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dc.contributorXoplaki, Elena
dc.contributor.authorEllsäßer, Florian
dc.contributor.otherJustus-Liebig University Gießen, ZEU – Center for International Development and Environmental Researchde_DE
dc.date.accessioned2022-09-20T04:55:01Z
dc.date.available2022-09-20T04:55:01Z
dc.date.issued2022-09-19
dc.identifier.urihttps://jlupub.ub.uni-giessen.de//handle/jlupub/7745
dc.identifier.urihttp://dx.doi.org/10.22029/jlupub-7176
dc.description.abstractThis data set contains a .csv file yield_anomaly_catalogue_v001.csv that lists all areas affected by large or extreme yield anomalies. Large and extreme anomalies are defined according to the Standardized Yield Anomaly Index (SYAI) where “large” is defined as all values between ± 1 standard deviation (std) and ± 2 std and “extreme” values are defined as all values above or below ± 2 stds from the mean. The data set is organized by the following headers: year = harvest year of occurrence; crop = defining the crop type; attribute = where -2 and -1 are extreme and large negative yield anomalies respectively and 1 and 2 are large and extreme positive yield anomalies respectively; size = affected area in km²; relative_size = affected area in relative terms compared to the total area of Germany; average = average/mean value of all pixels in this affected area. This data set is based on multiple data sets that were provided by the federal and state statistical offices of Germany and the Federal Agency for Cartography and Geodesy. The copyright statements and names of institutions are mentioned and listed in the following: For the spatial data set (county borders): © GeoBasis-DE / BKG (2022) - Datenlizenz Deutschland Version 2.0, further raw data from Regionaldatenbank Deutschland were used on federal level: © Statistisches Bundesamt (Destatis), 2022. Further data from individual states were collected and include the following copyright statements: Schleswig-Holstein: © Statistisches Amt für Hamburg und Schleswig-Holstein, Hamburg 2022; Niedersachsen: © Landesamt für Statistik Niedersachsen, Hannover 2020; Nordrhein-Westfalen: © Information und Technik Nordrhein-Westfalen, Düsseldorf 2020; Hessen: © Hessisches Statistisches Landesamt, Wiesbaden, 2022; Rheinland-Pfalz: © Statistisches Landesamt Rheinland-Pfalz, Bad Ems, 2022. Baden-Württemberg:© Statistisches Landesamt Baden-Württemberg, Stuttgart, 2020; Freistaat Bayern: © Bayerisches Landesamt für Statistik, Fürth, 2022; Saarland: © Statistisches Amt des Saarlandes, Saarbrücken; Brandenburg: © Amt für Statistik Berlin-Brandenburg, Potsdam, 2021; Mecklenburg-Vorpommern: © Statistisches Amt Mecklenburg-Vorpommern, Schwerin, 2022, Freistaat Sachsen: © Statistisches Landesamt des Freistaates Sachsen, Kamenz 2022; Sachsen-Anhalt: © Statistisches Landesamt Sachsen-Anhalt, Halle (Saale), 2020; Freistaat Thüringen: © Thüringer Landesamt für Statistik, Erfurt, 2021. Please refer to these institutions and copyright statements when publishing data or products that are based on this data set.de_DE
dc.description.sponsorshipBundesministerium für Bildung und Forschung (BMBF); ROR-ID:04pz7b180de_DE
dc.language.isoende_DE
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectcrop, yield anomaly, anomaly, SYAI, standardized yield anomaly index, yield, Germany, spatial, county, NUTS-3, winter wheat, rye, mixed winter cereals, spring barley, winter barley, oat, triticale, silage maize, oilseed rape, potato, sugar beetde_DE
dc.subject.ddcddc:000de_DE
dc.subject.ddcddc:333.7de_DE
dc.subject.ddcddc:500de_DE
dc.subject.ddcddc:550de_DE
dc.subject.ddcddc:580de_DE
dc.subject.ddcddc:630de_DE
dc.subject.ddcddc:710de_DE
dc.titlecropdata – yield anomaly catalogue for the ten most cultivated crops in Germany from 1989 to 2020 - version 1.0de_DE
dc.title.alternativeyield anomalies based on the Standardized Yield Anomaly Index (SYAI) for winter wheat, rye and mixed winter cereals, spring and winter barley, oat, triticale, silage maize, oilseed rape, potato and sugar beet in Germany from 1989 to 2020 - version 1.0de_DE
dc.typeDatasetde_DE
local.affiliationZEU Zentrum für internationale Entwicklungs- und Umweltforschungde_DE
local.projectclimXtreme project https://www.climxtreme.net/index.php/en/ C3 CROP project (grant number 01LP1903C) https://www.uni-giessen.de/zeu/CROPde_DE


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