A Multi-Scenario Land Expansion Simulation Method from Ecosystem Services Perspective of Coastal Urban Agglomeration: A Case Study of GHM-GBA, China

Abstract

Balancing urban development and ecosystem conservation in the context of natural resource scarcity can provide scientific guidance for land use planning. We integrated research methods, such as ecosystem services (ES) assessment, coastal vulnerability assessment, multi-objective linear planning, and land use change simulation, to develop a new model framework for multi-scenario urban land expansion simulation based on ecosystem services. In relation to the land use scale and constraints, we simulated three types of scenarios in 2035, including a status quo continuity scenario (SCS), economic development scenario (EDS), and ecological protection scenario (EPS), to explore the ideal land use optimization strategies to enhance ES and land use efficiency. The results indicated that the scale of construction land under the three scenarios grew, and arable land and grassland had the largest losses. The continued urban expansion in the Guangdong–Hong Kong–Macao Greater Bay Area has already had a significant negative impact on ecosystem services and could result in a total ESV loss of USD 28.1 billion by 2035 if an economic-first development model is adopted. Based on the hotspots of urban construction land expansion in the ecological–economic priority game, we proposed a classification and optimization strategy for land use, including proactive restoration of damaged ecological spaces with high ESVs (Zhaoqing City and Huizhou City), optimization of green space quality and formation of ecological corridors (Guangzhou City, Shenzhen City, Hong Kong, and Macao), and implementation of natural resource conservation planning and spatial regulation in the urban–rural integration area (Foshan City and Dongguan City). This research framework scientifically allocates the “quality” of ecosystem values and “quantity” of natural resources and provides a reference for regional “bottom-up” territorial spatial planning.