Li Maosu

The University of Hong Kong | HKU · Department of Urban Planning and Design

[Outstanding Paper Award] Window view is an intimate medium between occupants and nature, especially in high-density cities like Hong Kong; and thus belongs to the quality of a house or apartment. In literature, researchers found that window views of nature are vital to the occupants’ physical and psychological health and productivity improvement....

Every windowed room has a view, which reflects the visibility of nature and landscape and has a strong influence on the health, living satisfaction, and housing value of inhabitants. Thus, automatic accurate window view assessment is vital in examining neighborhood landscape and optimizing the social and physical settings for sustainable urban deve...

Urban dwellers enjoy nature exposure in the neighborhood built environment through visual and physical ways, such as window views and outdoor activities. However, existing studies and analytics examine these pathways separately, leading to underinformed urban planning practices such as difficult prioritizing urban areas with both low-level nature e...

Urban-scale quantification of window views can inform housing selection and valuation, landscape management, and urban planning. However, window views are numerous in high-rise, high-density urban areas and current automatic assessments of window views are inaccurate and time-consuming. Thus, both accurate and efficient assessment of window views i...

Large-scale assessment of window views is demanded for precise housing valuation and quantified evidence for improving the built environment, especially in high-rise, high-density cities. However, the absence of a semantic segmentation dataset of window views forbids an accurate pixel-level assessment. This paper presents a City Information Model (...

[Free PDF:🌐 https://authors.elsevier.com/a/1iYh03I9x1qnCf 🌐 until Apr 2024] Compact building models are demanded by global smart city applications, while high-definition urban 3D data is increasingly accessible by dint of the advanced reality capture technologies. Yet, existing building reconstruction methods encounter crucial bottlenecks against h...

Many existing 3D semantic segmentation methods, deep learning in computer vision notably, claimed to achieve desired results on urban point clouds. Thus, it is significant to assess these methods quantitatively in diversified real-world urban scenes, encompassing high-rise, low-rise, high-density, and low-density urban areas. However, existing publ...

Many existing 3D semantic segmentation methods, deep learning in computer vision notably, claimed to achieve desired results on urban point clouds, in which the city objects are too many and diverse for people to judge qualitatively. Thus, it is significant to assess these methods quantitatively in diversified real-world urban scenes, encompassing...

Building Information Modeling (BIM) has presented great potential in the construction industry. Scan-to-BIM is demanded to verify as-designed models and to digital twin many existing buildings without BIMs. This paper focuses on an extreme case without human interferences like data cleansing and partitioning – fully automatic Scan-to- BIM, on which...

Urban-scale quantification of window views can inform housing selection and valuation, landscape management, and urban planning. However, window views are numerous in high-rise, high-density urban areas and current automatic assessments of window views are inaccurate and time-consuming. Thus, both accurate and efficient assessment of window views i...

Urban material stock (UMS) represents an elegant thinking by perceiving cities as a repository of construction materials that can be reused in the future, rather than a burdensome generator of construction and demolition waste. Many studies have attempted to quantify UMS but they often fall short in accuracy, primarily owing to the lack of proper q...

The built environment closely relates to the development of COVID-19 and post-disaster recovery. Nevertheless, few studies examine its impacts on the recovery stage and corresponding urban development strategies. This study examines the built environment’s role in Wuhan’s recovery at the city block level through a natural experiment. We first aggre...

A view is among the critical criteria in an architectural design process. Presently, it is assessed by conventional site observation, labour-intensive data collection, and manual data analysis before designing a building mass, plan, façade, openings, and interior space. City Information Model (CIM), with its capabilities to store, visualize, and an...

Window view is an intimate medium between occupants and nature, especially in high-density cities like Hong Kong; and thus belongs to the quality of a house or apartment. In literature, researchers found that window views of nature are vital to the occupants’ physical and psychological health and productivity improvement. Understanding the view sit...

Building information modeling (BIM) of cultural heritages, i.e., historic building information modeling (HBIM), advances the monitoring, maintenance, restoration, and virtual exhibitions of historical buildings. However, due to the elaborate styles and the unavoidable erosion and renovation, the reconstruction of HBIM from the prevalent raw data, s...

Building information modeling (BIM) of cultural heritages, i.e., historic building information modeling (HBIM), advances the monitoring, maintenance, restoration, and virtual exhibitions of historical buildings. However, due to the elaborate styles and the unavoidable erosion and renovation, the reconstruction of HBIM from the prevalent raw data, s...

Massive spatiotemporal data scheduling in a cloud environment play a significant role in real-time visualization. Existing methods focus on preloading, prefetching, multithread processing and multilevel cache collaboration, which waste hardware resources and cannot fully meet the different scheduling requirements of diversified tasks. This paper pr...

Task-oriented scene data in big data and cloud environments of a smart city that must be time-critically processed are dynamic and associated with increasing complexities and heterogeneities. Existing hybrid tree-based external indexing methods are input/output (I/O)-intensive, query schema-fixed, and difficult when representing the complex relatio...