基于SPOT-5衛(wèi)星影像的水稻信息提取方法研究——以德陽市旌陽區(qū)為例
發(fā)布時間：2018-10-08 07:41
【摘要】：【目的】水稻遙感信息提取是遙感技術(shù)在農(nóng)業(yè)領(lǐng)域應用方面的重要內(nèi)容,也是快速、準確滿足水稻種植遙感監(jiān)測的需要�！痉椒ā勘狙芯恳运拇ㄊ〉玛柺徐宏枀^(qū)為研究區(qū),利用SPOT-5衛(wèi)星影像,對研究區(qū)的影像進行監(jiān)督、面向?qū)ο笠约皼Q策樹等多種方法分類,對分類結(jié)果進行對比,研究最適合提取水稻信息的方法�！窘Y(jié)果】結(jié)果表明:(1)監(jiān)督分類(6種分類器)人為控制訓練區(qū)提高精度的同時也加大了人為誤差;面向?qū)ο蠓诸愄岣吡诵?易出現(xiàn)分類混淆;決策樹分類法直觀、效率高,但在本研究區(qū)中,由于耕林混交的面積較大,水體和居民地亮度值接近,造成分類誤差加大。(2)神經(jīng)網(wǎng)絡和支持向量機的分類精度最高,分類效果清晰,說明在實際水稻信息提取中以監(jiān)督分類為最佳�！窘Y(jié)論】基于遙感技術(shù)和高分辨率數(shù)據(jù)提取水稻信息、實現(xiàn)水稻監(jiān)測是可行的。
[Abstract]:[objective] Rice remote sensing information extraction is an important content in the application of remote sensing technology in the agricultural field, and it is also rapid and accurate to meet the needs of remote sensing monitoring of rice cultivation. [methods] in this study, Jingyang District, Deyang City, Sichuan Province, was taken as the research area. The SPOT-5 satellite image is used to monitor the image of the research area, object oriented and decision tree are used to classify the image, and the classification results are compared. The results show that: (1) the artificial control training area of supervised classification (6 classifiers) improves the accuracy and increases the artificial error, and the object-oriented classification improves the efficiency and is liable to be confused; Decision tree classification method is intuitionistic and efficient, but in this study area, the brightness value of water body and residents is close, which results in the higher classification error. (2) the classification accuracy of neural network and support vector machine is the highest. The classification effect is clear, which shows that the best way to extract rice information is supervised classification. [conclusion] it is feasible to extract rice information based on remote sensing technology and high-resolution data.
【作者單位】： 四川師范大學地理與資源科學學院;四川師范大學西南土地資源評價與監(jiān)測教育部重點實驗室;四川省農(nóng)業(yè)科學院遙感應用研究所;
【基金】：國家自然科學基金項目“基于LUCC擾動影響的成都平原土地生態(tài)安全維持機理”(41371125)
【分類號】：S127;S511
本文編號：2255967
[Abstract]:[objective] Rice remote sensing information extraction is an important content in the application of remote sensing technology in the agricultural field, and it is also rapid and accurate to meet the needs of remote sensing monitoring of rice cultivation. [methods] in this study, Jingyang District, Deyang City, Sichuan Province, was taken as the research area. The SPOT-5 satellite image is used to monitor the image of the research area, object oriented and decision tree are used to classify the image, and the classification results are compared. The results show that: (1) the artificial control training area of supervised classification (6 classifiers) improves the accuracy and increases the artificial error, and the object-oriented classification improves the efficiency and is liable to be confused; Decision tree classification method is intuitionistic and efficient, but in this study area, the brightness value of water body and residents is close, which results in the higher classification error. (2) the classification accuracy of neural network and support vector machine is the highest. The classification effect is clear, which shows that the best way to extract rice information is supervised classification. [conclusion] it is feasible to extract rice information based on remote sensing technology and high-resolution data.
【作者單位】： 四川師范大學地理與資源科學學院;四川師范大學西南土地資源評價與監(jiān)測教育部重點實驗室;四川省農(nóng)業(yè)科學院遙感應用研究所;
【基金】：國家自然科學基金項目“基于LUCC擾動影響的成都平原土地生態(tài)安全維持機理”(41371125)
【分類號】：S127;S511
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1 錢永蘭,楊邦杰,雷廷武;用基于IHS變換的SPOT-5遙感圖像融合進行作物識別[J];農(nóng)業(yè)工程學報;2005年01期
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