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基于面向?qū)ο蠓诸惖募毿『恿魉w提取方法研究
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國家自然科學基金資助項目(41361044、61162025)


Extraction of Small River Information Based on Object-oriented Classification
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    摘要:

    以2010年8月和1986年8月橫山縣TM圖像為基礎數(shù)據(jù)源,獲取精準水域分布信息并進行動態(tài)分析。對2期TM圖像進行預處理;創(chuàng)建特征空間WFS,輔助土地利用現(xiàn)狀圖、地形圖、水系圖等專題圖件進行疊加分析,在WFS中通過全局閾值分割分離出溝谷陰影、植被等背景地物信息,粗提水域分布信息;在此基礎上進行LBV變換,并選取適宜尺度執(zhí)行面向?qū)ο蠓指?,?yōu)化目標對象識別區(qū);執(zhí)行SVM監(jiān)督分類并組合數(shù)學形態(tài)學開、閉運算對初始全域水體信息提取結(jié)果的二值圖像進行分類后處理,精確逼近各類水體的水陸界限;依據(jù)2期全域水體信息提取結(jié)果進行動態(tài)分析。結(jié)果表明,所用方法能完整、快速地提取出研究區(qū)各類型水體的分布信息,準確識別細小河流水體,顯著減少對溝谷陰影等背景地物的誤判,基本消除椒鹽效應;1986年和2010年2期水體提取結(jié)果的制圖精度和用戶精度分別為0.921、0.875和0.913、0.862。

    Abstract:

    A hybrid method for small river-water extraction using TM images, covering Hengshan County in Shaanxi Province and acquired in August 20, 2010 and August 2, 1986, is proposed. After the pretreatment of the original image data, WFS feature space is built. Then, WFS is segmented to remove the influence of background spectral interference by aid of overlay analysis with thematic maps, such as present land use map, topographic map and drainage map. Next, the multispectral images containing the preliminary water distribution information are processed with LBV transformation and object oriented segmentation. Further, the precise extraction of river water can be achieved by using SVM supervised classification and mathematical morphology open close operator. Finally, water dynamic analysis is accomplished by adopting the precise water change information acquired from the above results. Results show that using the method provided can get precise water distribution information in Hengshan County, especially can improve the identification accuracy for small river. The map accuracy of water extraction results in 1986 and 2010 are 0.921 and 0.875, respectively, and the user’s accuracy are 0.913 and 0.862, respectively. The hierarchical extraction method proposed is feasible and reliable for small river-water extraction, can reduce the error of loess hilly and gully region identification, significantly.

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劉 煒,王聰華,趙爾平,杜鶴娟.基于面向?qū)ο蠓诸惖募毿『恿魉w提取方法研究[J].農(nóng)業(yè)機械學報,2014,45(7):237-244. Liu Wei, Wang Conghua, Zhao Erping, Du Hejuan. Extraction of Small River Information Based on Object-oriented Classification[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(7):237-244.

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  • 收稿日期:2014-02-09
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  • 在線發(fā)布日期: 2014-07-10
  • 出版日期: 2014-07-10