A key feature of mapspamc is to allocate the crop statistics to areas identified as cropland on a map - the cropland extent. As described in the section on Input data, we use a so-called synergy cropland map to account for the uncertainty in the location of cropland. The synergy cropland map combines different cropland products to construct a single cropland map that presents the mean and maximum available crop area per grid cell as well as a ranking that measures the agreement between the various cropland products for each grid cell. A ranking of 1 means that all sources agree there is cropland in a grid cell, while a higher rank signals disagreement.

The package contains a script to create a synergy cropland map using global land use products that are included in the maspamc database: COPERNICUS, ESACCI, ESRI, GLAD and MODIS (see the database documentation for details). The script is located in the 02_3_pre_processing_cropland folder. Before the synergy cropland map can be created the user needs to clip target country from the global datasets and ensure the maps have the right format (i.e. desired extent, resolution and coordinate reference system). Scripts to do this for each global land use product are provided in the same folder.

For the Malawi example, we can make use of an existing global synergy cropland map (SASAM) that was prepared for SPAM2010, which can be selected by running select_sasam.R. For the Ethiopia country example we used information from four datasets that represent global cropland around the period 2015: GLAD, COPERNICUS, ESACCI and MODIS. The user needs to run select_*.R first to process the global maps. The script create_synergy_cropland_map.R combines the selected land use maps and creates a country synergy cropland map.

In order to create the synergy map, a ranking table is needed that indicates, which (combination) of the inputs maps is regarded as the most reliable. In case all the global cropland maps signal a grid cell contains cropland the ranking is 1 (highest and most reliable). For all other combinations the user needs to prepare a ranking table. The table for Ethiopia is added to the mapspamc database(synergy_cropland_table/synergy_cropland_table_2015.xlsx) and contains a ranking from 1 to 16 (see below) because it is based on four maps. For Ethiopia, we decided on the following order of increasing importance when creating the scoring table: (1) GLAD, (2) COPERNICUS, (3) ESACCI and (4) MODIS. GLAD receives the highest score because it has the highest original resolution (30 meter) and is therefore assumed to be the most accurate, followed by COPERNICUS (100 meter), ESACCI (300 meter) and MODIS (500 meter).

Ranking table for 2015 synergy cropland map
agreement rank glad copernicus esacci modis
4 1 1 1 1 1
3 2 1 1 1 0
3 3 1 1 0 1
3 4 1 0 1 1
2 5 0 1 1 1
2 6 1 1 0 0
2 7 1 0 1 0
2 8 1 0 0 1
2 9 0 1 1 0
2 10 0 1 0 1
2 11 0 0 1 1
1 12 1 0 0 0
1 13 0 1 0 0
1 14 0 0 1 0
1 15 0 0 0 1
0 16 0 0 0 0

If the user is interested in creating a more recent synergy cropland map (e.g. for around 2020), we recommend using the following combination of cropland products, which are available in the mapspamc database: ESRI (2020), GLAD (2019), COPERNICUS (2019) and ESACCI (2020), and modify the 2015 ranking table accordingly. Alternatively, and if available, the user could add a national land use product and create a ranking with five different inputs that goes up to 32.