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Data on global agricultural production are usually available as statistics at administrative units, which does not give any diversity and spatial patterns; thus they are less informative for subsequent spatially explicit agricultural and environmental analyses. In the second part of the two-paper series, we introduce SPAM2010 – the latest global spatially explicit datasets on agricultural production circa 2010 – and elaborate on the improvement of the SPAM (Spatial Production Allocation Model) dataset family since 2000. SPAM2010 adds further methodological and data enhancements to the available crop downscaling modeling, which mainly include the update of base year, the extension of crop list, and the expansion of subnational administrative-unit coverage. Specifically, it not only applies the latest global synergy cropland layer (see Lu et al., submitted to the current journal) and other relevant data but also expands the estimates of crop area, yield, and production from 20 to 42 major crops under four farming systems across a global 5 arcmin grid. All the SPAM maps are freely available at the MapSPAM website (http://mapspam.info/ , last access: 11 December 2020), which not only acts as a tool for validating and improving the performance of the SPAM maps by collecting feedback from users but is also a platform providing archived global agricultural-production maps for better targeting the Sustainable Development Goals. In particular, SPAM2010 can be downloaded via an open-data repository (DOI: 10.7910/DVN/PRFF8V; IFPRI, 2019). [ABSTRACT FROM AUTHOR]

Information on global cropland distribution and agricultural production is critical for the world's agricultural monitoring and food security. We present datasets of cropland extent and agricultural production in a two-paper series of a cultivated planet in 2010. In the first part, we propose a new Self-adapting Statistics Allocation Model (SASAM) to develop the global map of cropland distribution. SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of the cropland area, which is independent of training samples. First, cropland area statistics are used to rank the input cropland maps, and then a scoring table is built to indicate the agreement among the input datasets. Secondly, statistics are allocated adaptively to the pixels with higher agreement scores until the cumulative cropland area is close to the statistics. The multilevel allocation results are then integrated to obtain the extent of cropland. We applied SASAM to produce a global cropland synergy map with a 500 m spatial resolution for circa 2010. The accuracy assessments show that the synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics. The synergy cropland map is available via an open-data repository (10.7910/DVN/ZWSFAA; Lu et al., 2020). This new cropland map has been used as an essential input to the Spatial Production Allocation Model (SPAM) for producing the global dataset of agricultural production for circa 2010, which is described in the second part of the two-paper series. [ABSTRACT FROM AUTHOR]

Data on global agricultural production are usually available as statistics at administrative units, which does not give any diversity and spatial patterns thus is less informative for subsequent spatially explicit agricultural and environmental analyses. In the second part of the two-paper series, we introduce SPAM2010 - the latest global spatially explicit datasets on agricultural production circa year 2010 - and elaborate on the improvement of the SPAM (Spatial Production Allocation Model) dataset family since year 2000. SPAM2010 adds further methodological and data enhancements to the available crop downscaling modeling: it not only applies the latest global synergy cropland layer (see Lu et al., submitted to the current journal) and other relevant data, but also expands the estimates of crop area, yield and production from 20 to 42 major crops under four farming systems across a global 5 arc-minute grid. All the SPAM maps are freely available at the MapSPAM website (http://mapspam.info/), which not only acts as a tool for validating and improving the performance of the SPAM maps by collecting feedbacks from users, but also dedicates as platform providing archived global agricultural production maps for better targeting the Sustainable Development Goals by making proper agricultural and rural development policies and investments. In particular, SPAM2010 can be downloaded via an open-data repository (DOI: https://doi.org/10.7910/DVN/PRFF8V, IFPRI, 2019). [ABSTRACT FROM AUTHOR]