Classification of Building Function Using Available Sources of Vgi

Fonte, Cidália C.; Minghini, Marco; Antoniou, Vyron; Patriarca, Joaquim; See, Linda

doi:10.5194/isprs-archives-xlii-4-209-2018

Cited by 15 publications

(11 citation statements)

References 6 publications

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“…With the currently available data, there are still many built-up areas having the mixed land use label (LU235). We plan to use data from OSM and the Urban Atlas data to better distinguish the function of buildings so as to distinguish between Residential (LU5), Commercial (LU3) and Industrial (LU2) land use types by following the approach proposed by Fonte et al (2018).…”

Section: Discussionmentioning

confidence: 99%

A data fusion-based framework to integrate multi-source VGI in an authoritative land use database

Liu

Olteanu‐Raimond

Jolivet

et al. 2020

International Journal of Digital Earth

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Updating an authoritative Land Use and Land Cover (LULC) database requires many resources. Volunteered geographic information (VGI) involves citizens in the collection of data about their spatial environment. There is a growing interest in using existing VGI to update authoritative databases. This paper presents a framework aimed at integrating multi-source VGI based on a data fusion technique, in order to update an authoritative land use database. Each VGI data source is considered to be an independent source of information, which is fused together using Dempster-Shafer Theory (DST). The framework is tested in the updating of the authoritative land use data produced by the French National Mapping Agency. Four data sets were collected from several in-situ and remote campaigns run between 2018 and 2020 by contributors with varying profiles. The data fusion approach achieved an overall accuracy of 85.6% for the 144 features having at least two contributions when the confidence threshold was set to 0.05. Despite the heterogeneity and limited amount of VGI used, the results are promising, with 99% of the LU polygons updated or enriched. These results show the potential of using multi-source VGI to update or enrich authoritative LU data and potentially LULC data more generally.

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Section: Discussionmentioning

confidence: 99%

A data fusion-based framework to integrate multi-source VGI in an authoritative land use database

Liu

Olteanu‐Raimond

Jolivet

et al. 2020

International Journal of Digital Earth

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“…OSM has specific tags for users to indicate the building function. In a study by Fonte et al (2018), OSM data were extracted for a section of the city of Milan. By analyzing the tags associated with buildings as well as the points of interest layer, more than 80% of the buildings in Milan could be assigned a building function.…”

Section: Crowdsourcingmentioning

confidence: 99%

“…Other crowdsourced information can also be used to infer building use. In Fonte et al (2018), crowdsourced data from Facebook and Foursquare were additionally used to fill in some of the gaps from OSM regarding building use. Using only Foursquare, Spyratos et al (2017) classified buildings in Amsterdam according to building use types.…”

Section: Crowdsourcingmentioning

confidence: 99%

City-descriptive input data for urban climate models: Model requirements, data sources and challenges

et al. 2020

Self Cite

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City-descriptive input data for urban climate models: Model requirements, data sources and challenges Abstract 1) Introduction 1.1 Brief overview of urban atmospheric modelling 1.2 Scale issues: mesoscale and microscale 1.3 Coverage issues: from city-scale to global modelling 1.4 Fit for purpose 2) Land use and land cover classes 2.1 Description of the parameters and their relevance 2.2 Methodologies to gather land cover data 2.2.1. Remote sensing methods 2.2.2. From vector topographical databases and land registries 2.2.3. Data fusion 3) Morphological parameters 3.1 Description of the parameters and their relevance 3.2 Links between morphological parameters 3.3 Methodologies to gather morphological parameters 3.3.1 Data from remote sensing 3.3.2 GIS treatment of 2.5D cadaster vector data of individual buildings 3.3.4 Crowdsourcing or deep learning methods 4) Architectural parameters 4.1 Description of the parameters and their relevance 4.2 Developing comprehensive architectural databases 4.3 Methodologies to gather architectural information 4.3.1 Identification of representative archetypes 4.3.2 Remote sensing and image processing 4.3.3 Crowdsourcing 5) Socioeconomic data and building use 5.1 Description of the parameters and their relevance 5.2 Methodologies to gather uses, socioeconomic and anthropogenic heat parameters 5.2.1 From inventories 5.2.2 Crowdsourcing 6) Urban vegetation 6.1 Description of the parameters and their relevance 6.2 Methodologies to collect vegetation parameters at mesoscale 28 6.3 Methodologies to collect vegetation parameters at microscale 29 7) Discussion 30 7.1 Licensing issues 30 7.2 Cataloguing issues 31 7.3 Data quality 7.4 Open data 31 7.5 Research challenges for the next decade 32 7.6 From data of various origins to Urban Climate Services 33 8 Conclusions 33 Appendix 1: Overview of several global land cover data sets with an urban description 34 Acknowledgements 36 References 36

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“…Following this license, copy, distribution, transmission and modification of the data are allowed under the conditions of attributing and, if data are modified, distributing them again under the same license. OSM has been widely used for different topics as routing, navigation and transportation studies in research and professional applications (Bakillah et al, 2013, Bakillah et al, 2014, Graser et al, 2015, Zhang, Ai, 2015, but also in land-use studies (Costa et al, 2019) or building classification (Fonte et al, 2018).…”

Section: 11mentioning

confidence: 99%

Mapping the Accessibility in Openstreetmap: A Comparison of Different Techniques

Biagi

Brovelli

Stucchi

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Architectural barriers are physical elements that limit the freedom of movement and use of services of a person. The lack of accessibility is one of the physical barriers that most limit people with motor disabilities, as recognised by the World Health Organization. The work aims to identify the optimal methodology to map accessible ways and critical barriers, in order to produce cartographic support for people with motor disabilities. It should also be a tool that allows citizens to report barriers to public authority. The work is part of the ViaLibera?! project, which aims to apply the methodology in the Municipality 9 of the city of Milan. The project is founded by Fondazione di Comunit`a Milano; Politecnico di Milano is the scientific partner, while the other partners are associations that represent people with disabilities: Spazio Vita Niguarda Onlus, Ledha Milano and AUS Niguarda Onlus. The mapping elements of interest for the project were identified in collaboration with the other partners, also studying the state of the art. In the framework of Open Street Map, a comparison between different existing mapping techniques was done to select the optimal compromise between rigour and simplicity. In addition, the different techniques must be suitable for the chosen tagging scheme to map accessibility elements. The techniques analysed involve the use of paper maps, Field Papers, and street-level images or applications for smartphones. They are compared to identify the best one.

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Classification of Building Function Using Available Sources of Vgi

Cited by 15 publications

References 6 publications

A data fusion-based framework to integrate multi-source VGI in an authoritative land use database

A data fusion-based framework to integrate multi-source VGI in an authoritative land use database

City-descriptive input data for urban climate models: Model requirements, data sources and challenges

Mapping the Accessibility in Openstreetmap: A Comparison of Different Techniques

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