SPAM_data_reader

Read IFPRI and IIASA SPAM global data at the scale of user defined shapefiles and crop groups. SPAM 2020 data is available at https://www.mapspam.info/. SPAM data contains global gridded data for area, yield and production for 46 crops and 2 production systems (irrigated, rainfed), previously also: rainfed high input, rainfed low input and rainfed subsitence.

Requierments

You need python with the following libraries: pandas, geopandas, rasterstats, and numpy

Usage

• Download this repository
• Download the SPAM data: https://mapspam.info/ (SPAM2020v1)
• Place your desired shapefiles in the Shapefiles folder - the projection needs to be EPSG:4326 - WGS84 - default shapefiles of the Zambezi River Basin are in this repository for you to test the script
• Open the excel file SPAM_metadata.xlsx - in the sheet SHAPEFILES insert your shapefiles' name and the id to be used (replace default 'catchments' and 'countries' shapefiles)
• Run the SPAM_data_reader.py script
• (Automatic downloading of Data currently NOT available) - the first time, the script needs to download SPAM data (see Options to avoid this), hence it might take some time depending on your connection
• Go to the Ouptputs folder and look at the output files

Options

You can customize different options in the SPAM_metadata.xlsx file, a complete description of the options is available within the excel file:

• SHAPEFILES: define which shapefiles should be used
• SPAMvars: define which variables should be compiled, convert units, data source and download options
• SPAMcrops: define which crops should be compiled
• SPAMtechs: define which technologies (/production system) should be compiled
• GROUPcrops: define your own crop groups to reframe SPAM data
• EXPORT: define the outputs and csv files options
• INFO: define an Info message to be attached in the output excel files

Outputs

All outputs are found in the Outputs folder (or user-defined folder):

• SPAM_yourshapefile.csv: csv file with the raw SPAM data at the level of your shapefile
• SPAM_yourshapefile_cropgroups.csv: same as previous for user defined crop groups instead of SPAM crops
• SPAM_yourshapefile_summarized.xlsx: excel file with the SPAM data at the level of your shapefile as 2D Tables, area and production are summed, yield is as a weighted average (by harvested area)
• SPAM_yourshapefile_cropgroups_summarized.xlsx: same as previous for user defined crop groups instead of SPAM crops

Common errors

• If shapefiles do not have the correct projection WGS 84, EPSG 4326:

File "rasterio_io.pyx", line 323, in rasterio._io.DatasetReaderBase.read MemoryError

• If all crops are not assigned a crop group !

return cropgroup[cropgroup.eq(crop).any(1)].index[0] File "C:\Programs\envs\Python36\lib\site-packages\pandas\core\indexes\base.py", line 4280, in getitem return getitem(key) IndexError: index 0 is out of bounds for axis 0 with size 0

Author

Raphael Payet-Burin ([email protected])