Yizhou Wu

Dr. Yizhou Wu


Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 January 2015 in Sustainability
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XCXiaoteng Cen
Xiaoteng Cen
CWCifang Wu
Cifang Wu
XXXiaoshi Xing
Xiaoshi Xing
MFMing Fang
Ming Fang
ZGZhuoma Garang
Zhuoma Garang
YWYizhou Wu
Yizhou Wu
Despite the unprecedented rate of urbanization throughout the world, human society is still facing the challenge of coordinating urban socioeconomic development and ecological conservation. In this article, we integrated socioeconomic data and spatial metrics to investigate the coupling relationship between intensive land use (ILU) system and landscape ecological security (LES) system for urban sustainable development, and to determine how these systems interact with each other. The values of ILU and LES were first calculated according to two evaluation subsystems under the pressure-state-response (PSR) framework. A coupling model was then established to analyze the coupling relationship within these two subsystems. The results showed that the levels of both subsystems were generally increasing, but there were several fluctuation changes in LES. The interaction in each system was time lagged; urban land use/cover change (LUCC) and ecosystem transformation were determined by political business cycles and influenced by specific factors. The coupling relationship underwent a coordinated development mode from 1992–2012. From the findings we concluded that the coupling system maintained a stable condition and underwent evolving threshold values. The integrated ILU and LES system was a coupling system in which subsystems were related to each other and internal elements had mutual effects. Finally, it was suggested that our results provided a multi-level interdisciplinary perspective on linking socioeconomic-ecological systems. The implications for urban sustainable development were also discussed.

23 June 2020 in Social Indicators Research
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YWYizhou Wu
Yizhou Wu
XZXiaohong Zheng
Xiaohong Zheng
LSLi Sheng
Li Sheng
HYHeyuan You
Heyuan You

22 May 2010 in Acta Crystallographica Section E Structure Reports Online
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QLQiu-Yue Lin
Qiu-Yue Lin
NWNa Wang
Na Wang
YWYizhou Wu
Yizhou Wu
The title polymer, [Zn(3)(C(8)H(8)O(5))(2)(C(3)H(3)N(2))(2)(C(3)H(4)N(2))(2)](n), was formed by the reaction of zinc acetate with imidazole and 7-oxabicyclo-[2.2.1]heptane-2,3-dicarboxylic anhydride (norcan-tharidine). One of the two crystallographically unique Zn(II) atoms is four-coordinated by three N atoms of three imidazole ligands, two of which are deprotonated, and by one carboxyl-ate O atom of the demethyl-cantharate anion. The second Zn(II) atom is situated on an inversion centre and is six-coordinated by the bridging O atoms of two symmetry-related demethyl-cantharate anions and by four carboxyl-ate O atoms of the corresponding carboxyl-ate groups. The polymeric crystal structure is additionally stabilized by N-H⋯O hydrogen bonding between the imidazole ligands and carboxyl-ate O atoms.

5 November 2026 in Sustainability
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ACAnan Chen
Anan Chen
YWYizhou Wu
Yizhou Wu
Aligning regional innovation capability with territorial space use efficiency (TSUE) is important for regional sustainable development. Using data from 2010 to 2020, this study examines their spatiotemporal patterns and matching-type transitions in the Pearl River Delta urban agglomeration through entropy-weighted TOPSIS, a super-efficiency slacks-based measure (SBM) model incorporating undesirable outputs, and four-quadrant analysis. The results show that: (1) Both innovation capability and TSUE increased overall, but innovation disparities widened while efficiency disparities narrowed. (2) The composition of matching types shifted toward a predominance of high–high and innovation-lagging units. A core–periphery pattern was evident, with high–high units concentrated along the Pearl River Estuary and innovation-lagging units widespread in peripheral areas. (3) Matching types exhibited substantial persistence, alongside prominent transitions from low–low to innovation-lagging and from efficiency-lagging to high–high. High–high and innovation-lagging units showed particularly strong persistence, although some reversals also occurred. These findings support differentiated and locally adapted spatial governance: high–high areas should enhance spatial quality and innovation diffusion; innovation-lagging areas should strengthen innovation capability; efficiency-lagging areas should prioritize site-specific industrial-land regeneration and functional restructuring; and low–low areas should improve infrastructure and industrial conditions while gradually cultivating innovation capacity.