Cities are human ecosystems. Understanding human ecology is important for designing and planning the built environment. The ability to respond to changes and adapt actions in a positive way helps determine the health of cities. Recently, many studies have highlighted the great potential of photographic data shared on the Flickr platform for the analysis of environmental perceptions in landscape and urban planning. Other research works used panoramic images from the Google Street View (GSV) web service to extract urban quality data. Although other researches have used social media to characterize human habitat from an emotional point of view, there is still a lack of knowledge of the correlation between environmental and physical variables of the city and visual perception, especially at a scale suitable for urban planning and design. In ecology, the environmental suitability of a territory for a given biological community is studied through species distribution models (SDM). In this work we have adopted the state of the art of SDM (the ensemble approach) to develop a methodology transferable to cities with different sizes and characteristics that uses data deriving from many sources available on a global scale: social media platform, Google internet services, shared geographical information, remote sensing and geomorphological data. The result of our application in the city of Livorno offers important information on the most significant variables for the conservation, planning and design of urban public spaces at the project scale. However, further research developments will be needed to test the model in cities of different sizes and geographic locations, integrate the model with other social media, other databases and with traditional surveys and improve the quality of indicators that can be derived from information shared on the Internet

Urban Niche Assessment: An Approach Integrating Social Media Analysis, Spatial Urban Indicators and Geo-Statistical Techniques / Bernetti, Iacopo; Alampi Sottini, Veronica; Bambi, Lorenzo; Barbierato, Elena; Borghini, Tommaso; Capecchi, Irene; Saragosa, Claudio. - In: SUSTAINABILITY. - ISSN 2071-1050. - ELETTRONICO. - 12:(2020), pp. 3982-4012. [10.3390/su12103982]

Urban Niche Assessment: An Approach Integrating Social Media Analysis, Spatial Urban Indicators and Geo-Statistical Techniques

Bernetti, Iacopo;Alampi Sottini, Veronica;Bambi, Lorenzo;Barbierato, Elena;Borghini, Tommaso;Capecchi, Irene;Saragosa, Claudio
2020

Abstract

Cities are human ecosystems. Understanding human ecology is important for designing and planning the built environment. The ability to respond to changes and adapt actions in a positive way helps determine the health of cities. Recently, many studies have highlighted the great potential of photographic data shared on the Flickr platform for the analysis of environmental perceptions in landscape and urban planning. Other research works used panoramic images from the Google Street View (GSV) web service to extract urban quality data. Although other researches have used social media to characterize human habitat from an emotional point of view, there is still a lack of knowledge of the correlation between environmental and physical variables of the city and visual perception, especially at a scale suitable for urban planning and design. In ecology, the environmental suitability of a territory for a given biological community is studied through species distribution models (SDM). In this work we have adopted the state of the art of SDM (the ensemble approach) to develop a methodology transferable to cities with different sizes and characteristics that uses data deriving from many sources available on a global scale: social media platform, Google internet services, shared geographical information, remote sensing and geomorphological data. The result of our application in the city of Livorno offers important information on the most significant variables for the conservation, planning and design of urban public spaces at the project scale. However, further research developments will be needed to test the model in cities of different sizes and geographic locations, integrate the model with other social media, other databases and with traditional surveys and improve the quality of indicators that can be derived from information shared on the Internet
2020
12
3982
4012
Bernetti, Iacopo; Alampi Sottini, Veronica; Bambi, Lorenzo; Barbierato, Elena; Borghini, Tommaso; Capecchi, Irene; Saragosa, Claudio
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1193683
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