Buildings MDPI on LinkedIn: #highlycitedpaper #urbanspatialstructure #urbanvitality #influencemechanism (2024)

📊 Seeking to Understand and Define Cities through DataMIT's Department of Urban Studies and Planning (DUSP) is exploring ways to define cities using vast amounts of data. In a recent feature, DUSP highlights how understanding and analyzing urban centers is becoming increasingly data-driven. The initiative looks at using data points such as cell data from China, visualized as light nodes, where higher intensities represent more accumulated data. These techniques aim to offer new perspectives on urban patterns and can possibly inform city planning and management.Sources:https://lnkd.in/geWCuSCM#MIT #UrbanStudies #DataScience #CityPlanning #Technology #Innovation

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💡Pedestrian life has rarely been studied in informal areas. In a new study Yael Borofsky, Isabel Guenther and Stephanie Briers compare sensor data measuring pedestrian activity in Cape Town in informal settlements with the predictions from two pedestrian activity theories. 📄 Read thefull #OpenAccesspublication ➡️https://buff.ly/481MceF #PedestrianActivity #InformalSettlement

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Fresh from the oven, I recently got a copy of this beautiful book, 𝐂𝐢𝐭𝐲 𝐒𝐜𝐢𝐞𝐧𝐜𝐞: 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐅𝐨𝐥𝐥𝐨𝐰𝐬 𝐅𝐨𝐫𝐦, written byJeremy B.andRamon Gras Alomà from Aretian Urban Analytics and Design, published by Actar Publishers.The hard-cover piece is a work of art in itself, with so many beautiful geospatial data visualizations, the cover, and even the black insert pages!It also provides a great introduction and overview to anyone from beginners to practitioners in urban planning and design, geospatial data science, and complex systems and network science in city planning. The book walks the readers through a series of theoretical snippets, from urban innovation to city typology, and covers main city development directions and technicalities such as road network fractality and city orientations entropy. The team also develops methodologies to assess urban efficiency and introduces concepts to propose city design plans based on data.Finally, the book closes with a beautiful 𝘈𝘵𝘭𝘢𝘴 𝘰𝘧 𝘎𝘭𝘰𝘣𝘢𝘭 𝘊𝘪𝘵𝘪𝘦𝘴, visualizing and describing 100 global cities - amongst Budapest, kudos to that! Thanks for the book supply, Ramon!Get your copy here: https://lnkd.in/dvKei5cn#urbandesign #urbanplanning #gis #geospatialdata #datascience #networkscience #datavisualization

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Interested in Mobility and Urban Transport Planning?See my article that presents the main results of a Project that I was part of in 2022 - Integrative Learning from Urban Data and Situational Context for City Mobility Optimization (ILU).https://lnkd.in/dy6YKTfm

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I am happy to share that this article has been published in Raumforschung und Raumordnung | Spatial Research and Planning. Marie-Christin Althaus, Jan Heissler and I investigate methods, spatial patterns and determinants of digital and multi-channel participation in Germany based on a comprehensive examinationby websites of German cities and districts. https://lnkd.in/eGK4-PEZ

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Machine learning and remote sensing integration framework for urban sustainability.This framework also allows researchers to compare urban studies and assess the main contributions or novelty of their work/s. The framework has been structured using a recursive loop approach, which effectively demonstrates the iterative nature of the integration process, highlighting the fact that the process of addressing targeted urban issues requires ongoing refinement until a satisfactory solution is achieved.Reference: Li, F., Yigitcanlar, T., Nepal, M., Nguyen, K., & Dur, F. (2023). Machine Learning and Remote Sensing Integration for Leveraging Urban Sustainability: A Review and Framework.Sustainable Cities and Society, 104653.

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This paper introduces a novel Green Urban Scenarios framework to (re)design, forecast, and monitor #greeninfrastructure portfolios and their impacts under varying weather conditions, maintenance regimes, tree species compositions, disease exposures, and spatial distributions. The framework adopts an agent-based modelling (ABM) and simulation paradigm that embeds a green infrastructure portfolio within a city’s ecological, spatial, economic, and social context. ABM serves to build Digital Twins of urban ecosystems at any level of granularity, including the level of individual trees, to trace out their future trajectories https://lnkd.in/eyMf649i

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⚡ Selection and prediction of metro station sites based on spatial data and random forest: a study of Lanzhou, China | NatureDiscover more at "voltsbase.com/science"#Science #Voltsbase

NDBI stands for "Normalized Difference Built-Up Index." It is a remote sensing index that is used to map urban areas. NDBI is calculated using satellite imagery and is designed to distinguish between built-up and non-built-up areas.The NDBI is derived by computing the difference between the near-infrared (NIR) and shortwave infrared (SWIR) bands of satellite images and normalizing the result by adding the values of the two bands. The formula for NDBI is:NDBI = (NIR - SWIR) / (NIR + SWIR)The NDBI values range from -1 to +1, with positive values indicating the presence of built-up areas and negative values indicating non-built-up areas. A value of zero indicates a balanced mix of both built-up and non-built-up areas.The NDBI is useful for urban planning, land-use studies, and environmental monitoring. It can help identify areas of urban growth and development, and can be used to estimate the extent and distribution of impervious surfaces in urban areas.#urbanplanning #growth #development #help #computing #environmental saira ahmedZaheer AbbasAbid jahanZohra ManzoorMinhaj karimMushahid NabiEjaz Ali

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We are pleased to announce a collaboration with the Bundesamt für Bauwesen und Raumordnung (BBSR) (in Eng: Federal Office for Building and Regional Planning) and Arup on a research project titled "New Mobility Patterns? Behavioral Changes in Use of Public Spaces."Key Details:Funding Institution: Bundesamt für Bauwesen und Raumordnung (BBSR)(Federal Office for Building and Regional Planning)Partner: ArupProject Overview:Our research project will investigate the impact of the COVID-19 pandemic on mobility behavior and the use of public spaces. Using mobile phone data, we aim to quantify and analyze the extent of these changes. Additionally, we will assess the suitability and scalability of mobile phone data for urban analysis.For further information, please contact Yangqian Cai.This collaboration promises valuable insights into evolving urban dynamics, contributing to more adaptive urban planning. Stay tuned for updates as we progress with this important research initiative.https://lnkd.in/ewnkcEhG#UrbanPlanning #MobilityBehavior #PublicSpaces #ResearchProject #BBSR #ARUP #DataAnalysis #UrbanPhenomena

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