{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:01:12Z","timestamp":1743102072149,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031746321"},{"type":"electronic","value":"9783031746338"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-74633-8_29","type":"book-chapter","created":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T23:20:40Z","timestamp":1735687240000},"page":"405-411","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detection and\u00a0Semantic Description of\u00a0Changes in\u00a0Earth Observation Time Series Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3587-4838","authenticated-orcid":false,"given":"Daniela F.","family":"Milon-Flores","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2246-6568","authenticated-orcid":false,"given":"Camille","family":"Bernard","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1398-7118","authenticated-orcid":false,"given":"J\u00e9r\u00f4me","family":"Gensel","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1825-8865","authenticated-orcid":false,"given":"Gregory","family":"Giuliani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,1]]},"reference":[{"key":"29_CR1","doi-asserted-by":"crossref","unstructured":"Appel, M., Pebesma, E.: On-demand processing of data cubes from satellite image collections with the gdalcubes library. In: Data 4.3 (2019)","DOI":"10.3390\/data4030092"},{"key":"29_CR2","unstructured":"Janowicz, K., Haller, A., Cox, S.: Semantic Sensor Network Ontology. W3C Recommendation. https:\/\/www.w3.org\/TR\/vocabssn\/. W3C (2017)"},{"key":"29_CR3","unstructured":"Baumann, P.: The Datacube Manifesto (2017)"},{"key":"29_CR4","doi-asserted-by":"crossref","unstructured":"Bernard, C., et al.: An ontology-based algorithm for managing the evolution of multi-level territorial partitions. In: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (2018)","DOI":"10.1145\/3274895.3274944"},{"key":"29_CR5","unstructured":"Brizhinev, D., et al.: Publishing and using Earth observation data with the RDF data cube and the discrete global grid system. In: W3C Working Group Note and OGC Discussion Paper W3C 20170928 (2017)"},{"key":"29_CR6","unstructured":"Camara, G.: On the semantics of big Earth observation data for land classification. arXiv preprint arXiv:2204.11082 (2022)"},{"key":"29_CR7","doi-asserted-by":"crossref","unstructured":"Costa, H., Giraldo, A., Caetano, M.: Exploring BFAST to detect forest changes in Portugal. In: Image and Signal Processing for Remote Sensing XXVI, Vol. 11533. SPIE (2020)","DOI":"10.1117\/12.2566669"},{"key":"29_CR8","doi-asserted-by":"crossref","unstructured":"Giuliani, G., et al.: Building an earth observations data cube: lessons learned from the swiss data cube (SDC) on generating analysis ready data (ARD). Big Earth Data 1(1-2), 100\u2013117 (2017)","DOI":"10.1080\/20964471.2017.1398903"},{"key":"29_CR9","unstructured":"Koubarakis,M., et al.: Linked earth observation data: the projects TELEIOS and LEO. In: Proceedings of the Linking Geospatial Data Conference (2014)"},{"key":"29_CR10","doi-asserted-by":"crossref","unstructured":"Lewis, A., et al.: The Australian geoscience data cube-foundations and lessons learned. Remote Sens. Environ. 202, 276\u2013292 (2017)","DOI":"10.1016\/j.rse.2017.03.015"},{"key":"29_CR11","doi-asserted-by":"crossref","unstructured":"Masili\u016bnas, D., et al.: BFAST Lite: a lightweight break detection method for time series analysis. Remote Sens. 13(16), 3308 (2021)","DOI":"10.3390\/rs13163308"},{"key":"29_CR12","doi-asserted-by":"crossref","unstructured":"Noel, D., et al.: Design patterns for modelling life trajectories in the semantic web (2017)","DOI":"10.1007\/978-3-319-55998-8_4"},{"key":"29_CR13","unstructured":"Reynolds, D., Cyganiak, R., Tennison,J.: The RDF Data Cube Vocabulary. W3C Recommendation. https:\/\/www.w3.org\/TR\/vocab-datacube\/. W3C (2014)"},{"key":"29_CR14","doi-asserted-by":"crossref","unstructured":"Tran, B.H., et al.: An approach for integrating earth observation, change detection and contextual data for semantic search. In: IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE (2020)","DOI":"10.1109\/IGARSS39084.2020.9324064"},{"key":"29_CR15","doi-asserted-by":"crossref","unstructured":"Tran, B.H., et al.: Semantic integration of raster data for earth observation: an RDF dataset of territorial unit versions with their land cover. ISPRS Int. J. Geo-Inf. 9(9), 503 (2020)","DOI":"10.3390\/ijgi9090503"},{"key":"29_CR16","doi-asserted-by":"crossref","unstructured":"Verbesselt, J., et al.: Detecting trend and seasonal changes in satellite image time series. Remote Sens. Environ. 114(1), 106\u2013115 (2010)","DOI":"10.1016\/j.rse.2009.08.014"},{"key":"29_CR17","doi-asserted-by":"crossref","unstructured":"Verbesselt, J., et al.: Phenological change detection while accounting for abrupt and gradual trends in satellite image time series. Remote Sens. Environ. 114(12), 2970\u20132980 (2010)","DOI":"10.1016\/j.rse.2010.08.003"},{"key":"29_CR18","doi-asserted-by":"crossref","unstructured":"Yang, Y., Wang, Y.: Using the BFAST algorithm and multitemporal AIRS data to investigate variation of atmospheric methane concentration over Zoige Wetland of China. Remote Sens. 12(19), 3199 (2020)","DOI":"10.3390\/rs12193199"},{"key":"29_CR19","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Woodcock, C.E.: Continuous change detection and classification of land cover using all available Landsat data. Remote Sens. Environ. 144, 152-171 (2014). issn: 0034-4257","DOI":"10.1016\/j.rse.2014.01.011"}],"container-title":["Communications in Computer and Information Science","Machine Learning and Principles and Practice of Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-74633-8_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,8]],"date-time":"2025-03-08T04:39:53Z","timestamp":1741408793000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-74633-8_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031746321","9783031746338"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-74633-8_29","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"1 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Turin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2023.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}