In the context of urban landscape renewal and sustainable development, the use of EEG technology to measure and assess landscape fatigue and its frequency has become a preliminary issue in landscape perception research and practice, aiming to elucidate the characterization patterns and underlying logic of landscape fatigue. This study establishes an analysis framework for landscape fatigue and scenes EEG, builds a brain fatigue measurement model, and conducts an EEG experiment for the frequency statistics, analysis, and discussion of landscape fatigue. First, taking Xiangyang City Wall Park as a case, four elements were selected to organize single and composite scenes, and five experience rounds of EEG experiments were set up to collect the corresponding EEG and transform it into scene brain fatigue data. Moreover, ANOVA, correlation analysis, etc. are combined and used to build a brain fatigue measurement model to quantitatively describe the tendency, amplitude, consistency, and significance indices of landscape fatigue. Lastly, the fatigue characteristic index is used to calculate the interaction effects of multi-element scenes to verify and deduce the frequency rules of landscape fatigue. According to the research results, the brain fatigue value increases gradually with the rise in the landscape experience frequency. Brain fatigue has positive correlations with the landscape experience frequency and becomes stable after the third round of landscape experience. Additionally, the number of scene element types and the cumulative brain fatigue of repeated experience showed an inverted Ushaped relationship, and the collaborative design between elements can effectively alleviate the effect of landscape fatigue. These results verify the existence of “Third Time's the Fatigue” in landscape experience, and relevant rules and conclusions can increase the depth of landscape fatigue research and provide EEG theoretical foundation, experimental optimization paths, and profound professional knowledge for evidence-based research on routine experiential landscape.