A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Spatiotemporal Dynamics of Urban Growth and Greening Goals Towards Sustainable Development
https://orcid.org/http://orcid.org/0000-0003-3670-490X
https://orcid.org/http://orcid.org/0000-0001-7163-8114
A quantitative assessment of the complex relationship between urban growth and greening represents an efficient method to manage and understand the land cover transformation. A key solution to reach this aim is combining innovative Remote Sensing (RS) technologies and geospatial techniques to assess the interaction dynamics of urban and greening changes towards sustainability over time. Despite this, the research on this issue still needs to be fully explored. The authors propose an innovative methodology based on Deep Learning (DL) algorithms and Geographic Information Systems (GIS) techniques that, considering the population dynamics and two new indicators, evaluate the co-relation between urban growth, vegetation and population changes. The overall methodology is tested on the urban area of Matera municipality (Basilicata, Italy), analyzing changes in urban, greening and population from 2000 to 2020. Thanks to a quadrant analysis, the results (i) highlighted development patterns of the built-up area and the vegetation cover, (ii) identified the quadrants of the study area characterized by valuable or critical levels of co-relation between urban growth, greening changes, and population dynamics towards sustainability. The applied methodology could support local administrators, technicians, and researchers in promoting strategies to improve sustainable urban development.
Spatiotemporal Dynamics of Urban Growth and Greening Goals Towards Sustainable Development
https://orcid.org/http://orcid.org/0000-0003-3670-490X
https://orcid.org/http://orcid.org/0000-0001-7163-8114
A quantitative assessment of the complex relationship between urban growth and greening represents an efficient method to manage and understand the land cover transformation. A key solution to reach this aim is combining innovative Remote Sensing (RS) technologies and geospatial techniques to assess the interaction dynamics of urban and greening changes towards sustainability over time. Despite this, the research on this issue still needs to be fully explored. The authors propose an innovative methodology based on Deep Learning (DL) algorithms and Geographic Information Systems (GIS) techniques that, considering the population dynamics and two new indicators, evaluate the co-relation between urban growth, vegetation and population changes. The overall methodology is tested on the urban area of Matera municipality (Basilicata, Italy), analyzing changes in urban, greening and population from 2000 to 2020. Thanks to a quadrant analysis, the results (i) highlighted development patterns of the built-up area and the vegetation cover, (ii) identified the quadrants of the study area characterized by valuable or critical levels of co-relation between urban growth, greening changes, and population dynamics towards sustainability. The applied methodology could support local administrators, technicians, and researchers in promoting strategies to improve sustainable urban development.
Spatiotemporal Dynamics of Urban Growth and Greening Goals Towards Sustainable Development
https://orcid.org/http://orcid.org/0000-0003-3670-490X
https://orcid.org/http://orcid.org/0000-0001-7163-8114
A quantitative assessment of the complex relationship between urban growth and greening represents an efficient method to manage and understand the land cover transformation. A key solution to reach this aim is combining innovative Remote Sensing (RS) technologies and geospatial techniques to assess the interaction dynamics of urban and greening changes towards sustainability over time. Despite this, the research on this issue still needs to be fully explored. The authors propose an innovative methodology based on Deep Learning (DL) algorithms and Geographic Information Systems (GIS) techniques that, considering the population dynamics and two new indicators, evaluate the co-relation between urban growth, vegetation and population changes. The overall methodology is tested on the urban area of Matera municipality (Basilicata, Italy), analyzing changes in urban, greening and population from 2000 to 2020. Thanks to a quadrant analysis, the results (i) highlighted development patterns of the built-up area and the vegetation cover, (ii) identified the quadrants of the study area characterized by valuable or critical levels of co-relation between urban growth, greening changes, and population dynamics towards sustainability. The applied methodology could support local administrators, technicians, and researchers in promoting strategies to improve sustainable urban development.
Spatiotemporal Dynamics of Urban Growth and Greening Goals Towards Sustainable Development
Lecture Notes in Civil Engineering
Marucci, Alessandro (editor) / Zullo, Francesco (editor) / Fiorini, Lorena (editor) / Saganeiti, Lucia (editor) / Salvo, Carolina (author) / Vitale, Alessandro (author)
International Conference on Innovation in Urban and Regional Planning ; 2023 ; L'Aquila, Italy
2024-02-25
13 pages
Article/Chapter (Book)
Electronic Resource
English
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