Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques-A case study of a hilly area, Jiangle, China

PLoS One. 2018 Jul 13;13(7):e0200493. doi: 10.1371/journal.pone.0200493. eCollection 2018.

Abstract

Land use and land cover change research has been applied to landslides, erosion, land planning and global change. Based on the CA-Markov model, this study predicts the spatial patterns of land use in 2025 and 2036 based on the dynamic changes in land use patterns using remote sensing and geographic information system. CA-Markov integrates the advantages of cellular automata and Markov chain analysis to predict future land use trends based on studies of land use changes in the past. Based on Landsat 5 TM images from 1992 and 2003 and Landsat 8 OLI images from 2014, this study obtained a land use classification map for each year. Then, the genetic transition probability from 1992 to 2003 was obtained by IDRISI software. Based on the CA-Markov model, a predicted land use map for 2014 was obtained, and it was validated by the actual land use results of 2014 with a Kappa index of 0.8128. Finally, the land use patterns of 2025 and 2036 in Jiangle County were determined. This study can provide suggestions and a basis for urban development planning in Jiangle County.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • China
  • Conservation of Natural Resources / methods*
  • Environmental Monitoring / methods*
  • Geographic Information Systems*
  • Geography
  • Markov Chains
  • Models, Statistical
  • Remote Sensing Technology*
  • Software
  • Urbanization*

Grants and funding

This study was supported by the Introduce Project of Forest Multifunction Management Science and Technology of Forplan System (No.2015-4-31). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.