School of Architecture + Design

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Browsing School of Architecture + Design by Author "Chen, Mingze"

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    Examine an Intelligence Education Framework of Landscape Architecture (EFLA) Based on Network Model of Technology in Landscape Architecture (NMTLA)
    Ge, Mengting; Kong, Jie; Yang, Qiuyi; Chen, Mingze; Wang, Wenji (MDPI, 2023-07-19)
    The discipline of Landscape Architecture (LA) is currently expanding its disciplinary boundary. The supporting Technology in LA (TLA) is always evolving and optimized to solve environmental problems. Considering the uncertain classification of the current LA knowledge for education and the importance of technology in LA education, a refined education framework of LA is needed. This research first established a Network Model of Technology in LA (NMTLA) using Network Analysis (NA) and expert interviews. Then, this research proposed an Education Framework of LA (EFLA) based on the NMTLA. To build the NMTLA, this research identified 23 key categories of TLA through content analysis of secondary research. Then, the expert interview and network theory were used to analyze and visualize the relationships among the categories. By examining the degree centrality, closeness centrality, and betweenness centrality of different TLA, this study developed an EFLA which summarizes the twenty-three categories of TLA into four domains: core techniques, applied technologies, integrated technologies, and specific technologies. This study also proposes a series of suggestions for how to apply different categories of TLA in today’s and future LA education. The proposed NMTLA and EFLA in this research can contribute to the development of future LA higher education. They also can potentially address the Sustainable Development Goals (SDGs) in LA education and industry. However, the scope of this study is currently limited to LA education in the USA, which could be expanded to include a worldwide perspective in future research. To enhance the validity of the conclusions, a larger sample size for interviews should be employed in further studies.
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    Examining the Conceptual Model of Potential Urban Development Patch (PUDP), VOCs, and Food Culture in Urban Ecology: A Case in Chengdu, China
    Shen, Xiwei; Chen, Mingze; Ge, Mengting; Padua, Mary G. (MDPI, 2022-08-26)
    In China, traditional food is a significant element of culture that affects human behaviors. The point of interest (POI) of traditional food restaurants’ location and their volatile organic compounds (VOCs) emissions affect the urban ecology. Rather than examine potential urban development patch (PUDP) based on land use data, the perspective of this paper is to examine the PUDP, air quality, and food culture in urban ecology in Chengdu, China. Methods: First, the research identifies three types of PUDP models (open PUDP, landscape PUDP, and conflict PUDP) with the weighted overlay of land use data, then uses machine learning to examine the relationship between PUDP, POI of traditional food restaurant, and VOCs. Results: The study generates three types of PUDP which are open PUDP, landscape PUDP, and conflict PUDP. VOCs and POI of traditional restaurant have a strong correlation, and both have a significant negative correlation with open PUDP. However, the landscape PUDP and conflict PUDP do not show an obvious relationship with food POI and VOCs. Conclusion: The results indicate that the future urban ecology should consider restaurant location, VOCs from restaurants, and their relationship to urban land use data as they have a strong relationship.
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    Exploring Tourists' Multilevel Spatial Cognition of Historical Town Based on Multi-Source Data - A Case Study of Feng Jing Ancient Town in Shanghai
    Wang, Ling; Ding, Jiahui; Chen, Mingze; Sun, Yuan; Tang, Xueyun; Ge, Mengting (MDPI, 2022-11-01)
    Conducting research on the spatial cognition of tourists in historical towns helps to balance cultural heritage protection and tourism development. However, the current tourist cognition research is not comprehensive enough in terms of data sources, time dimension, and spatial objects. This research takes Fengjing Ancient Town in Shanghai as an example, and through multi-source data analysis explores how tourists’ perception and cognition of the attractions changes, discusses the impacts of characteristic of spatial system and elements on perception, and then establishes a spatial cognition analysis framework involving time dimension, cognitive depth, and spatial type. On-site aerial photos, Sina Weibo check-in data, tourist memory maps, and photos from tourism websites were used to classify tourists’ spatial cognition through content analysis, theme classification, and GIS spatial analysis. This research finds that tourists have formed three cognitive levels in the travel process, from “initial spatial consciousness” to “place memory” then to “imagery perception”. Meanwhile, space is the most important object of tourists’ cognition, and it is also the carrier of other intangible cultures. In terms of spatial cognition and ancient town tourism, this research finds the tourists’ spatial cognition of Fengjing Ancient Town is related to the main river and main tourist routes that represent the image characteristics of the ancient town. This research shows that clear boundaries of tourism space, richer folk activities, and more sequential tourism routes could help tourists form a more systematic spatial cognition. Based on the findings, this research also establishes an analysis and application framework of tourists’ multilevel spatial cognition to provide optimization suggestions for development of tourism.