Urban land-use planning under multi-uncertainty and multiobjective considering ecosystem service value and economic benefit - A case study of Guangzhou, China

Effective land-use planning considering ecosystem service value (ESV) is indispensable in facilitating economic development and eco-environment sustainability. In this study, a Monte-Carlo-based interval fuzzy De Novo programming (MC-IFDP) method is developed for land-use planning under uncertainty. MC-IFDP can achieve optimal system design to maximize multiple conflicting objectives simultaneously, and provide a number of alternatives for decision-makers. It can also address both stipulation uncertainty and parameter uncertainty in constraint and objective function. MC-IFDP is then applied to a real case for land-use planning of Guangzhou (China), where six scenarios related to different decision-makers' preferences are examined. Results reveal that (i) different decision-makers' preferences (denoted as S1 to S6) result in different land-use planning schemes, leading to varied satisfactory degrees, system benefits, ESVs and pollutant emissions; (ii) system benefit would reduce as satisfactory degree. decreases, which would be RMB(sic) [4287.5, 11025.7] x 10(9) with the degree of. being [0.43, 0.76]; (iii) under advantage condition (S1), the area of ecological land would increase from [455.1, 494.1] x 10(3) ha to [503.9, 537.8] x 10(3) ha from period 1 to period 2; the total ESV would expect to have an average annual growth rate of [1.3, 1.5] %; (iv) pollutant emissions (e.g., solid waste, sulfur dioxide, dust, COD, and NH3-N) would be mitigated over the planning horizon under all scenarios. The findings are rewarding for decision-makers to identify desired land-use planning strategies and coordinate the conflicts among satisfactory degree, economic benefit, ESV, and pollutant mitigation under multi-uncertainty.

Automated summary

A method for land-use planning under uncertainty was developed, showing that different decision-makers' preferences lead to different planning schemes with impacts on satisfactory degree, system benefits, ESV, and pollutant emissions. In all scenarios, pollutant emissions are expected to be mitigated over the planning horizon.