The large-scale acquisition and widespread application of remote sensing image data have led to increasingly severe challenges in information security and privacy protection during transmission and storage. Urban remote sensing image, characterized by complex content and well-defined structures, are particularly vulnerable to malicious attacks and information leakage. To address this issue, the author proposes an encryption method based on the enhanced single-neuron dynamical system (ESNDS). ESNDS generates high quality pseudo-random sequences with complex dynamics and intense sensitivity to initial conditions, which drive a structure of multi-stage cipher comprising permutation, ring-wise diffusion, and mask perturbation. Using representative GF-2 Panchromatic and Multispectral Scanner (PMS) urban scenes, the author conducts systematic evaluations in terms of inter-pixel correlation, information entropy, histogram uniformity, and number of pixel change rate (NPCR)/unified average changing intensity (UACI). The results demonstrate that the proposed scheme effectively resists statistical analysis, differential attacks, and known-plaintext attacks while maintaining competitive computational efficiency for high-resolution urban image. In addition, the cipher is lightweight and hardware-friendly, integrates readily with on-board and ground processing, and thus offers tangible engineering utility for real-time, large-volume remote-sensing data protection.