vegetation Phenology and Productivity (HR-VPP), User Manual, European Environment Agency."},{"key":"ref_73","unstructured":"(2024, September 03). Copernicus Emergency Management Service (\u00a9 2023 European Union). EMSR686. Available online: https:\/\/rapidmapping.emergency.copernicus.eu\/EMSR686."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, B., S\u00e1nchez-Ruiz, S., Campos-Taberner, M., Garc\u00eda-Haro, F.J., and Gilabert, M.A. (2022). Exploring Ecosystem Functioning in Spain with Gross and Net Primary Production Time Series. Remote Sens., 14.","DOI":"10.3390\/rs14061310"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Matas-Granados, L., Pizarro, M., Cayuela, L., Domingo, D., G\u00f3mez, D., and Garc\u00eda, M.B. (2022). Long-Term Monitoring of NDVI Changes by Remote Sensing to Assess the Vulnerability of Threatened Plants. Biol. Conserv., 265.","DOI":"10.1016\/j.biocon.2021.109428"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1038\/s41597-021-01076-6","article-title":"The Swiss Data Cube, Analysis Ready Data Archive Using Earth Observations of Switzerland","volume":"8","author":"Chatenoux","year":"2021","journal-title":"Sci. Data"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"118324","DOI":"10.1016\/j.jenvman.2023.118324","article-title":"MAES Implementation in Greece: Geodiversity","volume":"342","author":"Mallinis","year":"2023","journal-title":"J. Environ. 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