The invention discloses a remote sensing image super-resolution land cover mapping method based on a street view image. Firstly, the remote sensing image is preprocessed, and the score image is obtained by soft classification method; at the same time, the convolutional neural network model (Convolutional Neural Network, CNN for short) and spatial positioning technology are used to extract the feature information of the street view image. Secondly, according to the set magnification factor, the ground objects in the street view image are located, and the area ratio of the sub-pixels they occupy is calculated. Then, considering the category and location attributes of the ground objects in the fractional image and the street view image, the spatial dependence index of the sub-pixel is calculated. Finally, according to the spatial dependence index of the sub-pixel and the area ratio of the sub-pixel, the class membership degree of the sub-pixel is obtained, and then the super-resolution land cover mapping result is obtained. The invention constructs a theoretical model of a remote sensing image super-resolution land cover mapping method based on a street view image, which can fuse high-resolution image surface feature information, and the mapping result has high precision.