...
首页> 外文期刊>Agronomy Journal >Deriving comprehensive county-level crop yield and area data for U.S. cropland.
【24h】

Deriving comprehensive county-level crop yield and area data for U.S. cropland.

机译:得出美国农田的县级作物综合产量和面积数据。

获取原文
获取原文并翻译 | 示例

摘要

Ground-based data on crop production in the USA is provided through surveys conducted by the National Agricultural Statistics Service (NASS) and the Census of Agriculture (AgCensus). Statistics from these surveys are widely used in economic analyses, policy design, and for other purposes. However, missing data in the surveys presents limitations for research that requires comprehensive data for spatial analyses. We created comprehensive county-level databases for nine major crops of the USA for a 16-yr period, by filling the gaps in existing data reported by NASS and AgCensus. We used a combination of regression analyses with data reported by NASS and the AgCensus and linear mixed-effect models incorporating county-level environmental, management, and economic variables pertaining to different agroecozones. Predicted yield and crop area were very close to the data reported by NASS, within 10% relative error. The linear mixed-effect model approach gave the best results in filling 84% of the total gaps in yields and 83% of the gaps in crop areas of all the crops. Regression analyses with AgCensus data filled 16% of the gaps in yields and crop areas of the major crops reported by NASS..
机译:美国国家农业统计局(NASS)和农业普查(AgCensus)进行的调查提供了有关美国作物生产的地面数据。这些调查的统计数据广泛用于经济分析,政策设计和其他目的。但是,调查中缺少的数据为需要空间分析的综合数据的研究提供了限制。通过填补NASS和AgCensus报告的现有数据中的空白,我们在16年内为美国的9种主要农作物创建了县级综合数据库。我们将回归分析与NASS和AgCensus报告的数据以及线性混合效应模型结合使用,该模型将县级环境,管理和与不同农业生态区有关的经济变量结合在一起。预测的产量和作物面积非常接近NASS报告的数据,相对误差在10%以内。线性混合效应模型方法在填充所有作物的总产量缺口的84%和作物面积的缺口的83%方面提供了最佳结果。利用AgCensus数据进行的回归分析填补了NASS报告的主要农作物的产量和作物面积缺口的16%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号