The invention discloses a remote sensing image classification method and system based on self-adaptive spatial information. The method comprises the steps of obtaining a remote sensing image; Performing initial classification on the remote sensing image by adopting a fuzzy C-means algorithm based on a Markov random field to obtain an initial fuzzy membership matrix; Calculating spatial attractionbetween a current central pixel and each neighborhood pixel in the remote sensing image under the current iteration frequency b by utilizing a spatial gravitation model; Performing edge detection on the remote sensing image by adopting a Sobel operator to obtain spatial structure characteristics; Calculating an edge coefficient of the current central pixel by adopting a gradient reciprocal smoothing method according to the spatial structure characteristics; Constructing a Markov random field with adaptive weight according to the space attraction and the edge coefficient; And combining the Markov random field with adaptive weight with a fuzzy C-means algorithm to determine a classification result of the remote sensing image. According to the method, the problem of boundary pixel and spatialinformation weight coefficient estimation can be effectively solved, and the classification precision is improved.