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The coverage of drone remote sensing images is wide, making it difficult to distinguish between building areas and background areas. Therefore, a measurement method for building areas using drone remote sensing images based on parallel convolutional neural networks is studied. Obtain drone remote sensing images and complete remote sensing image preprocessing through static output, image fusion, defogging, and other processes. Construct a parallel convolutional neural network, extract the edge features of the building area in drone remote sensing images through network training propagation, and recognize the building area in drone remote sensing images through feature matching. Combined with the area calculation results, obtain the measurement results of the building area. After precision performance testing experiments, it was concluded that the proposed method reduced the measurement errors of building areas by 0.505km2 and 0.305km2 respectively compared to traditional area measurement methods in foggy and non foggy environments, indicating that the measurement results of this method are more reliable.