Spatio-Temporal Patterns of Cropland Conversion in Response to the "Grain for Green Project" in China's Loess Hilly Region of Yanchuan County

نویسندگان

  • Jieyong Wang
  • Yansui Liu
  • Zhigao Liu
چکیده

To prevent environmental degradation, China’s central government launched the “Grain for Green Project” (GGP) in 1999. Since its beginning, the effects and influences of the GGP have been hotly debated among domestic and international scholars and policymakers. This paper is taking the County of Yanchuan in the Loess Plateau as a case study, examines the spatio-temporal patterns of cropland conversion in response to the GGP. This research is methodologically based on remote sensing (RS) and geographic information systems (GIS), and also employs personal interviews with local government officials and farmers. The results show that land use/cover patterns in Yanchuan County have changed dramatically after the implementation of GGP. Cropland has decreased remarkably, while orchard land and sparse forest has increased significantly: 23.84% of cropland was converted to orchard, and 22.25% to sparse forest. Simultaneously, the landscape has become more fragmented but also more diversified, forestland has become more dominant. A total of 61.19% of the total converted cropland was on slopes greater than 15 degrees, 64.85% of which was lower-grade land. The converted cropland is mostly located in more accessible areas for convenient management. Partially affected by farmers’ self-willingness, sloping cropland was preferred to orchard (economic forest), and some gentle slope (less than 15 degrees) or higher-grade cropland were involved in the GGP. To maintain and reinforce the achievements of the GGP and further contribute to the GGP’s sustainability and rural development, the paper recommends that the Chinese government should build a continuous compensation mechanism for the households who lost cropland for the GGP while improving the productivity of flat cropland. OPEN ACCESS Remote Sens. 2013, 5 5643

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عنوان ژورنال:
  • Remote Sensing

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2013