The Forecast and Low-carbon Performance of Land-use in Rapid Urbanization Area under the Multi-objective Spatial Planning: Evidence from Hangzhou, China

Abstract

Abstract The introduction of the carbon peak and carbon neutral targets by many countries’ central governments has put low-carbon oriented spatial planning at the forefront of discussions. However, few studies have focused on the balance of carbon emission reduction and economic goals in spatial planning, and the influence of the planning on land-use low-carbon performance remains uncertain. This study addresses this gap by conducting an empirical analysis in the rapidly urbanizing area of Hangzhou, China, taking into consideration low-carbon constraints and economic development demands. Using the STRIPAT model and Linear Programming-Markov, we predicted land use structures under both low-carbon and baseline scenario, and simulated land use patterns by using Ann-CA. The results showed rapid growth in urban and forest land, and a decline in farm and rural land under the low-carbon scenario. Urban land change was concentrated in downtown districts and suburbs, while farm and forest land change was concentrated in exurban areas. The low-carbon performance of land-use was reflected in carbon storage release, carbon emission capability change, and low-carbon capability. The most common conversion of land-use categories under the low-carbon scenario was between farm and forest land, and between rural and urban land, which resulted in less carbon storage release and carbon emissions compared to the baseline scenario. Additionally, the compactness and fragmentation of construction land improved under the low-carbon scenario. This study sheds light on the impact of multi-objective spatial planning on urban land expansion, providing empirical evidence for city governments in rapid urbanization areas to improve land-use efficiency.