---
title: "False Positives: Not every detection is a fire"
description: Use Classifications, Fire & Cluster Confidence to Deal with False Positives
---
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3. [Detections: Hotspots & Clusters](https://help.ororatech.com/learn-the-basics?hsLang=en#detections-hotspots-clusters)
# False Positives: Not every detection is a fire
## Use Classifications, Fire & Cluster Confidence to Deal with False Positives
In this article, we'll cover:
- [What are False Positives](https://help.ororatech.com/false-positives#Falsepositive)
- [Using Cluster and Fire Confidence to filter potential false positives](https://help.ororatech.com/false-positives#clusterfireconf)
- [Understand Location-Based Patterns](https://help.ororatech.com/false-positives#waysfilterconf)
### Introduction
Not every detected heat source is an actual fire. **False positives in our Wildfire Solution refer to detections where non-fire heat sources (like solar panels, industrial sites etc.) are mistakenly identified as potential fires.**
OroraTech’s WFS provides tools to help users distinguish genuine fire threats from false positives, ensuring that decision-makers have the most reliable data available.
The main features we recommend are:
- **Cluster Confidence**: Indicates how many satellites and algorithms have detected and processed the heat source; higher confidence suggests a more reliable detection.
- **Fire Confidence**: Shows the likelihood that a cluster represents an actual fire, based on weather, fire intensity, satellite confirmations, land type and other variables. To learn more read [this section](https://help.ororatech.com/fire-confidence?hsLang=en).
### What Are Common False Positives?
Common sources of false positives include:
- **Industrial sites** and machinery.
- **Volcanic activity** or geothermal hot spots.
- **Reflections** from materials like solar panels, steel roofs, or water bodies.
- **Naturally heated surfaces** like rocks or dry, harvested fields.
False positives are heat sources that mimic the *infrared signature* of a wildfire but are not actual fires.
These detections can occur in both rural and urban settings, with certain types of locations (e.g., cities, industrial zones) being more prone to false positives.
---
### Minimizing False Positives with Fire Confidence
#### **Use *Fire Confidence* to Assess Likelihood of Fire**
Fire Confidence helps assess whether a cluster is likely to be a wildfire. This metric accounts for:
- The heat intensity of the source.
- The environment (e.g., forests vs. urban areas).
- Confirmations from multiple satellites.
- Land Cover type & flammability (how easily the surrounding area can burn)
Example of high Fire Confidences compared to Clusters with low cluster confidence levels
If you want to learn more about Fire Confidence, please refer to [this article](https://help.ororatech.com/fire-confidence?hsLang=en).
---
### **Understand Location-Based Patterns**
Determining the context of a detection can also help evaluate its legitimacy:
- **Forest and Grassland Areas**: Hotspot detections in these areas are more likely to represent actual wildfires due to the high flammability of vegetation.
- **Urban or Industrial Zones**: Detections in these areas are more susceptible to false positives, often triggered by buildings, machinery, or solar panels.
** Clusters located in the middle of a forest tend to be real fires.
---
### Conclusion
While false positives are an inherent part of wildfire detection, OroraTech’s Wildfire Solution provides powerful tools to help users confidently interpret and verify detections.
By considering **both Cluster and Fire Confidence** metrics, as well as the location context, you can efficiently filter out false positives and focus on legitimate wildfire threats.
- [Start Here](https://help.ororatech.com/start-here?hsLang=en#main-content)
- [Explore WFS](https://help.ororatech.com/start-here?hsLang=en#explore-wfs)
- [Get Ready to Monitor](https://help.ororatech.com/start-here?hsLang=en#get-ready-to-monitor)
- [Learn the Basics](https://help.ororatech.com/learn-the-basics?hsLang=en#main-content)
- [Detections: Hotspots & Clusters](https://help.ororatech.com/learn-the-basics?hsLang=en#detections-hotspots-clusters)
- [Understand Fire Data](https://help.ororatech.com/learn-the-basics?hsLang=en#understand-fire-data)
- [Dive Deeper: Satellites & Fire Data](https://help.ororatech.com/learn-the-basics?hsLang=en#dive-deeper-satellites-fire-data)
- [Detect, Monitor & Analyze Fires](https://help.ororatech.com/detect-monitor-analyze-fires?hsLang=en#main-content)
- [Monitor & Assess Fire Activity](https://help.ororatech.com/detect-monitor-analyze-fires?hsLang=en#monitor-assess-fire-activity)
- [Fire Spread](https://help.ororatech.com/detect-monitor-analyze-fires?hsLang=en#fire-spread)
- [Burnt Areas & Data Analysis](https://help.ororatech.com/detect-monitor-analyze-fires?hsLang=en#burnt-areas-data-analysis)
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- [Account & Settings](https://help.ororatech.com/detect-monitor-analyze-fires?hsLang=en#account-settings)
- [Additional Knowledge](https://help.ororatech.com/detect-monitor-analyze-fires?hsLang=en#additional-knowledge)
- [Integrations & Advanced Setup](https://help.ororatech.com/integrations-advanced-setup?hsLang=en)
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- [During an Active Fire](https://help.ororatech.com/during-an-active-fire?hsLang=en)
- [The Science Behind WFS](https://help.ororatech.com/the-science-behind-wfs?hsLang=en)
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