Journal of Geographical Sciences ›› 2016, Vol. 26 ›› Issue (3): 272-296.doi: 10.1007/s11442-016-1268-1

• Orginal Article • Previous Articles     Next Articles

Scenario simulation and landscape pattern dynamic changes of land use in the PovertyBelt around Beijing and Tianjin: A case study of Zhangjiakou city, Hebei Province

SUN Piling1(),XU Yueping1(),YU Zhonglei2,LIU Qingguo3,XIE Baopeng1,LIU Jia1   

  1. 1. College of Resource and Environmental Sciences, China Agricultural University, Beijing 100193, China
    2. School of Geography, Beijing Normal University, Beijing 100875, China
    3. Qianjiang Xinhua Middle School, Chongqing 409000, China
  • Received:2015-04-15 Online:2016-03-20 Published:2016-03-20
  • Supported by:
    National Natural Science Foundation of China, No.41171088, No.41571087


Land use/cover change has been recognized as a key component in global change and has attracted increasing attention in recent decades. Scenario simulation of land use change is an important issue in the study of land use/cover change, and plays a key role in land use prediction and policy decision. Based on the remote sensing data of Landsat TM images in 1989, 2000 and 2010, scenario simulation and landscape pattern analysis of land use change driven by socio-economic development and ecological protection policies were reported in Zhangjiakou city, a representative area of the Poverty Belt around Beijing and Tianjin. Using a CLUE-S model, along with socio-economic and geographic data, the land use simulation of four scenarios-namely, land use planning scenario, natural development scenario, ecological-oriented scenario and farmland protection scenario-were explored according to the actual conditions of Zhangjiakou city, and the landscape pattern characteristics under different land use scenarios were analyzed. The results revealed the following: (1) Farmland, grassland, water body and unused land decreased significantly during 1989-2010, with a decrease of 11.09%, 2.82%, 18.20% and 31.27%, respectively, while garden land, forestland and construction land increased over the same period, with an increase of 5.71%, 20.91% and 38.54%, respectively. The change rate and intensity of land use improved in general from 1989 to 2010. The integrated dynamic degree of land use increased from 2.21% during 1989-2000 to 3.96% during 2000-2010. (2) Land use changed significantly throughout 1989-2010. The total area that underwent land use change was 4759.14 km2, accounting for 12.53% of the study area. Land use transformation was characterized by grassland to forestland, and by farmland to forestland and grassland. (3) Under the land use planning scenario, farmland, grassland, water body and unused land shrank significantly, while garden land, forestland and construction land increased. Under the natural development scenario, construction land and forestland increased in 2020 compared with 2010, while farmland and unused land decreased. Under the ecological-oriented scenario, forestland increased dramatically, which mainly derived from farmland, grassland and unused land. Under the farmland protection scenario, farmland was well protected and stable, while construction land expansion was restricted. (4) The landscape patterns of the four scenarios in 2020, compared with those in 2010, were more reasonable. Under the land use planning scenario, the landscape pattern tended to be more optimized. The landscape became less fragmented and heterogeneous with the natural development scenarios. However, under the ecological-oriented scenario and farmland protection scenario, landscape was characterized by fragmentation, and spatial heterogeneity of landscape was significant. Spatial differences in landscape patterns in Zhangjiakou city also existed. (5) The spatial distribution of land use could be explained, to a large extent, by the driving factors, and the simulation results tallied with the local situations, which provided useful information for decision-makers and planners to take appropriate land management measures in the area. The application of the combined Markov model, CLUE-S model and landscape metrics in Zhangjiakou city suggests that this methodology has the capacity to reflect the complex changes in land use at a scale of 300 m×300 m and can serve as a useful tool for analyzing complex land use driving factors.

Key words: land use change, Markov model, CLUE-S model, landscape metrics, Zhangjiakou city