G2TT
来源类型Articles
规范类型论文
DOI10.1016/j.jaridenv.2015.08.008
ISSN0140-1963
Analysing irrigated crop rotation patterns in arid Uzbekistan by the means of remote sensing: A case study on post-Soviet agricultural land use
Aini, F.K.; Hergoualc'h, K.; Smith, J.U.; Verchot, L.V.
发表日期2016
出处Journal of Arid Environments 124: 150-159
出版年2016
语种英语
摘要

In Central Asia, actual cotton rotation practices are repeatedly believed to resemble “Soviet cropping conditions” with continuous cotton sequences of six years or more. We investigated current cotton growing patterns in Khorezm, one representative cotton production region in Uzbekistan utilizing time series of 250-m MODIS satellite data. A Random Forest model was established using reference data of 2004–2007 to generate annual crop maps in 2000–2009. A linear model was applied to assess the spatial distribution of the longest observed cotton sequence within the ten-year observation period. All cotton-growing sequences were compared to the national crop rotation recommendations.
The classification achieved an overall accuracy of 82%. We found that cotton remains the major crop in the region. It was cultivated for more than five out of the ten years on 46.5% of the cropland. But “Soviet cropping conditions” on less than 20% and officially recommended cotton sequences on more than 50% of the cropland challenge the notion that cotton mono-crop dominates Central Asia. Statistical analysis revealed that long cotton sequences preferably occur on fields far from settlements and under reduced soil suitability for irrigation. The results enable decision makers to better explain unfavourable cotton cultivation practices and to stimulate improvements.

主题crop production ; arid zones ; remote sensing ; cotton
区域Central Asia,Uzbekistan
URLhttps://www.cifor.org/library/5708/
来源智库Center for International Forestry Research (Indonesia)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/93249
推荐引用方式
GB/T 7714
Aini, F.K.,Hergoualc'h, K.,Smith, J.U.,et al. Analysing irrigated crop rotation patterns in arid Uzbekistan by the means of remote sensing: A case study on post-Soviet agricultural land use. 2016.
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