{"id":"https://openalex.org/W2985358240","doi":"https://doi.org/10.1109/igarss.2019.8898926","title":"Remote Sensing For Assessing Drought Insurance Claims in Central Europe","display_name":"Remote Sensing For Assessing Drought Insurance Claims in Central Europe","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2985358240","doi":"https://doi.org/10.1109/igarss.2019.8898926","mag":"2985358240"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8898926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898926","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":"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/A5083100048","display_name":"Konrad Heidler","orcid":"https://orcid.org/0000-0001-8226-0727"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Konrad Heidler","raw_affiliation_strings":["Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054796189","display_name":"Arnaud Fietzke","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arnaud Fietzke","raw_affiliation_strings":["itestra GmbH, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"itestra GmbH, Munich, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2631,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61303953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"abs 1707 7321","issue":null,"first_page":"7306","last_page":"7309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11186","display_name":"Hydrology and Drought Analysis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9984999895095825,"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/T10930","display_name":"Flood Risk Assessment and Management","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/overfitting","display_name":"Overfitting","score":0.7905892133712769},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.6816772818565369},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6209280490875244},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5743821859359741},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4673405587673187},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4484536349773407},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4483923017978668},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4424991011619568},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.42701634764671326},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4189775586128235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41786086559295654},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.417577862739563},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3540268540382385},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.25491905212402344},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.23544061183929443},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10406273603439331}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7905892133712769},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.6816772818565369},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6209280490875244},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5743821859359741},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4673405587673187},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4484536349773407},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4483923017978668},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4424991011619568},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.42701634764671326},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4189775586128235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41786086559295654},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.417577862739563},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3540268540382385},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.25491905212402344},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.23544061183929443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10406273603439331},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8898926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898926","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":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1978617972","https://openalex.org/W1995029758","https://openalex.org/W2012300893","https://openalex.org/W2029316659","https://openalex.org/W2159979951","https://openalex.org/W2253154013","https://openalex.org/W2288074780","https://openalex.org/W2725897987","https://openalex.org/W2738657266","https://openalex.org/W2883477750","https://openalex.org/W2890175609","https://openalex.org/W2898227265","https://openalex.org/W6696429117","https://openalex.org/W6741291971","https://openalex.org/W6755712434"],"related_works":["https://openalex.org/W2393964553","https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856"],"abstract_inverted_index":{"In":[0],"this":[1,85],"study,":[2],"the":[3,21,28,62,67,75,87,112,119,125],"viability":[4],"of":[5,17,77],"assessing":[6],"drought":[7],"insurance":[8],"claims":[9],"via":[10],"remote":[11],"sensing":[12],"is":[13,81],"explored.":[14],"Time":[15],"series":[16,64],"satellite":[18],"images":[19],"from":[20,27,43],"Sentinel-2":[22],"mission":[23],"and":[24,65],"weather":[25],"data":[26,42,68],"European":[29],"Climate":[30],"Assessment":[31],"&":[32],"Dataset":[33],"are":[34,53],"used":[35],"to":[36,58,69,73,107,111,116],"fit":[37],"classifiers":[38,52],"on":[39,61,127],"historical":[40],"loss":[41],"an":[44],"agricultural":[45],"insurance.":[46],"Two":[47],"different":[48],"approaches":[49],"for":[50,123],"training":[51],"explored,":[54],"designing":[55],"neural":[56,113],"networks":[57],"learn":[59],"directly":[60],"time":[63],"transforming":[66],"a":[70,128,138],"fixed-size":[71],"representation":[72],"enable":[74],"use":[76],"other":[78],"methods.":[79],"It":[80],"shown":[82],"that":[83],"in":[84],"case":[86],"second":[88],"approach":[89],"yields":[90],"much":[91],"better":[92],"results,":[93],"as":[94],"careful":[95],"feature":[96],"engineering":[97],"combined":[98],"with":[99],"more":[100],"rigid":[101],"methods":[102,121],"like":[103],"gradient":[104],"boosting":[105],"leads":[106],"less":[108],"overfitting":[109],"compared":[110],"network":[114],"approach.Compared":[115],"existing":[117],"approaches,":[118],"proposed":[120],"allow":[122],"analyzing":[124],"situation":[126],"per-field":[129],"level":[130],"while":[131],"using":[132],"high":[133],"resolution":[134],"imagery":[135],"(Sentinel-2)":[136],"over":[137],"large":[139],"geographic":[140],"area.":[141]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
