Abstract: In the context of high-quality development and stock renewal of urban environment, the accurate diagnosis of emotion perception in built environment has become the research basis for scientific cognitive development and emotion measurement of contemporary landscape architecture. “Arousal-valence” is a scientific representation of environmental emotion. Gone through the stages of emotion recognition and element analysis, relevant electroencephalogram (EEG) researches have progressed to the algorithm model stage, and provided core concepts and technical means for quantitative analysis and objective evaluation of landscape emotion. This research establishes a correlation mechanism between scenescape and EEG-based emotion and, taking Xiangyang Weidong Plant as an example, summarizes the observation elements of typical built environment. Moreover, based on EEG measurement experiments and data processing, the research conducts a cluster analysis of emotion arousal and valence level of landscape elements. It also integrates relevant algorithms such as the entropy weight method (EWM), grey relational analysis (GRA), technique for order preference by similarity to ideal solution (TOPSIS) and obstacle factor to develop the Scenescape EEG GRA-TOPSIS model, based on which obtains an emotion index decision matrix and conducts an evidence-based analysis. Relevant research results can provide basic EEG analysis methods and referable and scalable technologies for landscape emotion assessment.