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Method and Algorithms of Forecasting the Seasonal Characteristics of Anthropogenic Impact Areas Using Long-Term Remote Sensing Data

机译:长期遥感数据预测人为影响区季节特征的方法和算法

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摘要

A method for predicting the characteristics of areas subject to the anthropogenic impact according to the Earth's remote sensing data is proposed. The developed method is based on the identification of patterns using long-term periodic observations. These patterns are applied to the seasonal observations of the current year. The method is implemented in a set of algorithms and predictive models. An example of the use of the method of the agricultural yield forecasting is given. The training and validation of models for the prediction of crop yields based on the long-term spatial data on the state of vegetation are described. Different regions of the Russian Federation including the Arctic regions are considered.
机译:提出了一种根据地球遥感数据预测人为影响区域特征的方法。所开发的方法基于使用长期定期观察的模式识别。这些模式适用于当年的季节性观测。该方法在一组算法和预测模型中实现。举例说明了农业产量预测方法的使用。描述了基于植被状态的长期空间数据对作物产量预测模型的训练和验证。考虑了俄罗斯联邦的不同地区,包括北极地区。

著录项

  • 来源
  • 作者

    V. Yu. Ignatiev; A. B. Murynin;

  • 作者单位

    Institute for Scientific Research of Aerospace Monitoring Aerocosmos, Moscow, Russia;

    Institute for Scientific Research of Aerospace Monitoring Aerocosmos, Moscow, Russia,Dorodnitsyn Computing Centre, Moscow, Russia;

  • 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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