How China's linked urban-rural construction land policy impacts rural landscape patterns: a simulation study in Tianjin, China

Authored by Guangjin Tian, Bingran Ma, Lingqiang Kong, Xiaojuan Liu

Date Published: 2018

DOI: 10.1007/s10980-018-0669-1

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

To prevent the area of arable land from crossing the limit of 120 million ha arable land red line, China's government proposed a linked urban-rural construction land policy. This policy helps to protect the arable land but will impact the rural landscape. The objective is to evaluate the effect of the linked urban-rural construction land policy on rural landscape in the future. We performed a simulation method to predict the rural landscape pattern changes in Tianjin during 2005-2020 using a cellular automata and multi-agent system model under the scenarios with or without implementing this policy. The landscape metrics were calculated for both scenarios to find the effects caused by this policy. Following this policy, the Total Area and Large Patch Index of arable land decreased slowly. 65.50\% of the occupied arable land can be compensated. For rural settlements, the Mean Patch Area increased to 2.87 times that in 2005. Number of Patches reduced greatly, and 1053 of the total rural settlements distributed along the periphery of Tianjin were reclaimed for arable land during 2005-2020. Aggregation Index increased greatly. According to the simulation model, the policy is effective on slowing down the loss of total arable land and the process of large arable land fragmentation. The increasing degree of aggregation of rural settlements is beneficial to the optimal allocation of resources and rural centralized management. However, as the rural settlements gather to urban construction land, they are more vulnerable to urban issues.

Tags

Agent-based model Cellular automata Multi-agent system Biodiversity growth Cellular-automata Region Expansion Metrics Linked urban-rural construction land policy Rural landscape pattern Driving forces Sustainable development