IGSNRR OpenIR
Analysis on urban densification dynamics and future modes in southeastern Wisconsin, USA
Wang, Lingzhi1,2,3; Omrani, Hichem4; Zhao, Zhao5; Francomano, Dante3; Li, Ke6; Pijanowski, Bryan3
2019-03-06
Source PublicationPLOS ONE
ISSN1932-6203
Volume14Issue:3Pages:22
Corresponding AuthorWang, Lingzhi(wanglingz@jlu.edu.cn)
AbstractUrban 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.
DOI10.1371/journal.pone.0211964
WOS KeywordLAND-USE CHANGE ; COVER DATABASE ; IMPERVIOUS SURFACE ; ENVIRONMENTAL-IMPACT ; CELLULAR-AUTOMATA ; URBANIZATION ; VALIDATION ; GROWTH ; SIMULATION ; LANDSCAPE
Indexed BySCI
Language英语
Funding ProjectJilin Province Science and Technology Development Plan Project[20180418111FG] ; Jilin Provincial Department of Education 13th Five-Year Science and Technology Project[JJKH20180163KJ] ; Major Science and Technology Program for Water Pollution Control and Treatment[2012ZX07408001] ; Jilin Science Foundation for Excellent Young Scholars[20180520169JH] ; National Research Fund Luxembourg (FNR-Luxembourg) ; LISER research institute-Luxembourg
Funding OrganizationJilin Province Science and Technology Development Plan Project ; Jilin Provincial Department of Education 13th Five-Year Science and Technology Project ; Major Science and Technology Program for Water Pollution Control and Treatment ; Jilin Science Foundation for Excellent Young Scholars ; National Research Fund Luxembourg (FNR-Luxembourg) ; LISER research institute-Luxembourg
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000460372100017
PublisherPUBLIC LIBRARY SCIENCE
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49314
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWang, Lingzhi
Affiliation1.Jilin Univ, Coll Earth Sci, Changchun, Jilin, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
3.Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA
4.LISER, Urban Dev & Mobil Dept, Esch Sur Alzette, Luxembourg
5.Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing, Jiangsu, Peoples R China
6.Jilin Jianzhu Univ, Key Lab Songliao Aquat Environm, Minist Educ, Changchun, Jilin, Peoples R China
Recommended Citation
GB/T 7714
Wang, Lingzhi,Omrani, Hichem,Zhao, Zhao,et al. Analysis on urban densification dynamics and future modes in southeastern Wisconsin, USA[J]. PLOS ONE,2019,14(3):22.
APA Wang, Lingzhi,Omrani, Hichem,Zhao, Zhao,Francomano, Dante,Li, Ke,&Pijanowski, Bryan.(2019).Analysis on urban densification dynamics and future modes in southeastern Wisconsin, USA.PLOS ONE,14(3),22.
MLA Wang, Lingzhi,et al."Analysis on urban densification dynamics and future modes in southeastern Wisconsin, USA".PLOS ONE 14.3(2019):22.
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