Remote sensing technology has been widely applied in island identification in recent years, but the automatic identification method for island identification has several problems, such as low precision and poor timeliness. Because of these problems, a method for rapid identification of island by improving deep convolutional neural network (DCNN) was proposed. The improved method contains two aspects. Firstly, adding a 1×1 convolution kernel as the bottleneck unit in the convolutional layer, it reduced the dimension of remote sensing images. Secondly, a resampling method has introduced in the pooling layer to perform feature compression on the target features. Taking 300 scenes of Landsat-8 remote sensing image as an example data, the improved method was compared with CNN model and RCNN model by identifying the islands. The results showed that the improved method reduced the computational time of island identification and improved the accuracy of island identification. Based on the experimental results, the model is more suitable for automatic island identification of remote sensing images.