Open Earth Monitor — Global Workshop 2024

Given that food and shelter are basic human needs, it is not surprising that much scientific focus goes into understanding and modelling plant production systems for nutrition and industrial needs. It is crucial to understand where and when specific crops are most suitable to grow now and in the (near-term) future under risk scenarios [1, 2].

Agricultural land suitability assessment models [3] are based on complex biophysical and human-nature interactions, and traditional approaches based on mechanistic plant growth models may be insufficient to map actual patterns because they miss socio-economic processes [4]. Farmers need to follow decision processes that result in their continued survival in the system [5], which can often lead to "the most suitable" location not being selected. While it is evident that access to technology and resources consumed by crops shape land-use patterns, market and regulatory considerations need to be followed as well, which are notoriously hard to model spatially explicitly.

We have devised a modelling framework to build a spatiotemporal series of crop suitabilities annually between 2000 and 2020 at a resolution of 1km², addressing the circa 170 FAOstat crop types. We informed our modelling framework with a wide range of datasets indicating the occurrence of crops (in-situ occurrences, areal sub-national census data, parcel-level polygons, etc.) matched with an advanced, globally harmonised, hierarchical crop-type ontology. We then complement this knowledge graph with the mechanistic crop growth information to apply an environmental filtering approach and impute a range of additional indications of crop presence and absence. Finally, we use bio-physical and socio-economic predictors of crop production in a deliberate multi-label random forest model, resulting in the realised socio-environmental niche of crops.