The world is being fed at the expense of nature: A remote sensing based global assessment from 2000 to 2019

Understanding agricultural productivity dynamics is essential for evaluating the global capacity to achieve food security while safeguarding nature. This requires tracking food production relative to natural resource use. The Comprehensive Assessment of Water Management in Agriculture (CAWMA), a landmark CGIAR-led study by over 700 scientists, presents six scenarios for the future of food production; its optimal scenario outlines a pathway to meeting food, economic, and environmental objectives by 2050. Using satellite remote sensing from validated global datasets, we derived spatially explicit trends in key agricultural variables from 2000 to 2019 and compared these against CAWMA optimal scenario projections. Our findings show that the world has substantially deviated from this scenario, aligning with more pessimistic outlooks. Global agricultural production increased by 24.3%, nearly meeting the projected 26.2% growth in food demand, but through an 11.5% expansion of cropland area, three times faster than the projected 3.6%, and at least 15.0% increase in irrigated area, more than two times the projected 6.1%. Crop water consumption rose by 25.3% against a projection of 7.4%. Land productivity improved by only 11.6% versus a projected 21.7%, and water productivity declined by 1.6% against a projected increase of 12.9%. These trends confirm continued resource-intensive habits, risking nature and undermining long-term water and food security. To redirect these trajectories, we recommend grounding agricultural scenarios in empirical evidence integrating remote sensing with statistical data; regularly updating productivity models; improving data accessibility for policymakers; shifting toward systemic transformation of food production; and adopting locally differentiated yet globally coordinated responses.

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Publication Details

Journal
Agricultural Water Management
Published
2026-08-27
DOI
https://doi.org/10.1016/j.agwat.2026.110711
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

The world is being fed at the expense of nature: A remote sensing based global assessment from 2000 to 2019

CHARLOTTE DE FRAITURE, Poolad Karimi, Abdur Rahim Safi
Agricultural Water Management
Remote Sensing in Agriculture
article

The world is being fed at the expense of nature: A remote sensing based global assessment from 2000 to 2019

CHARLOTTE DE FRAITURE, Poolad Karimi, Abdur Rahim Safi
article en

Abstract

Understanding agricultural productivity dynamics is essential for evaluating the global capacity to achieve food security while safeguarding nature. This requires tracking food production relative to natural resource use. The Comprehensive Assessment of Water Management in Agriculture (CAWMA), a landmark CGIAR-led study by over 700 scientists, presents six scenarios for the future of food production; its optimal scenario outlines a pathway to meeting food, economic, and environmental objectives by 2050. Using satellite remote sensing from validated global datasets, we derived spatially explicit trends in key agricultural variables from 2000 to 2019 and compared these against CAWMA optimal scenario projections. Our findings show that the world has substantially deviated from this scenario, aligning with more pessimistic outlooks. Global agricultural production increased by 24.3%, nearly meeting the projected 26.2% growth in food demand, but through an 11.5% expansion of cropland area, three times faster than the projected 3.6%, and at least 15.0% increase in irrigated area, more than two times the projected 6.1%. Crop water consumption rose by 25.3% against a projection of 7.4%. Land productivity improved by only 11.6% versus a projected 21.7%, and water productivity declined by 1.6% against a projected increase of 12.9%. These trends confirm continued resource-intensive habits, risking nature and undermining long-term water and food security. To redirect these trajectories, we recommend grounding agricultural scenarios in empirical evidence integrating remote sensing with statistical data; regularly updating productivity models; improving data accessibility for policymakers; shifting toward systemic transformation of food production; and adopting locally differentiated yet globally coordinated responses.

Agricultural Water ManagementVol. 335
IHE Delft Institute for Water Education (NL), Wageningen University & Research (NL)
Zero hunger
Openalex Percentile: Top 11%
Remote Sensing in Agriculture
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