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    How Repeatable Waypoint Flights Create Seasonal Drone Transitions

    How Repeatable Waypoint Flights Create Seasonal Drone Transitions

    • by Stefan Gandhi

    One of the most striking aerial techniques doing the rounds at the moment is the seasonal transition shot, where a single continuous camera move appears to travel through winter, summer and night in one unbroken take. A recent video shared on the r/drones community shows exactly how it is done, and the secret is not clever editing alone. It comes down to repeatable waypoint flights flown over the same route months apart, then aligned and blended using photogrammetry.

    What u/Kind_Taro_9674 Built

    Reddit user u/Kind_Taro_9674 posted the latest video in an ongoing Montreal project on 7 June 2026. A few months earlier they had shared a winter day-to-night transition video created from repeatable waypoint flights over the city, and this clip takes that idea further. They flew the same route again in summer and at night, then aligned all three flights and combined them into a single continuous camera move that runs winter day, to summer day, to summer night.

    What lifts the result above a standard timelapse is the method behind the blends. As u/Kind_Taro_9674 explains, the transitions are based on photogrammetry and depth rather than simple dissolves. That allows different parts of the city to change at different times depending on their 3D position, so the season and time of day appear to sweep through the scene and follow the actual buildings and streets rather than washing across a flat frame.

    Why Repeatable Waypoint Flights Are The Key

    The whole effect rests on flying the exact same path more than once. A waypoint mission lets you record a route as a series of GPS points, with the drone storing the position, altitude, speed and camera angle at each one. Once that mission is saved, the drone can fly it again automatically on demand, whether that is the next day or several months later in a different season.

    This repeatability is what makes the frames line up. If each flight were flown by hand, tiny differences in path and timing would make the clips impossible to align cleanly. By letting the drone repeat the route precisely, the pilot captures matching footage of the same scene under completely different conditions, which is the raw material the transition needs.

    Using Photogrammetry For Depth-Based Transitions

    Photogrammetry is the process of building a 3D model of a scene from many overlapping photographs. Software identifies common points across the images and works out the geometry, producing a model where every part of the frame has a known position in space, including its depth from the camera.

    That depth information is what makes the Montreal transitions special. Instead of crossfading the whole image at once, the pilot can drive the blend using distance and position, so nearer rooftops might shift to summer while the far skyline is still in winter. The change ripples through the scene in three dimensions. It is a far more convincing result than a dissolve, and it is only possible because the repeatable flights gave consistent footage to reconstruct from.

    How To Plan Your Own Seasonal Transition

    You do not need a Montreal skyline to try this. Start by choosing a stable vantage point and an interesting route with strong foreground and background depth. Fly it as a saved waypoint mission using a drone that supports automated waypoint flight, and make a note of your camera settings so you can match them later.

    Then comes the patient part. Re-fly the identical mission in a different season or at a different time of day, keeping exposure, white balance and frame rate as consistent as you can. If you want depth-based blends rather than simple fades, capture overlapping stills along the route so you can build a photogrammetry model in post. Align the clips, mask the transitions by depth, and you have the makings of your own seasonal move. The technique rewards planning across weeks or months, so it suits anyone happy to revisit the same spot over time.

    FAQs

    What is a waypoint flight on a drone?

    A waypoint flight is an automated mission where the drone follows a pre-set route of GPS points, holding the same altitude, speed and camera angles each time. Because the mission is saved, you can re-fly the identical path on demand, which is essential for matching footage captured on different days or in different seasons.

    What is drone photogrammetry?

    Drone photogrammetry is the process of building a 3D model of a place from many overlapping aerial photographs. The software calculates the geometry of the scene, giving each point a position and depth, which can then be used for mapping, surveying or creative effects like depth-based transitions.

    Can a drone fly the same route automatically?

    Yes. Drones with waypoint flight features can record a route and repeat it automatically as many times as you like. This is what makes seasonal transition projects possible, since every pass captures the same framing under different conditions.

    How do you make a day to night drone transition?

    Fly the same waypoint route in daylight and again at night, keeping your camera settings consistent, then align the two clips in editing software. For a more advanced result, use photogrammetry to blend the footage by depth so the change moves through the scene rather than fading across the whole frame at once.

    Final Thoughts

    The Montreal project is a brilliant reminder that the most impressive aerial work often comes from method rather than expense. Repeatable waypoint missions give you matching footage across seasons, photogrammetry gives you the depth to blend it convincingly, and patience ties the two together. Credit to u/Kind_Taro_9674 for sharing a clear breakdown that other pilots can learn from and build on.

    If you fancy trying a seasonal transition of your own, the waypoint-capable DJI Mavic 4 Pro is a superb place to start, available now at the Coptrz official online store.


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