An Evaluation and Region Division Method for Ecosystem Service Supply and Demand Based on Land Use and POI Data

Yuchun Pan,Yu Liu,Xiumei Tang

doi:10.3390/su12062524

Abstract

Mastering the regional spatial differences of ecosystem service supply and ecosystem service demand is of great significance to scientifically planning the development and utilization of national land and maintaining healthy development of ecosystems. Based on the relationship analysis of ecosystem service supply and ecosystem service demand, this study explored the regional ecosystem service supply by ecosystem service value based on grid data and constructed an ecosystem service demand evaluation model that integrated the construction land ecosystem service demand equivalent for static aspects and the point of interest (POI) kernel density estimation for dynamic aspects on the basis of land use and POI data. In the end, it put forward a region division method for ecosystem service supply and ecosystem service demand and conducted an empirical analysis of Haidian District, Beijing. The following results were concluded: (1) the ecosystem service value of different grids in Haidian District was between RMB (Chinese monetary unit, Yuan) 0 and RMB 2.4787 million. In terms of spatial distribution, the ecosystem service supply took on an obvious trend of gradual decrease from the northwest to the southeast, with major ecosystem service supply coming from the northwest. (2) The construction land ecosystem service demand equivalent of Haidian District was characterized by a multicenter cluster: the high equivalent area was in the southeast, while the equivalent of the northwest was relatively low. POI kernel density estimation demonstrated cluster distribution, with a high kernel density estimation in the southeast, a lower kernel density estimation in the central part, and the lowest kernel density estimation in the northwest. The ecosystem service demand index also showed cluster distribution: high index in the southeast, low index in the northwest, and prominent sudden changes from the central part to the south. (3) The bivariate local spatial autocorrelation cluster diagram method was used to divide five types of ecosystem service supply and ecosystem service demand, namely non-significant correlation region, high ecosystem service supply and high ecosystem service demand region, high ecosystem service supply and low ecosystem service demand region, low ecosystem service supply and high ecosystem service demand region, low ecosystem service supply and low ecosystem service demand region. Grids with the highest ratio belonged to the non-significant correlation region; the distribution of low ecosystem service supply and high ecosystem service demand region had the greatest concentration, mainly in the southeast; the grids of high ecosystem service supply and low ecosystem service demand region were mainly present in the northwest and in a continuous way; the grids of low ecosystem service supply and low ecosystem service demand region, and high ecosystem service supply and high ecosystem service demand region were extremely few, with sporadic distribution in the central part. The research results could provide a basis for the adjustment and fine management of regional land use structure.

Highlights

Human unceasing pursuit of economic development and changes in land use pattern have influenced the ecosystem structure and process and changed the supply capacity of ecosystems [1,2,3]
As shown in the picture, the ecosystem service value (ESV) of the south and the midwest in Haidian District was on the low side, and the value of most grids was lower than RMB 200,000; the ESV of the central part and the north was mostly between RMB 200,000 and RMB 500,000 while few grids were between RMB 500,000 and RMB 800,000; the grid value of the northwest was higher, and the value of most grids was more than RMB 1.2 million
This study proposed an ecosystem service supply (ESS) and ecosystem service demand (ESD) evaluation method based on land use and point of interest (POI) data, and different regions of ESS and ESD were identified

Summary

Introduction

Human unceasing pursuit of economic development and changes in land use pattern have influenced the ecosystem structure and process and changed the supply capacity of ecosystems [1,2,3]. The development of internet technology has constantly enriched the geographic space big data, which is represented by mobile phone signaling data, especially GPS trajectory data and point of interest (POI) data Owing to characteristics such as large quantity, easiness to acquire, and explicit spatial location, they have been extensively applied in studies on the identification of urban commercial center [14,15]; coupling analysis of commerce, population, and transportation [16,17]; and the identification of green space service scope [18]. It assessed regional ESS and ESD based on land use and POI data, and five types of ESS and ESD were determined, with a view to putting forward an evaluation method suitable for small-scale ESS and ESD, providing a reference and basis for regional fine land use and structure adjustment, regional ecological environment protection, and landscape construction

Methods

Results

Conclusion