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中国农学通报 ›› 2015, Vol. 31 ›› Issue (5): 182-188.doi: 10.11924/j.issn.1000-6850.2014-2636

所属专题: 土壤重金属污染 现代农业发展与乡村振兴

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

遥感在农业面源污染中的应用研究

付碧玉1,马友华1,吴 靓1,王雪蕾2,王 强1,张笑宇1,张维维1,殷寒旭1   

  1. (1安徽农业大学资源与环境学院,合肥 230036;2环境保护部卫星环境应用中心,北京 100094)
  • 收稿日期:2014-09-30 修回日期:2014-10-27 接受日期:2014-11-27 出版日期:2015-03-20 发布日期:2015-03-20
  • 通讯作者: 付碧玉
  • 基金资助:
    国家科技支撑计划“南方平原稻作农区农业面源污染防控技术集成与示范”(2012BAD15B03)。

Remote Sensing on Agricultural Non-point Source Pollution Research

Fu Biyu1, Ma Youhua1, Wu Liang1, Wang Xuelei2, Wang Qiang1, Zhang Xiaoyu1, Zhang Weiwei1, Yin Hanxu1   

  1. (1College of Resources and Environment, Anhui Agricultural University, Hefei 230036;2Environmental Protection Department Satellite Environment Application Center, Beijing 100094)
  • Received:2014-09-30 Revised:2014-10-27 Accepted:2014-11-27 Online:2015-03-20 Published:2015-03-20

摘要: 遥感作为农业面源污染的重要研究方法,主要是因为遥感具有尺度大、效率高、可重复性强、经济性好等一系列特有的优点,遥感与传统的研究方法相结合具有实际的应用。介绍了遥感在农业面源污染监测、估算和评价以及预报预测中的研究应用。遥感在农业面源污染监测中的应用主要体现在利用遥感对农业面源污染进行调查、农田水体污染和农田土壤污染进行监测。利用遥感来获取农业面源污染中的水文、土地、地形、气象和农业生产活动5大类重要数据,对水环境进行监测和评价主要是通过水体及其污染物的光谱特性,遥感对农田的地表光谱进行观测,能够了解农田土壤污染的来源、性状和程度。而遥感与模型和GIS结合能够对农业面源污染进行定量估算,也能够对农业面源污染内部的复杂规律进行评价研究,“3S”技术在农业面源污染模型中的集成应用,使得模型和各种管理措施两者能够相结合,用于非点源污染的预测预报,为治理农业面源污染提供了有力的依据。

关键词: 黑龙江, 黑龙江, 农民, 收入影响因素, 多元线性回归模型, 惠农政策

Abstract: The remote sensing has been applied in the research on agricultural non-point source pollution with the unique advantages of large scale, high efficiency, strong repeatability, economical and so on. Remote sensing combined with traditional research method has practical application. This article introduces remote sensing application and research in agricultural non-point source pollution monitoring, estimation, assessment, forecast and prediction. Remote sensing applied in agricultural non-point source pollution monitoring mainly has three aspects, investigating agricultural non-point source pollution, monitoring farmland water pollution and soil pollution. These data such as hydrology, soil, terrain, weather, and agricultural production activity can be obtained by remote sensing. These five kinds of data are very important data of agricultural non-point source pollution. Monitoring and evaluating water environment is on the basis of the spectral characteristics of the water body and its pollution. Measuring surface spectral of farmland by remote sensing can understand the sources, properties and degree of farmland soil pollution. Remote sensing combined with model and GIS can estimate the agricultural non-point source pollution quantificationally and evaluate the complex pattern within agricultural non-point source pollution. By the integrated application of “3S” technology, the models and various management measures can be combined to forecast non-point source pollution and to provide the base for governing agricultural non-point source pollution.