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Open AccessArticle

Integration of Boosted Regression Trees and Cellular Automata—Markov Model to Predict the Land Use Spatial Pattern in Hotan Oasis

1
College of Water Conservancy, Yunnan Agricultural University, Kunming 650201, China
2
College of Agricultural Engineering, Hohai University, Nanjing 210098, China
3
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(4), 1396; https://doi.org/10.3390/su12041396 (registering DOI)
Received: 20 January 2020 / Revised: 6 February 2020 / Accepted: 7 February 2020 / Published: 13 February 2020
(This article belongs to the Special Issue Modelling Land Use Change and Environmental Impact)
The simulation and prediction of the land use changes is generally carried out by cellular automata—Markov (CA-Markov) model, and the generation of suitable maps collection is subjective in the simulation process. In this study, the CA-Markov model was improved by the Boosted Regression Trees (BRT) to simulate land use to make the model objectively. The weight of ten driving factors of the land use changes was analyzed in BRT, in order to produce the suitable maps collection. The accuracy of the model was verified. The outcomes represent a match of over 84% between simulated and actual land use in 2015, and the Kappa coefficient was 0.89, which was satisfactory to approve the calibration process. The land use of Hotan Oasis in 2025 and 2035 were predicted by means of this hybrid model. The area of farmland, built-up land and water body in Hotan Oasis showed an increasing trend, while the area of forestland, grassland and unused land continued to show a decreasing trend in 2025 and 2035. The government needs to formulate measures to improve the utilization rate of water resources to meet the growth of farmland, and need to increase ecological environment protection measures to curb the reduction of grass land and forest land for the ecological health. View Full-Text
Keywords: land use change; CA-Markov model; boosted regression trees; Hotan Oasis land use change; CA-Markov model; boosted regression trees; Hotan Oasis
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Wang, S.; Jiao, X.; Wang, L.; Gong, A.; Sang, H.; Salahou, M.K.; Zhang, L. Integration of Boosted Regression Trees and Cellular Automata—Markov Model to Predict the Land Use Spatial Pattern in Hotan Oasis. Sustainability 2020, 12, 1396.

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