From SketchUp to AI Animation | Urban Analysis Workflow Explained

In this video, I'll show you how I created these urban analysis diagrams and animations using AI. To build the animation properly, I break it down into five scenes. The first scene starts flat, then transitions into growing buildings. In the second scene, the buildings shift into an isometric view, where I add color, labels, and begin the retail analysis. The third scene transitions from the retail analysis into an open space study diagram. Then we move into the final rendering stage, where the diagram evolves into a more realistic visualization. And finally, I add a smooth camera rotation to complete the animation. Let's start with the first scene. For these animations, I'm using Google Flow. Later in the video, I'll also compare it with a few other AI tools. To start, I upload two images, the start frame and the end frame. Both are exported directly from my SketchUp model. These two frames define the transformation, moving from a flat base to a growing building mass. Then I enter a prompt describing the motion. Buildings grow smoothly upward from their footprints and stop exactly at the final heights shown in the reference image. Once that's processed, we get our first scene. The buildings rising cleanly and stopping precisely at the intended height. Next, we move to scene two. I use the frame to video function again. The start frame is an empty urban model, and the end frame is the space analysis diagram I generated with NanoBanana. I import both frames into Veo 3, enter a simple transition prompt, and generate the second video. For scene three, I follow the same process. I upload two images, the start frame and the end frame, and then enter my prompt to define the transition. Scene four is pretty simple. The diagram naturally transitions into a more realistic rendering, blending from analytical graphics into a spatial visualization. For Veo 3, I usually prefer to write a more detailed prompt to get better control over the motion. In the last scene, I rotate the camera to reveal the other side of the urban bird's eye view, which makes the animation feel more dynamic and immersive. This time, I only use a single image and guide the movement entirely through the prompt. The rendering I use in Veo 3 was also generated with NanoBanana. I've shared many other cases where I use Gemini to generate diagrams, renderings, plans, and even 3D models. You can find more detailed examples in my other videos. Gemini does have built-in video generation, but I don't use it here. I keep it turned off. Personally, I prefer using the Veo 3 platform for animation because it gives me more control over motion and camera behavior. Finally, I want to share a quick comparison with Ximeng AI and Kling AI. I've tested both in my own practice, and they're both solid tools. Ximeng is more affordable on the basic plan, but it tends to be a bit slower in processing. So that's my full workflow for creating urban analysis diagrams and animations using AI. From SketchUp models, to diagrams generated with NanoBanana, to animations in Veo 3, and even testing tools like Gemini, Ximeng, and Kling, this is how I build a complete visual narrative step by step. AI doesn't replace design thinking, but it definitely accelerates the process when you know how to control it. If you found this helpful, let me know in the comments, and tell me which tool you'd like me to test next. Thanks for watching, and I'll see you in the next tutorial.