Invasive plants constitute one of the major causes of biodiversity loss, and its monitoring plays an important role in the management of coastal ecological systems. This study aimed to apply high precision 3D mesh-model and digital orthophoto map (DOM) derived from unmanned aerial vehicle (UAV) multi view images to monitor the invasive plants over coastal mountain region in Shenzhen, China. To overcome the limitations of RGB images, the Gray-level Cooccurrence Matrix (GLCM) features of images were analyzed and combined with spectral features to obtain the 2dimentional distribution of invasive plants first, using an object-based image analysis technique. A fine analysis was then introduced to obtain a more accurate 3-dimentional distribution of invasive plant by combining 2-dimentional distribution of invasive plant and 3D mesh model. the results have shown that: (1) Although the UAV RGB image has limited spectral information, the low-altitude makes the spatial resolution very high, which can effectively enhance the effectiveness of the texture in mapping invasive plants, and finally achieved an overall accuracy of 93.25%. (2) The use of 3D mesh model, on the one hand, could significantly alleviate the impact of undulatory terrain over mountain area and improve the classification result; on the other hand, it could better visualize the final results, helping us more intuitively understanding the distribution of invasive plants. This study demonstrated the great potential of UAV-derived 3D mesh model in accurate natural resource management over mountain areas.