8 hasil untuk "Jonathan Proctor"
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Artikel Jurnal
Global climate migration is a story of who and not just how many
Abstract Understanding the impact of climate change on human migration is critical for policymakers. Yet climate change can both incentivize people to migrate and reduce their ability to move, making its effect on human migration ambiguous. We propose an approach to studying migration that combines…
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Artikel Jurnal
Divergent estimates of agricultural climate sensitivity from survey and satellite yield data
Accurate monitoring of crop yields is critical for understanding historical food production trends, identifying yield gaps, assessing food security risks, and evaluating climate impacts. Two primary means of estimating yields are through surveys and satellite remote sensing. We compare…
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Artikel Jurnal
Is Water Stress the Root Cause of the Observed Nonlinear Relationship Between Yield Losses and Temperature?
Abstract Observational analyses consistently find that yields of major rainfed crops increase with temperature up to a threshold of approximately 32°C, above which they reduce sharply. Two damage pathways have been suggested to explain this relationship: that high temperatures directly stress crops…
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Artikel Jurnal
Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning
Abstract The United Nations Human Development Index, which incorporates income, education and health, is arguably the most widely used alternative to gross domestic product. However, official country-resolution estimates (N=191) limit its use. We build on recent advances in machine learning and…
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Artikel Jurnal
Differences in Radiative Forcing, Not Sensitivity, Explain Differences in Summertime Land Temperature Variance Change Between CMIP5 and CMIP6
Abstract How summertime temperature variability will change with warming has important implications for climate adaptation and mitigation. CMIP5 simulations indicate a compound risk of extreme hot temperatures in western Europe from both warming and increasing temperature variance. CMIP6…
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Artikel Jurnal Teks lengkap
Monitoring Maize Yield Variability over Space and Time with Unsupervised Satellite Imagery Features
Recent innovations in task-agnostic imagery featurization have lowered the computational costs of using machine learning to predict ground conditions from satellite imagery. These methods hold particular promise for the development of imagery-based monitoring systems in low-income regions, where…
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Artikel Jurnal
A generalizable and accessible approach to machine learning with global satellite imagery
This paper presents MOSAIKS, a system for planet-scale prediction of multiple outcomes using satellite imagery and machine learning (SIML). MOSAIKS generalizes across prediction domains and has the potential to enhance accessibility of SIML across research disciplines.
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Artikel Jurnal
HarvestStat: a global effort towards open and standardized sub-national agricultural data
Agricultural production statistics underpin diverse research efforts and development activities. Yet despite their critical importance, efforts to collate, update, and harmonize detailed sub-national agricultural production statistics are frequently redundant and incomplete due to the substantial…