Abstract
AbstractLong time series with spatially highly resolved crop data are important for research projects on numerous future challenges in the environment and food sector. In this publication, we describe a dataset with crop-yield and area data for Germany from 1979 to 2021. The data are spatially resolved to 397 districts, which have an average size of 900 km2, and include the crops spring barley, winter barley, grain maize, silage maize, oats, potatoes, winter rape, rye, sugarbeet, triticale and winter wheat. The crop-yield data cover, on average, about 9.5 million hectares per year and 80% of Germany’s total arable land. The dataset contains 214,820 yield and area data points. These were obtained by collecting and digitizing crop data from multiple statistical sources and transforming the data to match the district boundaries in 2020. Potential applications of the data include the analysis of interactions between agricultural yields and environmental factors, such as weather; the validation of yield prediction methodologies or the analysis of yield-loss risks in agriculture.
Publisher
Springer Science and Business Media LLC
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