Influence of urban land-use change on cold-air path occurrence and spatial distribution

The urban population is predicted to reach a 70% share of global population by mid-century. Future urbanization might be directed along several development typologies, e.g. sprawling urbanization, more compact cities, greener cities, or a combination of different typologies. These developments induce urban land-use change that will affect urban climate and might reinforce phenomena such as the urban heat island and thermal discomfort of urban residents. A planning-based mitigation approach to ensure thermal comfort of residents are urban cold-air paths, i.e. low-roughness areas enabling drainage and transport of colder air masses from rural surroundings. We study how urban land-use change scenarios influence cold-air path occurrence probability and spatial distribution in a mid-European city using a machine learning approach, i.e. boosted regression trees. The Urban Sprawl Scenario results in the strongest reduction of cold-air path area by 3.6% in comparison to the reference case. The Green City Scenario gives evidence for an increase of cold-air path area (2.2%) whereas the Compact Green City Scenario partly counteracts the negative influence of urban densification by increased fractions of vegetated areas. The proposed method allows for the identification of priority areas for cold-air path preservation in urban planning.

A regional spatial-retrofitting approach to geovisualise regional urban growth: An application to the Golden Horseshoe in Canada

Understanding urban change in particular for larger regions has been a great demur in both regional planning and geography. One of the main challenges has been linked to the potential of modelling urban change. The absence of spatial data and size of areas of study limit the traditional urban monitoring approaches, which also do not take into account visualization techniques that share information with the community. This is the case of the Golden Horseshoe in southern Ontario in Canada, one of the fastest growing regions in North America. An unprecedented change on the urban environment has been witnessed, leading to an increased importance of awareness for future planning in the region. With a population greater than 8 million, the Golden Horseshoe is steadily showing symptoms of becoming a mega-urban region, joining surrounding cities into a single and diversified urban landscape. However, little effort has been done to understand these changes, nor to share information with policy makers, stakeholders and investors. These players are in need of the most diverse information on urban land use, which is seldom available from a single source. The spatio-temporal effect of the growth of this urban region could very well be the birth of yet another North American megacity. Therefore, from a spatial perspective there is demand for joint collaboration and adoption of a regional science perspective including land use and spatio-temporal configurations. This calls forth a novel technique that allows for assessment of urban and regional change, and supports decision-making without having the usual concerns of locational data availability. It is this sense, that we present a spatial-retrofitting model, with the objective of (i) retrofitting spatial land use based on current land use and land cover, and assessing proportional change in the past, leading to four spatial timestamps of the Golden Horseshoe’s land use, while (ii) integrating this in a multi-user open source web environment to facilitate synergies for decision-making. This combined approach is referred to as a regional-spatial-retrofitting approach (RSRA), where the conclusions permit accurate assessment of land use in past time frames based on Landsat imagery. The RSRA also allows for a collective vision of regional urban growth supporting local governance through a decision-making process adhering to Volunteered Geographic Information Systems. Urban land use change can be refined by means of contribution from end-users through a web environment, leading to a constant understanding and monitoring of urban land use and urban land use change.

A regional spatial-retrofitting approach to geovisualise regional urban growth: An application to the Golden Horseshoe in Canada

Understanding urban change in particular for larger regions has been a great demur in both regional planning and geography. One of the main challenges has been linked to the potential of modelling urban change. The absence of spatial data and size of areas of study limit the traditional urban monitoring approaches, which also do not take into account visualization techniques that share information with the community. This is the case of the Golden Horseshoe in southern Ontario in Canada, one of the fastest growing regions in North America. An unprecedented change on the urban environment has been witnessed, leading to an increased importance of awareness for future planning in the region. With a population greater than 8 million, the Golden Horseshoe is steadily showing symptoms of becoming a mega-urban region, joining surrounding cities into a single and diversified urban landscape. However, little effort has been done to understand these changes, nor to share information with policy makers, stakeholders and investors. These players are in need of the most diverse information on urban land use, which is seldom available from a single source. The spatio-temporal effect of the growth of this urban region could very well be the birth of yet another North American megacity. Therefore, from a spatial perspective there is demand for joint collaboration and adoption of a regional science perspective including land use and spatio-temporal configurations. This calls forth a novel technique that allows for assessment of urban and regional change, and supports decision-making without having the usual concerns of locational data availability. It is this sense, that we present a spatial-retrofitting model, with the objective of (i) retrofitting spatial land use based on current land use and land cover, and assessing proportional change in the past, leading to four spatial timestamps of the Golden Horseshoe’s land use, while (ii) integrating this in a multi-user open source web environment to facilitate synergies for decision-making. This combined approach is referred to as a regional-spatial-retrofitting approach (RSRA), where the conclusions permit accurate assessment of land use in past time frames based on Landsat imagery. The RSRA also allows for a collective vision of regional urban growth supporting local governance through a decision-making process adhering to Volunteered Geographic Information Systems. Urban land use change can be refined by means of contribution from end-users through a web environment, leading to a constant understanding and monitoring of urban land use and urban land use change.