hotosm/drone-tm - Open Source PR Review Scorecard

Drone Tasking Manager - community-driven drone imagery collection.

C-Rank Grade: A (Welcoming) - 62/100

External PR Merge Rate: 60%

Response Time: -

First Timer Success: 100%

Frequently Asked Questions

Is hotosm/drone-tm welcoming to first-time open-source contributors?

hotosm/drone-tm has a recorded first-timer success rate of 100.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in hotosm/drone-tm respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 62.0 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 62.0 places hotosm/drone-tm in the A tier.

What is the external contributor pull request merge rate for hotosm/drone-tm?

The external contributor pull request merge rate for hotosm/drone-tm is 60.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in hotosm/drone-tm?

hotosm/drone-tm currently has 10 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

hotosm
hotosm/drone-tmA•Welcoming104
GitHub
Back to Explorer
hotosm

hotosm/drone-tm

104
InactiveA•Welcoming(62/100)Python

Drone Tasking Manager - community-driven drone imagery collection.

GitHub
Compare••
Jump to:

AI Maintainer Review Guidelines

Review Persona

Welcoming Community Builder

Warmth Score
8.6/10
Patience Score
8.6/10
Nitpick Rate
35%

Highly welcoming maintainers in hotosm/drone-tm. Prompt code reviews with positive guidance for new contributors.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
-
No reviewer activity recorded

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
60.0%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
100.0%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
9 core
Highly collaborative maintainer core
Diagnostic Health HUD
60.0%
Merge Gauge
100.0%
1st-Timer
Community Vibe54/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for hotosm/drone-tm
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/hotosm/drone-tm)](https://getmerged.abhishekco.de/hotosm/drone-tm?utm_source=github&utm_medium=badge)

Active Good First Issues (5)

View on GitHub

Related to #853 and disaster response use cases. An interesting workflow for response targeting: Often there are other aerial vehicles like helicopters around. Something like a GoPro can be strapped to the bottom with a photo interval timer. The imagery probably can't be stitched into a single ortho, but can be used for targeting response areas. Pt1: Hosting the captured photos Could go into OAM, but it mostly focuses on stitched orthos... Any way we could collate the photos into a single product, or find a simple way to link them all together without hundreds of OAM STAC items? Food for thought! Pt2: fAIr workflows for targeting Based on criteria, we could run fAIr models on the imagery. E.g. identify bridges for transport connectivity post earthquake. E.g. identify building damage to help target settlements most badly affected. This would then feed decision making for where to send resources, and in the case of DroneTM, where to fly imagery to get a better picture of the respons

📅 Opened Sep 23, 2026💬 1 comment
Quality: 90/100Contribute

E.g. Flying a city every year for change detection - every year clone the prev project. During disaster response, we want fresh imagery every few days to assess the situation on the ground: clone the same project for different dates. Common use case, simple implementation, and nice helper to those that need to do this.

📅 Opened Sep 23, 2026💬 1 comment
Quality: 90/100Contribute

Drone monitoring platform Main use case would be coordination during disaster response, but also useful for government agencies / avitation authorities to keep track of drones flying in a country. Possible requirements Where drones located How many drones imported via custom offices Who are drone pilots, who is using them Mobile version of app offline/online Arrangement with gov for liability etc This, of course, is a big risk for liability, if used by aviation authorities to plan other aerial vehicle activities based on the drone / operator locations. Drone location tracking An approach such as https://github.com/spwoodcock/nepal-pilot-dashboard WhatsApp + ChatMap --> locations of the pilots, which approximates locations of drones within a few km radius. Self reported locations Live tracking drone locations Notes from a slack channel. For that we can use the DJI v5 SDK (are they using DJI drones that are supports in the README there?). We could use this pre-built wrapper around the

📅 Opened Sep 23, 2026💬 3 comments
Quality: 90/100Contribute

I defined a no-fly zone for this project - a rectangle along the top border of the project because the project borders a military barracks to the north. Two issues: The no-fly zone is not visible on the project overview map (task selection map) When creating the flight plan there are flightplan points that enter deep into the no-fly zone that I defined. This is high risk

📅 Opened Sep 15, 2026💬 2 comments
Quality: 90/100Contribute

Specs: https://www.potensic.com/atom-3-specs.html 1/1.3-inch CMOS Quoted battery life 40 mins. More details: #863 Analysis of the files: It uses global.json and a xxx.json file for the waypoint missions, same as Atom 2. The global.json is exactly the same. The xxx.json file is slightly different: No ;[] POI suffix. Atom 2 mission files are [waypoints];[poi_list]; the Atom 3 file is a plain JSON array ending }] - no semicolon, no POI array at all, no trailing newline. The main change here. No fileName key on waypoints. Atom 2 always writes one (point_<ts>.jpg, a thumbnail for the Eve UI); Atom 3 omits the key entirely. Thumbnails are aesthetic only, so not an issue we need to action. Two enum values not previously documented: yawType: "TO_WAYPOINT" (with yaw: 0 throughout) and zoomType: "HAND". Atom 2 captures only ever showed DEFINE for both. Most likely these are mission settings the selected manually in Potensic Eve in the example provided by @zigulicd? Perhaps it means 'set yaw

📅 Opened Aug 18, 2026💬 3 comments
Quality: 90/100Contribute
Looking for more Python beginner tasks?Explore Python GFI

Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

3 ratings required
Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for hotosm/drone-tm

When evaluating whether to contribute to hotosm/drone-tm, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of hotosm/drone-tm acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 60.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to hotosm/drone-tm

01

Is hotosm/drone-tm welcoming to first-time open-source contributors?

hotosm/drone-tm has a recorded first-timer success rate of 100.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 62.0 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 62.0 places hotosm/drone-tm in the Welcoming tier.

04

What is the external contributor pull request merge rate for hotosm/drone-tm?

The external pull request merge rate is 60.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in hotosm/drone-tm?

Yes, hotosm/drone-tm currently has 10 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for hotosm/drone-tm are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.