ABot-Earth 0.5: Generative 3D Earth Model
Authors: name: Ming Qian, name: Tianjian Ouyang, name: Mingchao Sun, name: Zijian Wang, name: Jincheng Xiong, name: Jiarong Han, name: Yongchang Zhang, name: Jiawei Zhang, name: Xu Wang, name: Yu Liu, name: Luyang Tang, name: Fei Yu, name: Zengye Ge, name: Mengmeng Du, name: Yuan Liu, name: Nianfei Fan, name: Song Wang, name: Yingliang Peng, name: Chunxue Jia, name: Yang Liu, name: Shiying Zeng, name: Haozhe Shi, name: Junnan Lai, name: Hongyu Pan, name: Zheng Wu, name: Ning Guo, name: Mu Xu, name: Hang Zhang
Organization: Alibaba AMAP CV Lab

We present ABot-Earth 0.5, a generative 3D framework designed to synthesize vast, seamless 3D environments from ubiquitous, geospatially referenced satellite imagery. To achieve this, we propose a novel generative model formulated directly with the 3D Gaussian Splatting (3DGS) representation. The model is trained on a diverse corpus of existing real-world urban reconstructions, learning to generate realistic geometry and textures. At inference, it synthesizes novel 3D scenes conditioned solely on satellite imagery at a scalable rate of under 10 minutes per square kilometer, while demonstrating exceptional realism. The framework is designed for accessibility, with integrated hierarchical level-of-detail (LOD) structures that permit real-time, interactive visualization on web-based map engines. This high-fidelity simulation sandbox effectively mitigates the sim-to-real domain gap, enabling critical downstream Embodied AI applications like closed-loop UAV navigation. By providing an ultra-low-cost and high-efficiency solution, ABot-Earth 0.5 significantly lowers the technical and financial barriers to large-scale 3D reconstruction and empowers the future of global digital earth visualization.