Xiaoyu Hou 侯小雨
- Email: firstname.lastname@example.org
- Thesis title: Cultural Heritage Protection: Innovative tools and methods
- Supervisor: Professor Gehan Selim
Xiaoyu Hou (Tel: 18866680916) is a first-year PhD student at the Architecture & Urbanism Research Group. He is under the supervision of Professor Gehan Selim, who is also from the School of Civil Engineering. He graduated from the University of Leeds with a Merit in MSc GIS and from Xi'an University of Science and Technology with a Distinction in BSc Geography. With a strong interest in post-natural disaster cultural heritage preservation, he started his new journey in a relatively new area with his background in ArcGIS mapping, data management and in-field surveying experiences.
Research &Learning experience
Investigation of the Energy Consumption change between 2013 and 2016
Module project supervised by Dr Nick Hood, using energy-consuming data to indicate high consumption areas and detecting economic relationships, helping governments carry out carbon track proof and limitation policy. Developed advanced data processing/cleaning ability and building classification systems (Excel, ArcMap etc.). More importantly, that was my first attempt to connect my report to academic and other industries (London local authorities/government). The final report was given 65/100, and the poster was marked as an excellent demonstration of the work for the good use of inserts from the report to act as evidence/example and good presentation skills.
England housing price spatial variation and its influencing factors: A comparison of geographically weighted regression and the global OLS method
Master's degree final dissertation supervised by Dr Nick Hood. Gained experience in nationwide small area study and data aggregation from different census data. All geodemographic variable data from census 2011 has to match the level of aggregation in house price data: compared Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR). Thorough understanding of residual handling/model fit and spatial non-stationarity when processing housing data.
- Advanced in ArcMap, QGIS, SPSS, Tableau, ERDAS IMAGINE, MapInfo Pro and familiar with Python, R
- Data Visualization and Analysis, Digital Image Processing, Environmental Assessment, Geodemographics and Neighbourhood Analysis
Xiaoyu Hou's research mainly focuses on the rebuilding of the local heritage sites after natural disasters. The reconstruction is not only limited to the physical site itself but also the cultural context. As resilience is a broad definition and can be differently defined within different countries and social backgrounds, the local community's voice tends to be neglected and the experts' theory based on a wider background might fail to fill the need of residents. Also, by comparing the different cultural heritage resilience, people might understand different aspects of cultural heritage protection and the multiple meanings of resilience. Utilizing Geographical Information System techniques and interviews with residents, the mixed-method approach might offer a new path for people to learn about the stricken area's cultural heritage protection in diversity world.
His current research is focused on cultural heritage and community resilience, particularly in disaster-prone areas. In terms of hazard mitigation, the resilience study is currently vague. Western academics have introduced the concept of resilience and applied it to heritage protection and regional development, but there are still few practical examples, with the majority being theoretical justification. As a result, implementing this in rural China has global implications in the resilience field. The approach taken from the start of data collection to the end of data collection may differ from previous resilience studies in Western. Consider my project: the area of interest is in rural China, and the ancient building border data is not officially documented. Meanwhile, many satellite image websites, such as Planet, do not have data in China. To solve the problem, shapefiles would be created using Google Earth and the ArcGIS Pro base map. The project uses a mixed-method approach after obtaining border data. First, building resilience can be detected using the dialogic method as the building map is created. The assessment is made through interviews with residents. Unlike traditional quantitative methods, the perceptions of residents are summarised and demonstrated using maps. Workshops and questionnaires would also be used to investigate their own hazard experience and how resilience is perceived and applied after the extreme event.
- 2019-2020 University of Leeds, MA in MSc GIS
- 2015-2019 University of Xi'an University of Science and Technology, BA in Physical geography
- Royal Meteorological Society Yorkshire Branch (since 24/02/2020)
- Royal Geographical Society (RGS) official licensed ambassador (since Feb. 2020)