We developed BestiaPop (a spanish word that translates to pop beast), a Python package which allows model users to automatically download SILO's (Scientific Information for Land Owners) or NASAPOWER gridded climate data and convert this data to files that can be ingested by Crop Models like APSIM or DSSAT. Moreover, source data providers like SILO or NASA POWER are usually neutral in the type of data output files they provide as part of their API services which leads to a gap between source raw data and processed data required by crop modelling suites to develop their models. However, Crop Models expects input data to be encapsulated in custom file formats ( MET, WTH, etc.) which don't conform to a common standard and require various customizations, depending on the prediction engine that generates crop models. #APSIM DOCUMENTATION DOWNLOAD#![]() BestiaPop: A python package to automate the extraction and processing of climate data for crop modellingĬlimate data is an essential input for crop models to predict crop growth and development using site-specific (point) or gridded climate data.
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