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It includes household level socioeconomic survey data, satellite derived rainfall and potential evapotranspiration data, and Python scripts used for data processing, analysis, and visualization. The socioeconomic data are cross sectional and describe household demographics, livelihoods, and assets, while the climate data provide spatially and temporally explicit measures of hydroclimatic conditions. The Python scripts document the analytical workflow and enable reproducibility of the results. Together, these materials support integrated socioeconomic and environmental analysis and are intended for research and policy relevant applications."}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Agricultural Sciences","Earth and Environmental Sciences","Social Sciences","Other"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Food Insecurity"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Soil Degradation"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Drought"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"These datasets were used to study food insecurity in an integrated manner. 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