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基于無人機遙感技術的玉米種植信息提取方法研究
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國家國際科技合作項目(2014DFG72150)和楊凌示范區(qū)工業(yè)項目(2015GY—03)


Extraction Method of Maize Planting Information Based on UAV Remote Sensing Techonology
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    摘要:

    使用無人機遙感試驗獲取的可見光圖像研究拔節(jié)期玉米種植信息提取方法。首先確定感興趣區(qū)地物種類,包括:玉米、小麥、向日葵、樹苗和裸地;然后分別統(tǒng)計計算5類地物的27項紋理特征,比較各類地物特征的種內(nèi)變異系數(shù)和與玉米的相對差異系數(shù),選出適宜提取玉米種植信息的特征。經(jīng)過分析發(fā)現(xiàn),僅用一個特征參數(shù)難以準確提取玉米種植信息,需要各特征組合分層分類提取玉米信息。最后確定綠色均值、藍色協(xié)同性和紋理低通植被指數(shù)TLVI為玉米種植信息提取特征。經(jīng)過對初步提取結果的分析,發(fā)現(xiàn)分類后的小麥地和樹苗地中仍殘留有與玉米區(qū)特征相同的斑塊,玉米地中有與非玉米區(qū)特征相同的斑塊,結合兩種斑塊各自形狀面積分布的獨特性,分別實現(xiàn)殘留斑塊去除和玉米地錯分斑塊保留,完成玉米種植信息提取。選取與感興趣區(qū)影像同時期不同區(qū)域的兩幅影像進行方法驗證,結果表明:該方法對玉米種植信息提取有較好效果,面積提取誤差在20%以內(nèi),對用無人機可見光遙感影像進行玉米種植信息提取具有一定的適用性。

    Abstract:

    A method of information extraction for maize at jointing stage was described by using the high-resolution visible images, which were obtained by the unmanned aerial vehicle (UAV) remote sensing system. The 27 texture features of five ground objects were calculated separately, including maize, wheat, sunflower, sapling and bare land in the region of interest obtained by using co-occurrence measures and convolutions low pass. Comparing the variation coefficient of five ground objects and the relative difference with maize, the mean of green, homogeneity of blue and texture low pass vegetation index (TLVI) were chosen as the feature to obtain planting information of maize. In order to distinguish the maize land and sapling land, the TLVI was built by using scatter diagram in which the X axis was the lowpass red band and the Y axis was the low-pass blue band of maize land and sapling land. In the preliminary result, it was found that there were patches which had the same feature with maize land in wheat land and sapling land and patches of other kinds in the maize land. By analyzing the uniqueness of shape and area of two kinds of patches, the other patches were removed and the patches of maize land were retained. In order to verify the applicability and the reliability of the method, two different images which were in the same period with the region of interest were chosen to process by using the same method. The results indicated that the method could extract planting information of maize through using the high-resolution visible images obtained by the UAV remote sensing system and the area extraction error was less than 20%.

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韓文霆,李廣,苑夢嬋,張立元,師志強.基于無人機遙感技術的玉米種植信息提取方法研究[J].農(nóng)業(yè)機械學報,2017,48(1):139-147. HAN Wenting, LI Guang, YUAN Mengchan, ZHANG Liyuan, SHI Zhiqiang. Extraction Method of Maize Planting Information Based on UAV Remote Sensing Techonology[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(1):139-147.

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  • 收稿日期:2016-04-24
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  • 在線發(fā)布日期: 2017-01-10
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