Brainfood: Mapping edition
- We’re moving house so this might be the last post for a while. See you on the other side. In the meantime, enjoy this bunch of papers on different applications of spatial analysis to agricultural biodiversity and associated topics.
- Addressing global hotspots of drought-related crop production losses. A crop-specific drought sensitivity metric for 17 major crops finds rainfed production losses of 10% globally under historically observed extremes, enough to feed 2 billion people, with hotspots in the US Midwest, eastern Brazil, the Mediterranean and South Asia. Sustainable irrigation expansion and crop switching could avoid 60% of those losses. No word on varietal change, but I’m sure it would help.
- GEM-Forest: A Global satellite EMbedding–based map of forests and tree crops for 2020. Using Google DeepMind’s Alpha Earth Foundation embeddings, this 10 m global dataset classifies forest, non-forest and tree crop areas with 90% accuracy, showing that lightweight classifiers on satellite embeddings 1 can rival more complex forest-monitoring pipelines built to support things like the EU Deforestation Regulation.
- Global distribution of cattle, horses, goats, sheep and buffaloes at 1 km resolution for 2000–2022 based on subnational census data and spatiotemporal machine learning. Harmonizing 55,336 census polygons across 147 countries produces annual 1 km livestock headcount and density layers for five species, letting users track shifting grazing pressure over more than two decades rather than relying on single-year snapshots. 2
- A Spatial-Econometric Analysis of Fruit Tree Diversity in Lebanon: A contextual framework for supporting smallholder farmers. How geography, socio-economic conditions and local context shape fruit tree diversity in Lebanon, helping identify where interventions could best support smallholder resilience.
- High-resolution mapping of rice cropping pattern, intensity, calendar, and ecosystem type across Southeast Asia. Joins the growing pile of fine-resolution rice products for the region, this one distinguishing not just how many harvests a field gets but which rice ecosystem (irrigated, rainfed, upland) it belongs to. Is which variety is being grown next on the agenda?
- Entrenchment of cropping patterns reinforces climate exposure for certain crops in US. County-level analysis of US cropping decisions finds that climate risk has actually risen for some crops (like rainfed soybeans) even as it fell for others, suggesting economic and policy incentives are keeping farmers planted in increasingly climate-mismatched patterns rather than nudging them toward the drought-sensitivity-driven switching the first paper above models.
Source: https://agro.biodiver.se/2026/07/brainfood-mapping-edition/
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