{"id":"https://openalex.org/W2760609732","doi":"https://doi.org/10.1109/agro-geoinformatics.2017.8047071","title":"CST, a freeware for predicting crop yield from remote sensing or crop model indicators: Illustration with RSA and Ethiopia","display_name":"CST, a freeware for predicting crop yield from remote sensing or crop model indicators: Illustration with RSA and Ethiopia","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2760609732","doi":"https://doi.org/10.1109/agro-geoinformatics.2017.8047071","mag":"2760609732"},"language":"en","primary_location":{"id":"doi:10.1109/agro-geoinformatics.2017.8047071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/agro-geoinformatics.2017.8047071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 6th International Conference on Agro-Geoinformatics","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/A5027546688","display_name":"Herv\u00e9 Kerdiles","orcid":"https://orcid.org/0000-0002-0306-2405"},"institutions":[{"id":"https://openalex.org/I4210118689","display_name":"Joint Research Centre","ror":"https://ror.org/02qezmz13","country_code":"IT","type":"government","lineage":["https://openalex.org/I1320481043","https://openalex.org/I2800387288","https://openalex.org/I4210118689","https://openalex.org/I4210161702"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"H. Kerdiles","raw_affiliation_strings":["Food Security Unit, Joint Research Centre of the European Commission, Ispra, VA, Italy"],"affiliations":[{"raw_affiliation_string":"Food Security Unit, Joint Research Centre of the European Commission, Ispra, VA, Italy","institution_ids":["https://openalex.org/I4210118689"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055011860","display_name":"Felix Rembold","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118689","display_name":"Joint Research Centre","ror":"https://ror.org/02qezmz13","country_code":"IT","type":"government","lineage":["https://openalex.org/I1320481043","https://openalex.org/I2800387288","https://openalex.org/I4210118689","https://openalex.org/I4210161702"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Rembold","raw_affiliation_strings":["Food Security Unit, Joint Research Centre of the European Commission, Ispra, VA, Italy"],"affiliations":[{"raw_affiliation_string":"Food Security Unit, Joint Research Centre of the European Commission, Ispra, VA, Italy","institution_ids":["https://openalex.org/I4210118689"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030183502","display_name":"Oberdan L\u00e9o","orcid":"https://orcid.org/0000-0002-3621-4743"},"institutions":[{"id":"https://openalex.org/I4210118689","display_name":"Joint Research Centre","ror":"https://ror.org/02qezmz13","country_code":"IT","type":"government","lineage":["https://openalex.org/I1320481043","https://openalex.org/I2800387288","https://openalex.org/I4210118689","https://openalex.org/I4210161702"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"O. Leo","raw_affiliation_strings":["Food Security Unit, Joint Research Centre of the European Commission, Ispra, VA, Italy"],"affiliations":[{"raw_affiliation_string":"Food Security Unit, Joint Research Centre of the European Commission, Ispra, VA, Italy","institution_ids":["https://openalex.org/I4210118689"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013271290","display_name":"Hendrik Boogaard","orcid":"https://orcid.org/0000-0001-7831-2280"},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"H. Boogaard","raw_affiliation_strings":["Wageningen Environmental Research (WENR), Wageningen University and Research, Wageningen, AA, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Wageningen Environmental Research (WENR), Wageningen University and Research, Wageningen, AA, The Netherlands","institution_ids":["https://openalex.org/I913481162"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103205638","display_name":"Steven Hoek","orcid":"https://orcid.org/0000-0002-7472-8526"},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"S. Hoek","raw_affiliation_strings":["Wageningen Environmental Research (WENR), Wageningen University and Research, Wageningen, AA, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Wageningen Environmental Research (WENR), Wageningen University and Research, Wageningen, AA, The Netherlands","institution_ids":["https://openalex.org/I913481162"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5027546688"],"corresponding_institution_ids":["https://openalex.org/I4210118689"],"apc_list":null,"apc_paid":null,"fwci":0.9014,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83267841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10439","display_name":"Climate change impacts on agriculture","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1105","display_name":"Ecology, Evolution, Behavior and Systematics"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10439","display_name":"Climate change impacts on agriculture","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1105","display_name":"Ecology, Evolution, Behavior and Systematics"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9926999807357788,"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/outlier","display_name":"Outlier","score":0.7160272598266602},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.6938669085502625},{"id":"https://openalex.org/keywords/crop-yield","display_name":"Crop yield","score":0.6848807334899902},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.594551682472229},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5180287957191467},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5062114596366882},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.49364933371543884},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.49226489663124084},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.48577311635017395},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.483478844165802},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.4105631113052368},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3779376745223999},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3544618785381317},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17464286088943481},{"id":"https://openalex.org/keywords/climate-change","display_name":"Climate