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Wang Y.,Guangzhou Institute of Geography | Zhao L.,Guangzhou Institute of Geography | Zhao L.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Sobkowiak L.,Adam Mickiewicz University | And 2 more authors.
Journal of Geographical Sciences | Year: 2015

In this study, housing prices data for residential quarters from the period 2001–2012 were used and Global Differentiation Index (GDI) was established to measure the overall differentiation trend in housing prices in Yangzhou City, eastern China. Then the influence of the natural landscape and environment on prices of global housing market and housing submarkets was evaluated by the hedonic price model. The results are shown as follows. (1) There have been increasing gaps among housing prices since 2001. In this period, the differentiation trend has shown an upward fluctuation, which has been coupled with the annual growth rate of housing prices. (2) The spatial distribution of residential quarters of homogenous prices has changed from clustered in 2001 into dispersed in 2012. (3) Natural landscape and environmental externalities clearly influence spatial differentiation of housing prices. (4) In different housing submarkets, the influence of natural landscape and environmental externalities are varied. Natural landscape characteristics have significant impact on housing prices of ordinary commercial houses and indemnificatory houses, while the impact of environmental characteristics have obvious influence on housing prices of cottages and villas. © 2015, Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg.

Zhou M.,Huazhong University of Science and Technology | Cai Y.,Peking University | Guan X.,National Academy for Mayors of China | Tan S.,Huazhong University of Science and Technology | Lu S.,Beijing Forestry University
Chinese Geographical Science | Year: 2014

Land scarcity has become the prominent obstacle on the way to sustainable development for China. Under the constraints of land shortage, how to allocate the finite land resources to the multiple land users in China considering various political, environmental, ecological and economic conditions have become research topics with great significance. In this study, an interval fuzzy national-scale land-use model (IFNLM) was developed for optimizing land systems of China. IFNLM is based on an integration of existing interval linear programming (ILP), and fuzzy flexible programming (FFP) techniques. IFNLM allows uncertainties expressed as discrete interval values and fuzzy sets to be incorporated within a general optimization framework. It can also facilitate national-scale land-use planning under various environmental, ecological, social conditions within a multi-period and multi-option context. Then, IFNLM was applied to a real case study of land-use planning in China. The satisfaction degree of environmental constraints is between 0.69 and 0.97, the system benefit will between 198.25 × 1012 USD and 229.67 × 1012 USD. The results indicated that the hybrid model can help generate desired policies for land-use allocation with a maximized economic benefit and minimized environmental violation risk. Optimized land-use allocation patterns can be generated from the proposed IFNLM. © 2014, Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag Berlin Heidelberg.

Lu S.,Beijing Forestry University | Guan X.,National Academy for Mayors of China | Zhou M.,Huazhong University of Science and Technology | Wang Y.,Guangzhou Institute of Geography
Environmental Management | Year: 2014

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty. © 2014 Springer Science+Business Media.

Fang C.L.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Guan X.L.,National Academy for Mayors of China | Lu S.S.,Beijing Forestry University | Zhou M.,Peking University | Deng Y.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research
Urban Studies | Year: 2013

Urban agglomerations (UAs) in China play a vital role in the distribution of productive forces and constitute the most dynamic and potentially rich core areas for future economic development. However, the rapid economic growth and high-intensity interactions seen in relation to these areas, results of the high population densities and aggregation of industries in UAs, also pose significant ecological threats to the environment. This paper attempts to analyse changing trends in the input-output efficiency of UAs in China based on the data envelopment analysis (DEA) approach. The paper investigates the DEA efficiency of UAs with different population sizes and geographical locations, explores the relationship between the elements that make up a decomposed model of efficiency and compares the efficiency performance of China's UAs with that of 35 central cities. Moreover, the exogenous factors determining the input-output efficiency of UAs, the question of how to improve UAs' efficiency performance, as well as the focus of future research are also discussed. A number of valuable implications have been drawn from the study, which may be helpful to the task of understanding more deeply the high-density aggregation effects of UAs in China. © 2013 Urban Studies Journal Limited.

Lu S.,Beijing Forestry University | Zhou M.,Huazhong University of Science and Technology | Guan X.,National Academy for Mayors of China | Tao L.,Wuhan University
Environmental Science and Pollution Research | Year: 2015

A large number of mathematical models have been developed for supporting optimization of land-use allocation; however, few of them simultaneously consider land suitability (e.g., physical features and spatial information) and various uncertainties existing in many factors (e.g., land availabilities, land demands, land-use patterns, and ecological requirements). This paper incorporates geographic information system (GIS) technology into interval-probabilistic programming (IPP) for land-use planning management (IPP-LUPM). GIS is utilized to assemble data for the aggregated land-use alternatives, and IPP is developed for tackling uncertainties presented as discrete intervals and probability distribution. Based on GIS, the suitability maps of different land users are provided by the outcomes of land suitability assessment and spatial analysis. The maximum area of every type of land use obtained from the suitability maps, as well as various objectives/constraints (i.e., land supply, land demand of socioeconomic development, future development strategies, and environmental capacity), is used as input data for the optimization of land-use areas with IPP-LUPM model. The proposed model not only considers the outcomes of land suitability evaluation (i.e., topography, ground conditions, hydrology, and spatial location) but also involves economic factors, food security, and eco-environmental constraints, which can effectively reflect various interrelations among different aspects in a land-use planning management system. The case study results at Suzhou, China, demonstrate that the model can help to examine the reliability of satisfying (or risk of violating) system constraints under uncertainty. Moreover, it may identify the quantitative relationship between land suitability and system benefits. Willingness to arrange the land areas based on the condition of highly suitable land will not only reduce the potential conflicts on the environmental system but also lead to a lower economic benefit. However, a strong desire to develop lower suitable land areas will bring not only a higher economic benefit but also higher risks of violating environmental and ecological constraints. The land manager should make decisions through trade-offs between economic objectives and environmental/ecological objectives. © 2014, Springer-Verlag Berlin Heidelberg.

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