Analysis on urban densification dynamics and future modes in southeastern Wisconsin, USA.
PLoS One 2019;
14:e0211964. [PMID:
30840656 PMCID:
PMC6407910 DOI:
10.1371/journal.pone.0211964]
[Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 01/24/2019] [Indexed: 11/24/2022] Open
Abstract
Urban change (urbanization) has dominated land change science for several
decades. However, few studies have focused on what many scholars call the urban
densification process (i.e., urban intensity expansion) despite its importance
to both planning and subsequent impacts to the environment and local economies.
This paper documents past urban densification patterns and uses this information
to predict future densification trends in southeastern Wisconsin (SEWI) by using
a rich dataset from the United States and by adapting the well-known Land
Transformation Model (LTM) for this purpose. Urban densification is a
significant and progressive process that often accompanies urbanization more
generally. The increasing proportion of lower density areas, rather than higher
density areas, was the main characteristic of the urban densification in SEWI
from 2001 to 2011. We believe that improving urban land use efficiency to
maintain rational densification are effective means toward a sustainable urban
landscape. Multiple goodness-of-fit metrics demonstrated that the reconfigured
LTM performed relatively well to simulate urban densification patterns in 2006
and 2011, enabling us to forecast densification to 2016 and 2021. The predicted
future urban densification patterns are likely to be characterized by higher
densities continue to increase at the expense of lower densities. We argue that
detailed categories of urban density and specific relevant predictor variables
are indispensable for densification prediction. Our study provides researchers
working in land change science with important insights into urban densification
process modeling. The outcome of this model can help planners to identify the
current trajectory of urban development, enabling them to take informed action
to promote planning objectives, which could benefit sustainable urbanization
definitely.
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