Building and Environment, Год журнала: 2025, Номер unknown, С. 112883 - 112883
Опубликована: Март 1, 2025
Язык: Английский
Building and Environment, Год журнала: 2022, Номер 217, С. 109056 - 109056
Опубликована: Апрель 8, 2022
Язык: Английский
Процитировано
111
Building and Environment, Год журнала: 2023, Номер 237, С. 110295 - 110295
Опубликована: Апрель 18, 2023
Geospatial data of the building stock is essential in many domains pertaining to built environment. These datasets are often provided by governments, but crowdsourcing them has surged last decade. Nowadays, OpenStreetMap (OSM) – most popular Volunteered Geographic Information (VGI) platform contains geospatial and descriptive on more than 500 million buildings worldwide collected millions contributors, it increasingly used studies ranging from energy microclimate urban planning life cycle assessment. However, large-scale understanding their quality remains limited, which may hinder use management. In this paper, we seek understand state information OSM whether a reliable source such data. We provide comprehensive study assess attribute (descriptive) mapped globally, e.g. function, key ingredients analyses simulations examine three aspects: completeness, consistency, accuracy. assessment, first at scale available hitherto, find that continues be highly heterogeneous — poor some, very high completeness other areas, potentially benefiting range application domains, estimate 3D models 443 administrative units (mostly cities municipalities) around world can generated OSM, underpinning generation digital twins. The number floors type frequent properties contributors record, cases accurate, while mapping interior did not gain momentum.
Язык: Английский
Процитировано
86
Energy and Buildings, Год журнала: 2021, Номер 257, С. 111809 - 111809
Опубликована: Дек. 24, 2021
Язык: Английский
Процитировано
64
International Journal of Geographical Information Science, Год журнала: 2022, Номер 37(1), С. 36 - 67
Опубликована: Авг. 1, 2022
Urban morphology is important in a broad range of investigations across the fields city planning, transportation, climate, energy, and urban data science. Characterising buildings with set numerical metrics fundamental to studying form. Despite rapid developments 3D geoinformation science, growing availability, most studies simplify their 2D footprint, when taking height into account, they at assume one value per building, i.e. simple 3D. We take first step elevating building full/true 3D, uncovering use higher levels detail, account detailed shape building. foundation new research line on by providing comprehensive metrics, implementing them openly released software, generating an open dataset containing for 823,000 Netherlands, demonstrating case where clusters architectural patterns are analysed through time. Our experiments suggest added complement existing counterparts, reducing ambiguity, advanced insights. Furthermore, we provide comparative analysis using different detail models.
Язык: Английский
Процитировано
51
Energy and Built Environment, Год журнала: 2023, Номер 5(6), С. 957 - 969
Опубликована: Июль 23, 2023
As the world continues to urbanize at an unprecedented rate, energy demand in cities is rising. Buildings account for over 75% of all consumed and are responsible two-thirds emissions. Assessment buildings a highly integrative endeavour, bringing together interdisciplinary fields urban studies, along with host technical domains namely, geography, engineering, economics, sociology, planning. In last decade, several building modelling tools (UBEMs) have been developed estimation as well prediction cities. These models useful policymaking they can evaluate future scenarios. However, data acquisition generating input database UBEM has major challenge. this review, comprehensive assessment potential remote sensing GIS techniques presented. Firstly, most common variables identified by reviewing recent publications on then studies related corresponding these explored. More than 140 research papers review articles relevant applications level extraction areas investigated purpose. After going through details required each components studying possibility acquiring some those using sensing, it inferred that satellite Unmanned Aerial Vehicles (UAVs) strong enhancing space but their applicability limited. Further, challenges usage technologies possible solutions also presented study. It recommended utilise existing methodologies extracting information from UBEM, newer such machine learning artificial intelligence.
Язык: Английский
Процитировано
32
Advances in Applied Energy, Год журнала: 2023, Номер 12, С. 100155 - 100155
Опубликована: Окт. 6, 2023
The urban energy infrastructure is facing a rising number of challenges due to climate change and rapid urbanization. In particular, the link between morphology systems has become increasingly crucial as cities continue expand more densely populated. Achieving neutrality adds another layer complexity, highlighting need address this relationship develop effective strategies for sustainable infrastructure. occurrence extreme events can also trigger cascading failures in system components, leading long-lasting blackouts. This review paper thoroughly explores incorporating into models through comprehensive literature proposes new framework enhance resilience interconnected systems. emphasizes integrated provide deeper insights design operation addresses failures, interconnectivity, compound impacts urbanization on It emerging opportunities, including requirement high-quality data, utilization big integration advanced technologies like artificial intelligence machine learning proposed integrates classification, mesoscale microscale process consider influence morphology, variability, events. Given prevalence climate-resilient strategies, study underscores significance improving accommodate future variations while recognizing interconnectivity within
Язык: Английский
Процитировано
28
Building and Environment, Год журнала: 2023, Номер 246, С. 110960 - 110960
Опубликована: Окт. 27, 2023
Язык: Английский
Процитировано
26
Building and Environment, Год журнала: 2024, Номер 250, С. 111181 - 111181
Опубликована: Янв. 10, 2024
Язык: Английский
Процитировано
11
Energies, Год журнала: 2024, Номер 17(4), С. 881 - 881
Опубликована: Фев. 14, 2024
Technological improvements are crucial for achieving decarbonisation targets and addressing the impacts of climate change in built environment via mitigation adaptation measures. Data-driven methods building performance prediction particularly important this regard. Nevertheless, deployment these technologies faces challenges, domains artificial intelligence (AI) ethics, interpretability explainability machine learning (ML) algorithms. The challenges encountered applications amplified, when data-driven solutions need to be applied throughout all stages life cycle address problems from a socio-technical perspective, where human behaviour needs considered. This requires consistent use analytics assess building, ideally by employing digital twin (DT) approach, which involves creation counterpart continuous analysis improvement. paper presents an in-depth review critical connections between methods, AI their implementation environment, acknowledging complex interconnected nature topics. is organised into three distinct analytical levels: first level explores key issues current research on methods. second considers adoption interpretable energy modelling problem establishing link with third level, examines physics-driven grey-box techniques, order provide integrated solutions. review’s findings highlight how concept relevant multiple contexts pertaining some knowledge gaps can addressed further broad area
Язык: Английский
Процитировано
11
Building Simulation, Год журнала: 2024, Номер 17(5), С. 695 - 722
Опубликована: Март 11, 2024
Язык: Английский
Процитировано
10