• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Agro-Geoinformatics >Outliers detection of cultivated land quality grade results based on spatial autocorrelation
【24h】

Outliers detection of cultivated land quality grade results based on spatial autocorrelation

机译：基于空间自相关的耕地质量等级结果异常值检测

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Scientific and accurate cultivated quality grade results are an important guarantee for applications. However, the phenomenon of abnormal cultivated land quality is always occurred due to the error of investigation or computation, so exploring effective method to inspect abnormal data of the grade results is an important problem to be solved. Cultivated land quality grade results of Wuhan Hannan district are selected as the research data, and several typical relative indexes of cultivated land quality are researched as spatial variables, including natural index, use index and economic index, etc. Global Moran's I and Local Moran's I index are used to analyze spatial structural characteristic and clustering rules of cultivated land quality, and then put forward cultivated land quality outlier detect standard based on the research of the front. The results showed that: On the whole, natural index, use index and economic index all showed strong positive spatial correlation and the aggregation degree is high; On the local, the cultivated land quality form “high - high” and “low - low” spatial cluster, accompanied with “high - low”, “low - high” space isolation area, which formed a horizontal Mosaic distribution pattern of “patches” and “gaps”. Further study to the “high-low”, “low - high” space isolation zone with significance analysis can effectively detect the cultivated land quality abnormal data. This method improves the traditional statistics due to ignoring the spatial correlation in space anomaly inspection and provides a new train of thought for cultivated land quality data outliers detection.
机译：科学准确的栽培质量等级结果是应用的重要保证。但是，由于调查或计算的误差，经常会出现耕地质量异常的现象，因此寻求一种有效的方法来检验坡度结果的异常数据是一个亟待解决的重要问题。选择武汉市汉南区耕地质量等级结果作为研究数据，并研究了几种典型耕地质量的相对指标作为空间变量，包括自然指标，利用指标和经济指标等。Global Moran's I和Local Moran's I利用该指标对耕地质量空间结构特征和聚类规律进行分析，并在此基础上提出了耕地质量离群检测标准。结果表明：总体上，自然指数，利用指数和经济指数均表现出较强的正相关性，且聚集度较高。在当地，耕地质量形成了“高-高”和“低-低”的空间簇，并伴随着“高-低”，“低-高”的空间隔离区，形成了“斑块”的水平镶嵌分布格局。 ”和“空白”。通过对“高-低”，“低-高”空间隔离带的进一步研究，并进行显着性分析，可以有效地检测出耕地质量异常数据。该方法由于忽略了空间异常检查中的空间相关性，从而改进了传统的统计方法，为耕地质量数据离群值的检测提供了新的思路。

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