Abstract. Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may lack sufficient local variation in the economic activities to analyze local economic development patterns and the exposure to natural hazards. Agriculture GDP is a critical indicator for measurement of the primary sector, on which more than 2.5 billion people depend on their livelihoods that provide a key source of income for the entire household (FAO, 2021). Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 x 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper estimates the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP is an estimated US$432 billion of agricultural GDP circa 2010, where nearly 1.2 billion people live. The data are available on the World Bank Development Data Hub (DOI: http://doi.org/10.57966/0j71-8d56; IFPRI and World Bank, 2022).

中文翻译：

---

估算全球当地农业 GDP

摘要。经济统计数据通常在行政级别（例如地方分部）生成。然而，这些措施可能缺乏足够的当地经济活动差异来分析当地经济发展模式和自然灾害风险。农业 GDP 是衡量第一产业的关键指标，超过 25 亿人依靠其生计，为整个家庭提供了重要的收入来源（粮农组织，2021 年）。通过基于交叉熵优化的数据融合方法，本文使用卫星衍生的农业 GDP 组成部分指标，即作物, 牲畜, 渔业, 狩猎和木材生产。该论文估计，2000 年至 2009 年期间至少发生过一次极端干旱的地区对农业 GDP 的影响在 2010 年左右估计为 4320 亿美元，其中有近 12 亿人居住。数据可在世界银行发展数据中心（DOI：http://doi.org/10.57966/0j71-8d56；IFPRI 和世界银行，2022 年）上获得。