{"id":"https://openalex.org/W3205364463","doi":"https://doi.org/10.1109/igarss47720.2021.9553309","title":"A Stochastic Model for InSAR Timeseries: Estimation and Propagation for Reduced Datasets","display_name":"A Stochastic Model for InSAR Timeseries: Estimation and Propagation for Reduced Datasets","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3205364463","doi":"https://doi.org/10.1109/igarss47720.2021.9553309","mag":"3205364463"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9553309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044490008","display_name":"Sami Samiei-Esfahany","orcid":"https://orcid.org/0000-0002-6575-8571"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]},{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR","NL"],"is_corresponding":true,"raw_author_name":"Sami Samiei-Esfahany","raw_affiliation_strings":["Currently at School of Surveying and Geospatial Engineering, University of Tehran, Iran","Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Currently at School of Surveying and Geospatial Engineering, University of Tehran, Iran","institution_ids":["https://openalex.org/I23946033"]},{"raw_affiliation_string":"Delft University of Technology, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005320261","display_name":"Freek van Leijen","orcid":"https://orcid.org/0000-0002-2582-9267"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Freek J. van Leijen","raw_affiliation_strings":["Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008872493","display_name":"Ramon F. Hanssen","orcid":"https://orcid.org/0000-0002-6067-7561"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ramon F. Hanssen","raw_affiliation_strings":["Delft University of Technology, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044490008"],"corresponding_institution_ids":["https://openalex.org/I23946033","https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.10842797,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3185","last_page":"3188"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interferometric-synthetic-aperture-radar","display_name":"Interferometric synthetic aperture radar","score":0.8409069776535034},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6732819080352783},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6391813158988953},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5654377341270447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5562559962272644},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5484030842781067},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.500389575958252},{"id":"https://openalex.org/keywords/propagation-of-uncertainty","display_name":"Propagation of uncertainty","score":0.45780420303344727},{"id":"https://openalex.org/keywords/stochastic-modelling","display_name":"Stochastic modelling","score":0.4457639753818512},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4315069913864136},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4300461411476135},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.42936185002326965},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3488638997077942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25932323932647705},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2537028193473816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2381625771522522},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18084195256233215},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16434752941131592},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09365320205688477}],"concepts":[{"id":"https://openalex.org/C22286887","wikidata":"https://www.wikidata.org/wiki/Q1666056","display_name":"Interferometric synthetic aperture radar","level":3,"score":0.8409069776535034},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6732819080352783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6391813158988953},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5654377341270447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5562559962272644},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5484030842781067},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.500389575958252},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.45780420303344727},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.4457639753818512},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4315069913864136},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4300461411476135},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.42936185002326965},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3488638997077942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25932323932647705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2537028193473816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2381625771522522},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18084195256233215},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16434752941131592},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09365320205688477},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9553309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2103826408","https://openalex.org/W2104193490"],"related_works":["https://openalex.org/W1983957588","https://openalex.org/W2258123186","https://openalex.org/W1987404909","https://openalex.org/W2921280830","https://openalex.org/W2887132723","https://openalex.org/W4311761947","https://openalex.org/W1992097434","https://openalex.org/W2756533552","https://openalex.org/W2163704724","https://openalex.org/W4282813214"],"abstract_inverted_index":{"The":[0,44],"main":[1],"objective":[2],"of":[3,30,46,72],"this":[4],"paper":[5],"is":[6,26,59,77],"to":[7,14,41],"develop":[8],"and":[9,57],"evaluate":[10],"a":[11,52,68],"pragmatic":[12],"approach":[13],"obtain":[15],"an":[16],"InSAR":[17,22,35],"stochastic":[18,32],"model":[19],"for":[20,79],"reduced":[21,42,53,80],"datasets.":[23,43,81],"This":[24,66],"goal":[25],"achieved":[27],"by":[28],"calculation":[29],"the":[31,38,62,73],"parameters":[33],"per":[34],"stack,":[36],"propagating":[37],"noise":[39],"structure":[40],"propagation":[45],"full":[47],"covariance":[48,75],"matrices":[49],"when":[50],"using":[51,61],"dataset":[54],"in":[55],"space":[56],"time":[58],"avoided,":[60],"derived":[63],"analytical":[64],"functions.":[65],"way,":[67],"computationally":[69],"efficient":[70],"approximation":[71],"exact":[74],"matrix":[76],"obtained":[78]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}