Image footprint coverage

[shreya-hegde]

What type of PR is this? (check all applicable)

• 🍕 Feature
• 🐛 Bug Fix
• 📝 Documentation
• 🧑‍💻 Refactor
• ✅ Test
• 🤖 Build or CI
• ❓ Other (please specify)

Related Issue

Fixes #819

Describe this PR

What changed

• Added rectangular image footprints to task verification.
• Coverage now uses the union of those footprints instead of over-generous point coverage.
• Draws footprint outlines on the map.
• Clicking an image highlights its matching footprint.
• Added FC9313 for DJI Mini 5 Pro.

Notes

• Footprints use project altitude first, then EXIF relative altitude.
• Avoided EXIF absolute altitude because it is height above sea level and made coverage too large.

Tested

• Tested locally with Mt Agung data.
• Task Feat: Update task locking flow with more detail on tasks #155 had 10 assigned images.
• Coverage changed from 100% to 14%.

AI Tool Usage

• No AI tools were used
• [ x] AI tools were used (complete below)

If AI-assisted:

• Tool(s) used: Codex
• What was generated: Draft code changes, explanations, and debugging guidance.
• What you reviewed and changed: Reviewed the code, ran local/Docker tests, checked UI behavior, and adjusted altitude/footprint logic.

Screenshots

If applicable.

Alternative Approaches Considered

Did you consider other approaches? Why this one?

Review Guide

Notes for the reviewer. How to test this change?

Main things to look at:

• image_footprints.py: footprint size/shape calculation and union coverage logic.
• image_classification.py: task verification now uses footprint coverage instead of the old circular buffer coverage.
• TaskVerificationModal.tsx: footprint outlines are drawn on the map and selected image footprints are highlighted.

Things I’d especially like feedback on:

• Whether using project altitude first, then EXIF relative altitude, is the right assumption.
• Whether the Identify Flight Gaps flow should be updated to use the same footprints.

Checklist

• [ x] I have read the Contributing Guide
• [ x] I have read the Code of Conduct
• [x ] PR is focused and small
• [ x] Tests are included or updated
• [ x] I understand all code in this PR and can answer questions about it
• [ x] No secrets, credentials, or sensitive data are included
• [x ] Commit messages are descriptive
• Related docs and screenshots are updated

[optional] What gif best describes this PR or how it makes you feel?

https://giphy.com/gifs/square-triangle-shape-slap-V6kvt4UVqfHha3Eb19 (cuz the rectangles/squares are the superior shapes in image coverage)

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[shreya-hegde]

I have read the CONTRIBUTING.md document and I hereby sign and agree with the guidelines

[spwoodcock]

Really nice work!! This is looking great 😄

Left some small comments. The main one is about the mercator project towards the poles, which will distort the footprint calcs a lot

[spwoodcock]

This will be an EPSG:3857 (web mercator) coordination, but the footprint calculated below is true ground meters, so the calculations as we get closer to the equator will be increasingly incorrect.

I would propose a simple solution is to correct by the 1/cos(latitude) adjustment that web mercator uses:

center = transform(projector.transform, shape(image["location"]))
x, y = center.x, center.y

# EPSG:3857 stretches ground distance by 1/cos(lat). Scale the rectangle
# so its footprint is stretched to match the mercator projection.
lat_deg = image["location"]["coordinates"][1]
mercator_scale = 1 / math.cos(math.radians(lat_deg))
half_width = (width_m / 2) * mercator_scale
half_height = (height_m / 2) * mercator_scale

[spwoodcock]

Both these tests uses a 0,0 coord, so won't be affected by the web meracator stretching that I mentioned.

It would be good to add an additional test at say 45 latitude, to ensure our fix handles it well.

(perhaps add the tests first, run the test and see it fail, apply the fix, run again and see it pass 😄 )

[spwoodcock]

This is great 👍

We calculate coverage in this endpoint, but also for the entire project in get_project_coverage.

It would be great to refactor the usage there to also use this updated code, so the project level coverage is calculated correctly (merging this as-is would cause two different values between the two implementations. The old implementation can be removed / cleaned up)

[spwoodcock]

**any way we could consolidate these two footprint calcs, so we only have to do it once per image?