Title : 
  Germany - wide time series of interpolated phenological observations for main crop types between 1993 and 2021 
 Abstract_text_1 : 
  Germany - wide time series of interpolated phenological observations for main crop types between 1993 and 2021 . 
 Abstract_text_2 : 
  < p > The data set documents a Germany - wide and spatio - temporally consistent 1 × 1 km² analysis - ready time series ( ARD - TS ) of interpolated DOYs ( days of the year ) covering 56 beginning phenological development stages ( phases ) of 9 main crop types for the period between 1993 and 2021 . The derivation is based on Germany - wide observations of the German Weather Service ( DWD ) , which were statistically filtered and interpolated . < /p > < p > The German Weather Service operates a phenological observation network . About 1200 observers monitor 160 phenological phases of wild and cultivated plants . The PHASE model was developed to interpolate the phenological observations for the entire territory of Germany ( Gerstmann et al . ( 2016 ) Rel . Identifer TAB 8) . The model combines the concept of growing degree days ( GDD ) with a geostatistical interpolation procedure . The PHASE model was applied to create a Germany - wide and spatio - temporally consistent 1 × 1 km² analysis - ready time series ( ARD - TS ) of interpolated DOYs ( days of the year ) covering 56 beginning phenological development stages ( phases ) of 9 main crop types for the period between 1993 and 2021 . The dataset includes the following information : < /p > < p > • Germany - wide interpolated temperature data from the German Weather Service ( DWD ) , < br/ > • raster datasets of interpolated crop - specific and Germany - wide incipient phenological development stages for the period between 1993 and 2020 . The value in each pixel of these rasters represents the Day Of the Year ( DOY ) of the respective beginning phenological plant development stage , < br/ > • accuracy metrics ( RMSE , MSE , MAE , and R² ) for each Germany - wide interpolation result . < /p > < p > The code of the phase model is documented in a software repository ( Rel . Identifer TAB 9 and 10 ) . The temporally static model input data are also stored there . < /p > < p><b > Research question < /b > < br/ > The dataset allows the spatio - temporal definition of phenological windows for any available year and user - defined region ( Möller et al . ( 2020 ) Rel . Identifer TAB 1 ) . Such information is important for various agricultural issues such as the derivation of weather or biodiversity indices , crop classification , soil erosion or crop yield modeling ( Bucheli et al . ( 2022 ) Rel . Identifer TAB 5 ; Gerstmann et al . ( 2018 ) ; Rel . Identifer TAB 3 ; Möller et al . ( 2017 , 2018 ) ; Rel . Identifer TAB 2 and 4 ; Riedsel et al . ( 2022 ) ; Rel . Identifer TAB 6 ) . < /p > All relvant papers are listed under RelatedIdentifier . < br/ > A form for creating an individual WCS can be found here:<br/ > < a href="https://sf.julius - kuehn.de / openapi / phase/">https://sf.julius - kuehn.de / openapi / phase/</a > 
 Keywords : 
  Soil , agricultural practices , crop rotation , environmental monitoring , multiple regression analysis , plant developmental stages , phenology , opendata , Boden , agricultural management , crop rotation , environmental monitoring , interpolation , seasonal variation , biological development , elevation , land use , meteorological geographical features , geographical grid systems , Germany