Landmarks play an important role in spatial information transmission, especially for wayfinding navigation. Numerous studies have shown that the inclusion of landmarks in route tasks can effectively reduce steering errors. How to incorporate landmarks into navigation systems and break the barrier of using distance information as the indicator to guide users in wayfinding is currently a difficult problem to solve. And we-map provides a platform for users to produce and disseminate map content. Because we-map does not distinguish between mapmakers and map users, it lowers the threshold for mapping and enables users to have self-make maps. In the process of route mapping, we-map platform can provide a collection of landmarks for users to choose from and use them to complete their wayfinding, enabling the solution to the challenge of incorporating landmarks into navigation systems. In order to extract we-map landmarks accorded with people's spatial cognition, the method of extracting landmarks by user-generated content is proposed. First, there are three indicators (public awareness, city centrality, and individual characteristic value) that are calculated separately, and each of them is obtained by the entropy value method. Then, landmarks are extracted in a hierarchical manner in term of the difference in the significance of landmarks to establish a set of landmarks for serving the users of the we-map. Last, the user-generated landmarks are collected during the process of publishing, sharing, and disseminating the we-map to enrich the landmark library, aiming at realizing secondary dissemination about the extraction of landmarks from user-generated contents. The experiment selects POI data of An Ning District in Lanzhou City to calculate landmark salience, selects landmarks at different levels according to different scales, designs tasks for participants to describe routes and complete connections between landmarks, collects usage landmarks, forms user-generated content to disseminate landmark data, and draws personalized routes that meet different user needs. This study simulates the process of route-finding cartography using landmarks by we-map users to pave the ground for personalized navigation on the we-map platform. The experimental results show that the content generated by using users' shared service data effectively solves the problem of acquiring and timely updating landmark candidate sets, expresses the user's cognitive expressiveness to the greatest extent, and reduces the burden of wayfinding for pedestrians walking out. This study is applied to daily wayfinding, where we-map users participate in constructing and sharing service data, forming spontaneous dissemination of user-generated content, timely update, and dissemination of landmark data, providing reference for rapid we-map drawing, and improving wayfinding efficiency.