change","score":0.15168562531471252},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.14280763268470764},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.10619720816612244},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06848540902137756}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7160272598266602},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.6938669085502625},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.6848807334899902},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.594551682472229},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5180287957191467},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5062114596366882},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.49364933371543884},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.49226489663124084},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.48577311635017395},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.483478844165802},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.4105631113052368},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3779376745223999},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3544618785381317},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17464286088943481},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.15168562531471252},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.14280763268470764},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.10619720816612244},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06848540902137756},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/agro-geoinformatics.2017.8047071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/agro-geoinformatics.2017.8047071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 6th International Conference on Agro-Geoinformatics","raw_type":"proceedings-article"},{"id":"pmh:wur:oai:library.wur.nl:wurpubs/553546","is_oa":false,"landing_page_url":"https://research.wur.nl/en/publications/cst-a-freeware-for-predicting-crop-yield-from-remote-sensing-or-c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2017 6th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2017. Institute of Electrical and Electronics Engineers Inc.","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2017107861","https://openalex.org/W2031619975","https://openalex.org/W2261645655","https://openalex.org/W2319794630","https://openalex.org/W4256358309"],"related_works":["https://openalex.org/W4311044804","https://openalex.org/W2072076847","https://openalex.org/W4233375198","https://openalex.org/W2062105804","https://openalex.org/W2382415340","https://openalex.org/W2804312381","https://openalex.org/W2018697919","https://openalex.org/W1805207201","https://openalex.org/W2527659823","https://openalex.org/W2182796073"],"abstract_inverted_index":{"CST":[0,27,55,119,147,195,367],"(Crop":[1],"Statistics":[2],"Tool)":[3],"is":[4,28,98,162],"a":[5,49,95,110,136,180,218,327],"standalone":[6],"freeware":[7],"for":[8,109,121,183,246,255,335,373],"predicting":[9],"crop":[10,17,58,76,176,210,283,385,388,401],"yield":[11,46,102,105,137,358],"statistics":[12,154,359],"using":[13],"indicators":[14,167,260,310,317,375,394],"derived":[15,395],"from":[16,48,139,261,279,379,396],"models,":[18],"weather":[19],"or":[20,44,143,187,214,243,360,400],"remote":[21,397],"sensing":[22,398],"data.":[23],"The":[24],"principle":[25],"of":[26,72,194,248,330,357,363],"that":[29,349],"years":[30,123],"similar":[31,42,45,125],"to":[32,66,86,127,130,134,149,172,236,354,404],"the":[33,37,57,75,79,82,122,128,131,140,144,175,192,206,222,249,262,270,275,280,331,336,355,361,364,370],"target":[34],"year":[35,133],"(e.g.":[36],"current":[38,132],"year)":[39],"should":[40,383],"have":[41],"yields,":[43],"deviations":[47],"technological":[50],"time":[51,73,111,141,314,332,381],"trend.":[52],"In":[53,221,269],"practice,":[54],"guides":[56],"analyst":[59,77,177],"through":[60],"standard":[61,153],"steps:":[62],"after":[63],"data":[64,103,399],"screening":[65],"identify":[67],"possible":[68],"outliers":[69],"and":[70,104,155,203,212,267,289,298,312,319,323,334,340],"analysis":[71,92],"trend,":[74,315],"has":[78],"choice":[80],"between":[81,100,209,265],"following":[83],"two":[84,197,247,293],"approaches":[85],"forecast":[87],"yield:":[88],"(1)":[89],"multiple":[90],"regression":[91,207],"in":[93,390],"which":[94,161],"linear":[96],"relationship":[97],"calibrated":[99],"historical":[101],"indicators,":[106,337,366],"while":[107],"accounting":[108],"trend":[112,142,321,333],"if":[113],"present;":[114],"(2)":[115],"scenario":[116],"analysis,":[117],"whereby":[118],"looks":[120],"most":[124],"(according":[126],"indicators)":[129],"estimate":[135],"deviation":[138],"average":[145],"yield.":[146],"allows":[148],"assess":[150],"models":[151,303,402],"with":[152,196,240,292,313,369],"tests":[156],"as":[157,159],"well":[158,238],"warnings,":[160],"especially":[163],"useful":[164],"when":[165],"many":[166,393],"are":[168,403],"available.":[169],"Moreover,":[170],"thanks":[171],"batch":[173],"processing,":[174],"can":[178],"test":[179],"given":[181,219],"model":[182],"various":[184],"dekads,":[185,307],"regions":[186],"crops.":[188],"This":[189],"paper":[190],"illustrates":[191],"interest":[193],"case":[198],"studies":[199],"made":[200],"over":[201,232],"Africa":[202],"based":[204],"on":[205],"approach":[208],"yields":[211,228,278],"NDVI":[213,242,288],"cumulated":[215,290],"rainfall":[216,245,291],"at":[217,229,376],"dekad.":[220],"first":[223],"one,":[224],"South":[225],"African":[226],"maize":[227,252,277],"province":[230],"level":[231,378],"1987-2015":[233],"were":[234],"found":[235],"be":[237,351,405],"correlated":[239],"Vegetation/ProbaV":[241],"CHIRPS":[244],"three":[250],"main":[251,281],"producing":[253],"provinces;":[254],"each":[256],"province,":[257],"we":[258,273,300],"tested":[259,301],"15":[263,306],"dekads":[264],"January":[266],"May.":[268],"second":[271],"study,":[272],"regressed":[274],"1999-2014":[276],"26":[282],"production":[284],"zones":[285],"against":[286],"also":[287],"different":[294],"start":[295],"dates":[296],"(April":[297],"June);":[299],"3000":[302],"(26":[304],"zones,":[305],"3":[308],"single":[309],"without":[311],"all":[316],"together,":[318],"finally":[320],"alone)":[322],"obtained":[324],"mixed":[325],"results:":[326],"strong":[328],"dominance":[329],"unstable":[338],"relationships":[339],"sometimes":[341],"wrong":[342],"slope":[343],"signs.":[344],"Beyond":[345],"these":[346],"contrasting":[347],"results":[348],"could":[350],"partly":[352],"due":[353],"quality":[356],"relevance":[362],"selected":[365],"combined":[368],"SPIRITS":[371],"tool":[372],"extracting":[374],"region":[377],"raster":[380],"series,":[382],"help":[384],"analysts":[386],"predict":[387],"yield,":[389],"particular":[391],"where":[392],"tested.":[406]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}