Identifying optimal land-use patterns using a copula-based interval stochastic programming model for urban agglomeration under uncertainty

Abstract

In this study, a copula-based interval stochastic programming (CISP) model is developed for land-use planning management (LUPM), where uncertainties presented as interval values and random variables can be tackled. CISP can also reflect the interactions among random variables with different probability distributions. A CISP-LUPM model is formulated for identifying desired land-use patterns for the Guangzhou-Zhongshan urban agglomeration. Solutions related to land-use pattern, ecosystem services value (ESV), and system benefit have been generated under multiple scenarios with different constraint-violation levels. Results reveal that the forest and grass cover rate for the urban agglomeration would be [42.0, 44.4] % under synergistic scheme at the end of planning period. Results also show that the ESV supported by water area accounts for [44.6, 46.3] % the total ESVs, and waterbody plays a major role in maintaining the balance of the urban agglomeration ecosystem. Results also disclose that, under the influence of interactive ecological factors, the change in land-use patterns for Guangzhou is more sensitive to system violation-risk level than that for Zhongshan. The findings are helpful for reflecting interaction among ecological factors and disclosing their joint effects on land-use patterns, thus supporting an in-depth analysis of tradeoff between socio-economic development and ecological sustainability.