{"id":"https://openalex.org/W2989414888","doi":"https://doi.org/10.1109/igarss.2019.8900205","title":"An Adaptable Approach for Pixel-Based Compositing and Crop Type/Tree Species Mapping","display_name":"An Adaptable Approach for Pixel-Based Compositing and Crop Type/Tree Species Mapping","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2989414888","doi":"https://doi.org/10.1109/igarss.2019.8900205","mag":"2989414888"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8900205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5072454390","display_name":"Sebastian Preidl","orcid":"https://orcid.org/0009-0001-3717-9628"},"institutions":[{"id":"https://openalex.org/I137479271","display_name":"Helmholtz Centre for Environmental Research","ror":"https://ror.org/000h6jb29","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I137479271"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Preidl","raw_affiliation_strings":["Helmholtz Centre for Environmental Research GmbH - UFZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz Centre for Environmental Research GmbH - UFZ","institution_ids":["https://openalex.org/I137479271"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034422087","display_name":"Maximilian Lange","orcid":"https://orcid.org/0000-0001-9657-8779"},"institutions":[{"id":"https://openalex.org/I137479271","display_name":"Helmholtz Centre for Environmental Research","ror":"https://ror.org/000h6jb29","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I137479271"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maximilian Lange","raw_affiliation_strings":["Helmholtz Centre for Environmental Research GmbH - UFZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz Centre for Environmental Research GmbH - UFZ","institution_ids":["https://openalex.org/I137479271"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079074963","display_name":"Daniel Doktor","orcid":"https://orcid.org/0000-0002-4761-3344"},"institutions":[{"id":"https://openalex.org/I137479271","display_name":"Helmholtz Centre for Environmental Research","ror":"https://ror.org/000h6jb29","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I137479271"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Doktor","raw_affiliation_strings":["Helmholtz Centre for Environmental Research GmbH - UFZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz Centre for Environmental Research GmbH - UFZ","institution_ids":["https://openalex.org/I137479271"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I137479271"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1942194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T10895","display_name":"Species Distribution and Climate Change","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compositing","display_name":"Compositing","score":0.7804132103919983},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6522600054740906},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6194370985031128},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6150993704795837},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5213569402694702},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5080924034118652},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4891131520271301},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44347190856933594},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.43507134914398193},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4134944975376129},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3994487524032593},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3627663850784302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.356631338596344},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27534985542297363},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2082822322845459},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18311411142349243},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.15029498934745789}],"concepts":[{"id":"https://openalex.org/C129315195","wikidata":"https://www.wikidata.org/wiki/Q1121886","display_name":"Compositing","level":3,"score":0.7804132103919983},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6522600054740906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6194370985031128},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6150993704795837},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5213569402694702},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5080924034118652},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4891131520271301},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44347190856933594},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.43507134914398193},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4134944975376129},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3994487524032593},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3627663850784302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.356631338596344},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27534985542297363},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2082822322845459},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18311411142349243},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.15029498934745789},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8900205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.7699999809265137,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1594031697","https://openalex.org/W2124723853","https://openalex.org/W2130811469","https://openalex.org/W2260274902","https://openalex.org/W2307094448","https://openalex.org/W2572348253","https://openalex.org/W2596615883","https://openalex.org/W2597284376","https://openalex.org/W2900217217","https://openalex.org/W3085162807","https://openalex.org/W6735132182"],"related_works":["https://openalex.org/W2605318953","https://openalex.org/W2098628853","https://openalex.org/W4242350840","https://openalex.org/W2363688420","https://openalex.org/W2044092692","https://openalex.org/W2614621130","https://openalex.org/W2547665164","https://openalex.org/W3103111272","https://openalex.org/W4289655544","https://openalex.org/W2046697080"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,76],"novel":[3],"approach":[4,68],"for":[5,64,75,99],"detailed":[6],"crop":[7,82],"type":[8],"and":[9],"tree":[10,101,107,124],"species":[11,102,108,125],"classification":[12,57,67,88],"exploiting":[13],"high":[14],"spatio-temporal":[15],"resolution":[16],"Sentinel-2A":[17],"data.":[18],"Here,":[19],"we":[20,84],"address":[21],"the":[22,56],"challenge":[23],"of":[24,48,90,115,132],"frequent":[25],"cloud":[26],"coverage":[27],"in":[28],"satellite":[29],"observations":[30],"by":[31],"defining,":[32],"purely":[33],"data":[34,63],"driven,":[35],"adaptable":[36,66],"time":[37,53],"periods":[38,54],"to":[39,122,127],"create":[40],"image":[41],"composites":[42,49],"from":[43,50],"training":[44],"pixels.":[45],"A":[46,104],"set":[47],"all":[51],"established":[52],"within":[55],"year":[58],"serve":[59],"as":[60],"multi-temporal":[61],"input":[62],"an":[65,86,111,112],"that":[69],"uses":[70],"multiple":[71],"random":[72],"forest":[73],"models":[74],"Germany-wide":[77],"pixel-based":[78],"land-use":[79],"classification.":[80],"For":[81],"types,":[83],"achieved":[85],"overall":[87,113],"accuracy":[89,114],"88.5":[91],"%.":[92,117],"The":[93,118],"same":[94],"method":[95],"will":[96],"be":[97],"applied":[98],"nationwide":[100],"mapping.":[103],"pre-study":[105],"on":[106],"identification":[109],"showed":[110],"74.7":[116],"map":[119],"was":[120],"used":[121],"define":[123],"composition":[126],"better":[128],"determing":[129],"conservation":[130],"status":[131],"forests.":[133]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}