As simulation-informed design gains importance in addressing urban complexity,integrating urban imagery into interactive feedback and decision-making has become increasingly essential.However,this potential remains un...As simulation-informed design gains importance in addressing urban complexity,integrating urban imagery into interactive feedback and decision-making has become increasingly essential.However,this potential remains underused,as urban imagery is often treated as a supporting variable in urban research rather than a core layer of spatial intelligence,hindering informed strategies in city branding,resource allocation,and livability.This study develops a data-driven framework,Street View Search Engine,which integrates urban imagery analysis with interactive exploration to advance human-centered insights into urban visual form.Based on 81,478 street view imagery collected in Hong Kong,China,a dataset comprising 19 visual features was first constructed to represent urban visual information across three categories:physical,impression,and isovist.Subsequently,the machine learning algorithm self-organizing maps was employed to train the dataset,producing a visualized“data landscape”that re-organizes street views according to their visual similarities.Third,building on the data landscape,this study develops the Street View Search Engine framework to conduct three main tasks:define visual foundations,comprehend streetscape morphology,and evaluate regional visual schemes.These tasks combine general-use exploration with research-oriented analysis:a web-based platform was developed to support general-use exploration(http://47.113.226.77/project1/#/),while various data processing methods were employed to enable in-depth professional investigations.By transforming raw data into a visualizable,computable,and interactive urban imagery system,this study paves the way for evidence-based interventions,strategic resource allocation,and greater public engagement in urban planning.展开更多
Mass Customization and global economic collaboration drives the product development and management beyond internal enterprise to cover the whole product value chain. To meet such requirement, a strategy approach focus...Mass Customization and global economic collaboration drives the product development and management beyond internal enterprise to cover the whole product value chain. To meet such requirement, a strategy approach focusing on data organization for product lifecycle management was promoted. The approach takes product platform as the base, view engine and rule-based access as data access mechanism, and integration and collaboration bus as a enabler to allow participants involved in product lifecycle to get convenient, WEB-based access to the internal and external content, applications, and services.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52308015)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515011214)the Guangzhou Science and Technology Planning Project(Grant No.SL2024A04J01189).
文摘As simulation-informed design gains importance in addressing urban complexity,integrating urban imagery into interactive feedback and decision-making has become increasingly essential.However,this potential remains underused,as urban imagery is often treated as a supporting variable in urban research rather than a core layer of spatial intelligence,hindering informed strategies in city branding,resource allocation,and livability.This study develops a data-driven framework,Street View Search Engine,which integrates urban imagery analysis with interactive exploration to advance human-centered insights into urban visual form.Based on 81,478 street view imagery collected in Hong Kong,China,a dataset comprising 19 visual features was first constructed to represent urban visual information across three categories:physical,impression,and isovist.Subsequently,the machine learning algorithm self-organizing maps was employed to train the dataset,producing a visualized“data landscape”that re-organizes street views according to their visual similarities.Third,building on the data landscape,this study develops the Street View Search Engine framework to conduct three main tasks:define visual foundations,comprehend streetscape morphology,and evaluate regional visual schemes.These tasks combine general-use exploration with research-oriented analysis:a web-based platform was developed to support general-use exploration(http://47.113.226.77/project1/#/),while various data processing methods were employed to enable in-depth professional investigations.By transforming raw data into a visualizable,computable,and interactive urban imagery system,this study paves the way for evidence-based interventions,strategic resource allocation,and greater public engagement in urban planning.
文摘Mass Customization and global economic collaboration drives the product development and management beyond internal enterprise to cover the whole product value chain. To meet such requirement, a strategy approach focusing on data organization for product lifecycle management was promoted. The approach takes product platform as the base, view engine and rule-based access as data access mechanism, and integration and collaboration bus as a enabler to allow participants involved in product lifecycle to get convenient, WEB-based access to the internal and external content, applications, and services.
