Historical fire data by Ambee provides valuable insights into the occurrence, intensity, and impact of historical forest fires, enabling researchers, analysts, and organizations to make informed decisions and develop proactive risk-mitigation strategies. Get a complete picture of wildfire history, down to burned areas, FWI, FRP, and fire start and contain dates, among others.



































Ambee’s fire data is a result of the combination of various fire data sources that include satellite imagery, on-ground sensors, and open sources. Our proprietary models measure, process, and analyze data from these sources and process many terabytes of data every day.
Ambee offers an extensive collection of historical wildfire data, meticulously gathered and curated over a span of several years. Gain valuable insights into the patterns, trends, and impacts of wildfires with our comprehensive dataset.
Detect wildfires at their earliest stages and monitor hotspots, ignition points, and fire progression patterns. Identify high-risk areas, develop fire prevention strategies, and allocate resources effectively.
Analyze historical fire to accurately evaluate the fire risk associated with a particular business location or industry sector. Set appropriate insurance coverage and pricing, ensuring businesses are adequately protected against potential fire-related losses.
Understand fire behavior patterns, such as the rate of spread, intensity, and direction. Develop and refine fire behavior models essential for predicting fire behavior in different environments and under various climatic conditions.
Assess the vulnerability of transportation routes, warehouses, and distribution centers to wildfires. Develop contingency plans, implement fire prevention measures, and ensure the resilience of the supply chain.

Here’s how these companies have made strides using Ambee’s data




Our team of data scientists, developers, and experts is here to cater to all your business use cases. Get in touch with us today to help your customers live healthy, make better business decisions, and increase ROI along the way.
Historical wildfire data provide valuable insights into the occurrence, intensity, and impact of past forest fires. By analyzing this data, researchers, analysts, and organizations can identify patterns and trends in wildfire behavior. They can study the frequency and distribution of wildfires, assess their severity, and understand the factors that contribute to their occurrence. This information helps to develop proactive risk-mitigation strategies, allocate resources effectively, and identify high-risk areas for fire prevention efforts.
The 6+ years of historical wildfire data cover a significant span of time, enabling a comprehensive understanding of wildfire patterns and trends. The specific time range is not mentioned in the provided content, but it extends beyond seven years, offering a substantial dataset for analysis.
The historical wildfire data offered by Ambee results from various fire data sources. These sources include satellite imagery, on-ground sensors, and open sources. Ambee's proprietary models measure, process, and analyze data from these sources, resulting in a comprehensive dataset. This multi-source approach ensures the accuracy and reliability of the historical wildfire data.
Yes, the historical wildfire data provided by Ambee is reliable and accurate. Ambee employs advanced data collection methods and stringent quality control measures to ensure the dataset's accuracy. The data is sourced from reliable sources, including satellite imagery and ground sensors. Ambee's data scientists and experts work diligently to curate and verify the data, ensuring its reliability for research, analysis, and decision-making.
Ambee offers access to historical wildfire data provided by Ambee. Users can take advantage of the extensive collection of data by contacting Ambee's experts through the provided contact information. They can reach out to the team to inquire about accessing the historical wildfire data and gain insights into the availability, accessibility, and specific requirements for obtaining the dataset.