Mapping of user-perceived landscape types and spatial distribution using crowdsourced photo data and machine learning: Focusing on Taeanhaean National Park

User perception of protected areas is a valuable set of information for monitoring and managing those areas. To refer to the management direction of protected areas, various studies have been conducted to identify users' perspectives and find their needs. This study aimed to propose a method to analyze the landscapes perceived by users in Taeanhaean National Park and their spatial distribution by applying crowdsourced photos created and uploaded based on user experiences, Google Vision API, Latent Dirichlet allocation, and the self-organizing map (SOM) machine learning technique. According to the results, Taeanhaean National Park contains 12 major landscape types that include coastal landscapes, forest landscapes, sand dunes, horizontal land landscapes, and urban landscapes. Using crowdsourced photo data, this study was able to identify landscape types that were unrecognized from the perspective of experts or officials and was also able to map the distribution of each landscape type based on the photos' location information. Furthermore, this study aimed to derive the major bases of several landscape types in the large study area through SOM analysis. By using social media data to analyze users' preferences and perceptions of national parks and large protected areas, this study proposed a potential indicator for a user-participatory landscape monitoring system. Management implications: This study aims to help formulate a management plan considering users' preferences and perceptions of protected areas using crowdsourced photo data. In the analysis stage, an unsupervised learning method, a type of machine learning, was used to derive landscape areas containing the characteristics of various landscape elements. The study has elucidated the perception of new landscape resources and spaces that the existing analysis could not reveal. Mapping the landscape areas can contribute to the monitoring system of the protected area.center dot Taeanhaean National Park comprises 12 Landscape types by analyzing users' perceptions using crowdsourced photo data.center dot Four landscape areas were identified using a self-organizing map.center dot Social media data and machine learning can be useful for monitoring users' perceptions of national parks.