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Economics of wheat yield variability for Oklahoma farmers using satellite images.

机译:使用卫星图像的俄克拉荷马州农民的小麦单产变异性经济学。

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摘要

Scope and method of study. The variability in wheat yields over time and space is substantial. Satellite imagery provides an opportunity to study the spatial and temporal yield variability on the farmers' fields at low cost. Multi-year satellite images for three selected fields are obtained to study temporal and spatial variability, using the NDVI index. Farmers provided detailed information on inputs and analysis of 0.1544-acre pixels reveals substantial temporal and spatial variability. Budgeting is used to compare site-specific and uniform applications of nitrogen.; Finds and conclusions. Fields with highly variable yields resulting from soil variations and manageable inputs will gain the most from this technology. Such soils can perhaps be more efficiently managed through spatially variable technologies. An approach that would benefit some producers is to identify patterns of yield consistency and inconsistency in different parts of each field. Costs of site-specific management can be reduced if those distinctly behaving parts of the field are relatively large in size. Smaller and numerous micro-units may make precision farming economically infeasible, especially in case of a crop like wheat. There are some important issues that need to be addressed to make the satellite-generated information more beneficial for wheat producers. The time that the satellite images are taken is very important. Farmers tend to tailor their farm management practices based on the information that becomes available during the course of crop production. The study of satellite images for a given field for a number of years can make the farmer more aware of problem areas within their fields. Farmers could decide to change tillage or other input practices to increase yields in certain areas. Availability of climatic information, like rainfall, for different micro-units could be important in analyzing spatial and temporal variability. However, obtaining that information could be costly, and while it might help explain yield variability, producers would likely still find it difficult to manage weather-related variability.
机译:研究范围和方法。小麦产量随时间和空间的变化很大。卫星图像提供了一个机会,以低成本研究农民田间的时空产量变异性。使用NDVI指数,获得了三个选定领域的多年卫星图像,以研究时间和空间变异性。农民提供了有关输入的详细信息,对0.1544英亩像素的分析显示出巨大的时空变异性。预算用于比较特定地点和统一施用的氮。 发现和结论。由于土壤变化和可管理的投入而导致产量极高变化的田地将从这项技术中获得最大收益。可以通过空间可变技术更有效地管理此类土壤。对某些生产者有利的一种方法是在每个字段的不同部分确定产量一致性和不一致的模式。如果现场表现各异的部分规模较大,则可以减少特定于站点的管理成本。较小的微型单位可能使精耕细作在经济上不可行,尤其是在像小麦这样的农作物的情况下。为了使卫星产生的信息对小麦生产者更加有益,需要解决一些重要问题。拍摄卫星图像的时间非常重要。农民倾向于根据作物生产过程中可获得的信息来调整其农场管理实践。对给定田地的卫星图像进行多年研究可以使农民更加了解其田地内的问题区域。农民可以决定改变耕作或其他投入方式,以增加某些地区的单产。对于不同的微单位,诸如降雨之类的气候信息的可获得性在分析空间和时间变化方面可能很重要。但是,获得这些信息可能会花费很大,尽管它可能有助于解释产量变化,但生产者可能仍会发现难以管理与天气相关的变化。

著录项

  • 作者

    Asim, Mohammad.;

  • 作者单位

    Oklahoma State University.;

  • 授予单位 Oklahoma State University.;
  • 学科 Economics Agricultural.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 2000
  • 页码 94 p.
  • 总页数 94
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业经济;遥感技术;
  • 关键词

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