A Comparative Study of Various Land Use and Land Cover Change Models to Predict Ecosystem Service Value

Int J Environ Res Public Health. 2022 Dec 8;19(24):16484. doi: 10.3390/ijerph192416484.

Abstract

Ecosystem services are closely related to human well-being and are vulnerable to high-intensity human land-use activities. Understanding the evolution of land use and land cover (LULC) changes and quantifying ecosystem service value (ESV) are significant for sustainable development. In this study, we used land use and land cover data and other data from 2000 to 2020 to analyze the evolution of land use and land cover and ESV in Tongliao, China. With the goal of exploring the characteristics of different cellular automata (CA)-based models, CA-Markov, Future Land Use Simulation (FLUS), and Patch-generating Land Use Simulation (PLUS) models were used to simulate future land use and land cover, and the results were verified and compared. Considering the impacts of policies for capital farmland (CF) and ecological protection red line (EPRL) in the context of territorial spatial planning, four scenarios (inertial development, S1; CF, S2; EPRL, S3; EPRL and CF, S4) were set. The results showed that from 2000 to 2020, farmland and built-up land increased the most (341.18 km2 and 220.56 km2), while grassland had the largest decrease (380.08 km2). The main mutual transitions were from grassland and farmland. The total ESV showed a decreasing trend (from 52,364.56 million yuan to 51,620.62 million yuan). The simulation results for 2035 under four scenarios were similar, where farmland would decrease the most (96.81 km2). The ESV in 2035 would decrease from 51,620.62 million yuan to 51,541.12 million. In addition, under scenarios for the impact of policy, the land showed a trend of scattered expansion. This study provides a scientific basis for making regional sustainable development policy decisions and implementing ecological environmental protection measures.

Keywords: LULC change analysis; Tongliao city; different cellular automata (CA)-based models; ecosystem service value; policy impact.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Conservation of Natural Resources*
  • Ecosystem*
  • Farms
  • Humans
  • Sustainable Development

Grants and funding

This research was funded by the National Natural Science Foundation of China, grant number 52170186.