Best Practices
Get the most accurate results from Oceanir's AI geolocation platform
Optimize Your Analysis
While Oceanir's AI is highly capable, following these best practices will help you get the most accurate and reliable geolocation results. The quality and content of your input images significantly impact analysis accuracy.
Best Practices
Use Clear, High-Quality Images
Higher resolution images with clear details provide more visual information for the AI to analyze.
Include Landmarks or Distinctive Features
Buildings, signs, bridges, and other identifiable features help pinpoint exact locations.
Capture Wide-Angle Views
Broader perspectives give the AI more context about the surrounding area.
Choose Daylight Photos When Possible
While Oceanir handles night images well, daylight photos generally provide the most detail.
Select the Correct City
Using the right city-specific page (Miami, LA, or NYC) ensures the best analysis results.
Verify Results on the Map
Always use the interactive map to confirm the identified location makes sense.
What to Avoid
Don't Use Heavily Cropped Photos
Cropping removes contextual information that helps with accurate location identification.
Avoid Extreme Close-Ups
Photos focused on small details lack the broader geographic context needed for analysis.
Don't Rely on Indoor-Only Images
Interior shots without windows or distinctive features are difficult to geolocate.
Avoid Heavily Filtered Images
Filters and heavy editing can distort visual features that the AI uses for analysis.
Pro Tips
Image Quality Tips
- Use images with at least 1920x1080 resolution for best results
- Ensure good lighting and minimal blur
- Include the horizon or skyline when possible
- Capture multiple angles of the same location if available
Location Identification
- Look for street signs, building numbers, or business names in the image
- Architectural styles can help narrow down neighborhoods
- Natural features like waterways or mountains provide valuable context
- Consider the angle of sunlight to help determine direction
Understanding Results
- Confidence scores above 95% indicate very high certainty
- Review the analysis explanation to understand how the location was identified
- Use street view to verify the identified location matches the image
- Consider multiple factors if the confidence score is below 90%
Example Scenarios
Ideal Scenario
A high-resolution daylight photo of a Miami street corner showing building facades, street signs, and distinctive architectural features. The image includes the skyline in the background and clear visibility of nearby landmarks. This type of image provides optimal conditions for accurate analysis.
Challenging Scenario
A heavily cropped, low-resolution interior photo with only a small window showing a distant building. Limited context and visual information make precise geolocation difficult, potentially resulting in lower confidence scores or requiring multiple analysis attempts.
Ready to Analyze?
Apply these best practices and start using Oceanir for accurate geolocation analysis.