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东亚飞蝗生境的遥感分类——以河北省黄骅地区为例
  • ISSN号:1000-0585
  • 期刊名称:《地理研究》
  • 时间:0
  • 分类:TP75[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置] S433.2[农业科学—农业昆虫与害虫防治;农业科学—植物保护]
  • 作者机构:[1]南京师范大学地理科学学院,南京210097, [2]中国科学院南京土壤研究所,南京210008
  • 相关基金:国家自然科学基金资助项目(遥感与GIS支持的东亚飞蝗发生机理与预测模型研究,40371081)
中文摘要:

东亚飞蝗生境的分类研究是东亚飞蝗监测和防治的一项重要基础工作。本文以河北省黄骅地区为研究区,基于两个时相的TM图像,采用三种遥感波段组合方案,以及最大似然分类和基于知识的分层分类两种分类方法,进行了东亚飞蝗生境的分类研究。结果表明,三种组合方案的分类总精度相差不大,其中加入图像纹理信息的最大似然分类法的分类总精度最高。但是,基于知识的分层分类法的分类精度在各单项生境类型之问相差较小,从而显示出该方法在应用上仍有一定的优越性。

英文摘要:

The classification of breeding area for oriental migratory locust (Locust migratoria rnanilensis Meyen) is one of the most important tasks in terms of the monitoring and controlling of the damages induced by the locusts. In this study, the Huanghua region along the Bohai Bay in Hebei Province was selected as the study area and the locust breeding areas were classified based on the Landsat-5 TM images dated on August 14, 2003 (TM Ⅰ ) and May 28, 2004(TM Ⅱ ) respectively. Three different schemes of image band combination and two kinds of classifiers were used in the breeding area classification, i. e. the maximum likelihood classifier and the knowledge-based layered classifier. In more detail, they are 1) the combination of bands 3,4 and 5 of TM Ⅰ plus bands 3,4 and 5 of TM Ⅱ with the maximum likelihood classifier; 2)the combination of bands 3,4 and 5 of TM Ⅰ plus bands 3,4 and 5 of TM Ⅱ and the homogeneity index derived from the image of NDVI TMⅠ as a band which contains the spatial texture information of the images, with also the maximum likelihood classifier; and 3)the combination of bands 3,4 and 5 of TM Ⅰ plus bands 3,4 and 5 of TMⅡ and the NDVITMⅠ as a band, with the knowledge-based layered classifier. The results show that, firstly, there is no obvious difference among these different combination schemes in terms of the overall accuracy of the locust breeding area. Relatively speaking, the overall accuracy of the second combination scheme (89. 319) is somewhat higher than those of the other two combination schemes, which indicates that it is beneficial to accuracy improvement of locust breeding area classification if adding the spatial texture information of the images into the classification. Secondly, although the overall accuracy of locust breeding area classification with the third combination scheme is somewhat lower than those of the other two combination schemes, its variation range of locust breeding area classification accuracy among all individual locust br

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期刊信息
  • 《地理研究》
  • 北大核心期刊(2011版)
  • 主管单位:中国科学院
  • 主办单位:中国科学院地理科学与资源研究所
  • 主编:刘毅
  • 地址:北京安外大屯路甲11号
  • 邮编:100101
  • 邮箱:dlyj@igsnrr.ac.cn
  • 电话:010-64889584
  • 国际标准刊号:ISSN:1000-0585
  • 国内统一刊号:ISSN:11-1848/P
  • 邮发代号:2-110
  • 获奖情况:
  • 中国地理优秀期刊
  • 国内外数据库收录:
  • 日本日本科学技术振兴机构数据库,中国中国人文社科核心期刊,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:45649