4.7 Article

Land Cover Changes and Their Driving Mechanisms in Central Asia from 2001 to 2017 Supported by Google Earth Engine

Journal

REMOTE SENSING
Volume 11, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/rs11050554

Keywords

land change; driving mechanism; Central Asia; spatiotemporal analysis; GEE

Funding

  1. Strategic Priority Research Program of Chinese Academy of Sciences [XDA20010202, XDA19040301]
  2. National Key Research and Development Plan Program in China [2016YFC0503701, 2016YFB0501502]
  3. Key Project of the High Resolution Earth Observation System in China [00-Y30B14-9001-14/16]

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Limited research has been published on land changes and their driving mechanisms in Central Asia, but this area is an important ecologically sensitive area. Supported by Google Earth Engine (GEE), this study used Landsat satellite imagery and selected the random forest algorithm to perform land classification and obtain the annual land cover datasets of Central Asia from 2001 to 2017. Based on the temporal datasets, the distributions and dynamic trends of land cover were summarized, and the key factors driving land changes were analyzed. The results show that (1) the obtained land datasets are reliable and highly accurate, with an overall accuracy of 0.90 +/- 0.01. (2) Grassland and bareland are the two most prominent land cover types, with area proportions of 45.0% and 32.9% in 2017, respectively. Over the past 17 years, bareland has displayed an overall reduction, decreasing by 2.6% overall. Natural vegetation (grassland, forest, and shrubland), cultivated land, water bodies and wetlands have displayed increasing trends at different rates. (3) The amount of precipitation and degree of drought are the driving factors that affect natural vegetation. The changes in cultivated land are mainly affected by precipitation and anthropogenic drivers. The effects of increasing urban populations and expanding industrial development are the factors driving the expansion of urban regions. The advantages and uncertainties arising from the land mapping and change detection method and the complexity of the driving mechanisms are also discussed.

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