Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China
By Liping Chen, Sun Yujun, S. Saeed. PLoS ONE, 2018
457 citations recorded by the source corpus.
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.
Subfields: Atmospheric Science, Ecology, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/800ba54dfe42b091e29c92464be535b08d88a783
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In Atmospheric Science
In Ecology
In Global and Planetary Change
Citations in the corpus
- Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton (2019, methodology): “For instance, in China, a land use change model was developed using geographic information system (GIS) to monitor and predict change in the land [12,16,23,28].”