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首页> 外文期刊>International journal of remote sensing >Improved estimates of opium cultivation in Afghanistan using imagery-based stratification
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Improved estimates of opium cultivation in Afghanistan using imagery-based stratification

机译:使用基于图像的分层方法改进对阿富汗鸦片种植的估计

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摘要

The United Nations Office on Drugs and Crime and the US Government make extensive use of remote sensing to quantify and monitor trends in Afghanistan's illicit opium production. Cultivation figures from their independent annual surveys can vary because of systematic differences in survey methodologies relating to spectral stratification and the addition of a pixel buffer to the agricultural area. We investigated the effect of stratification and buffering on area estimates of opium poppy using SPOT5 imagery covering the main opium cultivation area of Helmand province and sample data of poppy fields interpreted from very high resolution satellite imagery. The effect of resolution was investigated by resampling the original 10 m pixels to 20, 30, and 60 m, representing the range of available imagery. The number of strata (1, 4, 8, 13, 23, 40) and sample fraction (0.2-2%) used in the estimate were also investigated. Stratification reduced the confidence interval by improving the precision of estimates. Cultivation estimates of poppy using 40 spectral strata and a sample fraction of 1.1% had a similar precision to direct expansion estimates using a 2% sample fraction. Stratified estimates were more robust to changes in sample size and distribution. The mapping of the agricultural area had a significant effect on poppy cultivation estimates in Afghanistan, where the area of total agricultural production can vary significantly between years. The findings of this research explain differences in cultivation figures of the opium monitoring programmes in Afghanistan and recommendations can be applied to improve resource monitoring in other geographic areas.
机译:联合国毒品和犯罪问题办公室和美国政府广泛使用遥感来量化和监测阿富汗非法鸦片生产的趋势。他们独立的年度调查得出的耕种数字可能会有所不同,这是因为与光谱分层相关的调查方法存在系统差异,并且在农业区域增加了像素缓冲区。我们使用覆盖赫尔曼德省主要鸦片种植区的SPOT5图像和从超高分辨率卫星图像解释的罂粟田样数据,研究了分层和缓冲处理对罂粟面积估计的影响。通过将原始的10 m像素重采样到20、30和60 m(代表可用图像的范围)来研究分辨率的影响。还研究了估计中使用的层数(1、4、8、13、23、40)和样本分数(0.2-2%)。分层通过提高估计的精度来减小置信区间。使用40个光谱层和1.1%样品分数的罂粟种植估算值与使用2%样品分数的直接扩展估算值具有相似的精度。分层估计对于样本量和分布的变化更为稳健。农业区域的测绘对阿富汗的罂粟种植估计有重大影响,阿富汗的农业总生产面积在几年之间可能有很大的不同。这项研究的结果解释了阿富汗鸦片监测计划的种植数字存在差异,可以提出建议来改善其他地理区域的资源监测。

著录项

  • 来源
    《International journal of remote sensing》 |2017年第14期|3785-3799|共15页
  • 作者单位

    Cranfield Univ, Cranfield MK43 0AL, Beds, England;

    Cranfield Univ, Cranfield MK43 0AL, Beds, England;

    Cranfield Univ, Cranfield MK43 0AL, Beds, England;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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