Ambee Global Pollen Data - Historical, Present Conditions, and Forecast

Ambee's Global Pollen Data provides global access to pollen conditions to support faster, more confident decision-making. Whether you are building personalized digital health applications, training AI and machine learning models, managing seasonal inventory, improving demand forecasts, running allergy-aware advertising campaigns, developing consumer health platforms, or powering clinical and epidemiological clinical trials or research. Ambee provides a single source of global pollen data with seamless access to past, present, and forecasted conditions.

The dataset is generated  by a blend of environmental signals and proprietary modeling techniques, designed to reflect real-world conditions. Pollen outputs are available at both category level (tree, grass, weed) and species level, with hourly updates and validated forecast windows from hours to days and all the way out to 30 days. Every forecast is benchmarked against seasonal cycles, elevation corrected, and adjusted by geography for local accuracy. Gaps are filled using region-specific calibration models, anomaly detection, and interpolation, ensuring the highest level of accuracy.

The parameters include tree, grass, and weed pollen count, risk index, and dominant species by category, and additional fields such as seasonal benchmarks and geography-adjusted categorical risk scores.

The dataset plugs directly into any existing analytics stack, forecasting models, or ML/AI pipelines. No preprocessing required on your end.

**What's included in the sample** 

This sample dataset provides access to Ambee pollen data across 9 cities spanning key global markets. Data is delivered in hourly and daily formats and includes 180 days of rolling history, present conditions, and a 14-day forecast.

1. New York, USA
2. San Francisco, USA
3. London, England
4. Frankfurt, Germany
5. Paris, France
6. Bengaluru, India
7. Tokyo, Japan
8. Sydney, Australia
9. Cairo, Egypt

***Note -** Ambee pollen data is not limited to these cities and time frames (historical, forecast). The full dataset covers any location across the globe, mappable to any lat / lon or geographically bounded areas such as ZIP or Postal Code, DMA, MSA, or user-defined boundaries.*

**What Ambee offers:**

- A historical pollen archive back to 2010 to present conditions, with forecast views ranging from hours to days and up to 30 days, both in hourly and daily formats.  
- Tree, grass, and weed pollen count across 30+ allergenic species, and categorical risk index, and seasonal benchmarks.
- Mappable to any  precise lat / lon or geographically bounded areas such as ZIP or Postal Code, DMA, MSA, or user-defined boundaries

原始信息汇总

数据集概述：Ambee Global Pollen Data - Historical, Present Conditions, and Forecast

• 提供方：Ambee
• 定价：免费，无限访问
• 刷新频率：每小时
• 时间覆盖：按小时提供

数据集描述

该数据集提供全球统一的、可用于分析的花粉数据，涵盖30多种过敏原的过去、当前和预报（最长30天）信息。数据通过环境信号与专有建模技术生成，反映真实世界情况。输出包括类别级别（乔木、草、杂草）和物种级别的花粉数据，并经过季节性周期校准、海拔修正和地理调整，确保本地准确性。缺失数据通过区域特定校准模型、异常检测和插值进行填充。

包含的关键参数

• 乔木、草、杂草的花粉计数
• 风险指数
• 各类别的优势物种
• 季节性基准
• 地理调整后的分类风险评分

样本数据

样本数据集包含全球9个城市（纽约、旧金山、伦敦、法兰克福、巴黎、班加罗尔、东京、悉尼、开罗）的花粉数据，提供每小时和每日格式，包含180天滚动历史、当前条件及14天预报。完整数据集支持任何全球位置，可映射至经纬度或地理边界区域（如邮政编码、DMA、MSA等）。

完整数据集特点

• 历史档案：自2010年至今，并提供从小时到30天的预报视图（每小时和每日格式）
• 物种覆盖：覆盖30多种致敏物种的乔木、草、杂草花粉计数、分类风险指数及季节性基准
• 地理映射：可映射至任意精确经纬度或地理边界区域

业务需求应用

• 广告与营销：帮助品牌和广告平台理解过敏驱动行为，优化受众定位和活动时机
• 需求预测：零售商和药店结合历史交易数据预测过敏相关产品需求，优化库存与促销
• 制药与生命科学：用于临床试验规划，考虑过敏原暴露，改善患者招募和试验设计
• 出行与汽车：支持车内空气质量管理和清洁空气路线规划
• 数字健康与保健：丰富健康监测数据，个性化户外活动建议
• 智能家居与联网设备：驱动花粉感知自动化和室内空气质量优化

使用示例（SQL查询）

• 查看伦敦当前花粉物种条件（包括桦树、橡树、梧桐、豚草、荨麻等物种计数及风险）
• 分析纽约过去180天的历史花粉条件（用树与杂草花粉均值）
• 查看德国黑森州未来14天的高风险花粉预报（关注草花粉风险指数与计数）

相关数据集

• Ambee Global Air Quality Data
• Ambee Global Weather Data

类别

AI & ML、需求预测、环境、健康与生命科学

联系方式

• 销售：[e-mail]
• 支持：[e-mail]

交付方式

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