A hybrid inexact optimization model for land-use allocation of China

Zhou, Min; Cai, Yong; Guan, Xingliang; Tan, Shukui; Lu, Shasha

doi:10.1007/s11769-014-0708-z

Cited by 23 publications

(8 citation statements)

References 27 publications

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“…It subsequently decreases rapidly in the last 4 years. The development of secondary and tertiary industry increases the amount of land required for construction (Su et al, 2014a,c), and the process of agricultural land conversion is driven by the local government to finance urban infrastructure and transportation (Tan et al, 2009;Zhou et al, 2015). The expansion of construction land increases the insecurity of the agricultural land because it is held publically under a household responsibility system.…”

Section: Impulse Response Function Analysismentioning

confidence: 99%

Impact of urbanization on pollution-related agricultural input intensity in Hubei, China

You

2016

Ecological Indicators

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a b s t r a c tAgricultural input intensity increases significantly during the rapid urbanization in China, which has contributed to the increasingly serious non-point pollution. Using the vector autoregression (VAR) model, this study analyzes the impact of urbanization on pollution-related agricultural input intensity in Hubei, China. Results of an impulse response function analysis reveal that pesticide use intensity continues to rise following shocks from the urban population proportion and the secondary and tertiary industry proportion. Responses of chemical fertilizer intensity first decrease and then increase subjected to the shocks from the urban population proportion and secondary and tertiary industry proportion. The intensity of agricultural plastic film use first increases and then decreases when receives the shocks from the urban population proportion which is the opposite to the response to the shock from the secondary and tertiary industry proportion. In addition, the responses of pesticide use intensity, chemical fertilizer use intensity and agricultural plastic film use intensity trend decrease following their own shocks after positive initial responses. The variance decomposition results demonstrate that the shocks due to pesticide use intensity, chemical fertilizer use intensity and agricultural plastic film use intensity generally explain the largest proportion of their own variation over the 10-year horizon. However, an increase in the urban population proportion plays a critical role in determining the variations of pesticide use intensity in late periods, it account for 56.88% the variations in the tenth period. And the contribution of the urban population proportion to the variations in agricultural plastic film use intensity increases consistently, it account for 33.74% of the variations in the tenth period. Therefore, the hidden drivers of these phenomena need to be further understood regarding the relationships between urbanization and diffuse pollution from agricultural production.

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Section: Impulse Response Function Analysismentioning

confidence: 99%

Impact of urbanization on pollution-related agricultural input intensity in Hubei, China

You

2016

Ecological Indicators

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“…According to Zhou et al (2013Zhou et al ( , 2014, an interval fuzzy programming (IFP) model can be expressed as follows:…”

Section: Appendix: the Ifp Modelmentioning

confidence: 99%

An interval fuzzy land-use allocation model (IFLAM) for Beijing in association with environmental and ecological consideration under uncertainty

et al. 2014

Self Cite

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In this study, an interval fuzzy land-use allocation method (IFLAM) is developed for the planning of urban land-use allocation system. The developed IFLAM method is based on interval parameter programming technique and fuzzy flexible programming, which could handle uncertainties expressed as interval values and fuzzy sets in the model's left-and righthand sides and objective function. A management problem for allocating land resources of Beijing, the capital of China, is studied to illustrate applicability of the proposed IFLAM approach. Results show that the optimized λ values (which means the satisfaction degree of all model constraints) are in the range of [0.67, 0.89], and the corresponding system benefit is between $ [534.03, 698.75] × 10 12 and $ [961.37, 1028.33] × 10 12 while the optimized urban land in the first studying period will be [71905, 77894] ha in the Function Central Zone, [35219, 39711] ha in the Function Extended Zone, [22012, 30547] ha in the New Urban Zone and [17609, 22910] ha in the Eco-Conservation Zone. Results indicate that reasonable solutions have been generated under various environmental, ecological and social conditions. They can help decision makers to identify desired alternatives for making the utmost of land resources of Beijing and for providing services for urban land management 123 M. Zhou et al.decisions; moreover, they are helpful for land managers to gain insight into the tradeoff between economic objective and eco-environment violation risk.

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“…Based on the review and sorting of existent related literature, these models could be divided into the following categories: first, spatial optimization models [1,2,3,4,5,6,7,8,9,10,11,12,13,14]—the core problem of which lies in how to properly adjust and control the spatial relations among land-use resources so as to make their spatial structure reaches an optimal status which best meets the requirement of a sustainable development target. Second, programming models [15,16,17,18,19,20,21,22], including linear programming models, multi-objective programming models, and non-linear programming models, generally apply mathematical models to achieve the best outcome such as maximum profit or lowest cost. Third, simulation models [12,23,24,25,26,27,28,29,30,31,32], which provide the process of creating and analyzing a digital land-use prototype of a model to predict its performance in the real world.…”

Section: Introductionmentioning

confidence: 99%

Land Suitability Evaluation and an Interval Stochastic Fuzzy Programming-Based Optimization Model for Land-Use Planning and Environmental Policy Analysis

Zuo

Zhou

et al. 2019

IJERPH

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People explosion and fast economic growth are bringing a more serious land resource shortage crisis. Rational land-use allocation can effectively reduce this burden. Existing land-use allocation models may deal with a lot of challenges of land-use planning. This study proposed a hybrid quantitative and spatial optimization land-use allocation model that could enrich the land-use allocation method system. This model has three advantages compared to former methods: (1) this model can simultaneously solve the quantitative land area optimization problem and spatial allocation problem, which are the two core aspects of land-use allocation; (2) the land suitability assessment method considers various geographical, economic and environmental factors which are essential to land-use allocation; (3) this model used an interval stochastic fuzzy programming land-use allocation model to solve the quantitative land area optimization problem. This model not only considers three uncertainties in the natural system but also involves various economic, social, ecological and environmental constraints—most of which are specifically put into the optimization process. The proposed model has been applied to a real case study in Liannan county, Guangdong province, China. The results could help land managers and decision makers to conduct sound land-use planning/policy and could help scientists understand the inner contradiction among economic development, environmental protection, and land use.

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A hybrid inexact optimization model for land-use allocation of China

Cited by 23 publications

References 27 publications

Impact of urbanization on pollution-related agricultural input intensity in Hubei, China

Impact of urbanization on pollution-related agricultural input intensity in Hubei, China

An interval fuzzy land-use allocation model (IFLAM) for Beijing in association with environmental and ecological consideration under uncertainty

Land Suitability Evaluation and an Interval Stochastic Fuzzy Programming-Based Optimization Model for Land-Use Planning and Environmental Policy Analysis

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