基于SPOT-5衛(wèi)星影像的水稻信息提取方法研究——以德陽(yáng)市旌陽(yáng)區(qū)為例
發(fā)布時(shí)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(yīng)用方面的重要內(nèi)容,也是快速、準(zhǔn)確滿足水稻種植遙感監(jiān)測(cè)的需要!痉椒ā勘狙芯恳运拇ㄊ〉玛(yáng)市旌陽(yáng)區(qū)為研究區(qū),利用SPOT-5衛(wèi)星影像,對(duì)研究區(qū)的影像進(jìn)行監(jiān)督、面向?qū)ο笠约皼Q策樹(shù)等多種方法分類(lèi),對(duì)分類(lèi)結(jié)果進(jìn)行對(duì)比,研究最適合提取水稻信息的方法。【結(jié)果】結(jié)果表明:(1)監(jiān)督分類(lèi)(6種分類(lèi)器)人為控制訓(xùn)練區(qū)提高精度的同時(shí)也加大了人為誤差;面向?qū)ο蠓诸?lèi)提高了效率,易出現(xiàn)分類(lèi)混淆;決策樹(shù)分類(lèi)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(lèi)誤差加大。(2)神經(jīng)網(wǎng)絡(luò)和支持向量機(jī)的分類(lèi)精度最高,分類(lèi)效果清晰,說(shuō)明在實(shí)際水稻信息提取中以監(jiān)督分類(lèi)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(shí)現(xiàn)水稻監(jiān)測(cè)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(xué)地理與資源科學(xué)學(xué)院;四川師范大學(xué)西南土地資源評(píng)價(jià)與監(jiān)測(cè)教育部重點(diǎn)實(shí)驗(yàn)室;四川省農(nóng)業(yè)科學(xué)院遙感應(yīng)用研究所;
【基金】:國(guó)家自然科學(xué)基金項(xiàng)目“基于LUCC擾動(dòng)影響的成都平原土地生態(tài)安全維持機(jī)理”(41371125)
【分類(lèi)號(hào)】:S127;S511
本文編號(hào):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(xué)地理與資源科學(xué)學(xué)院;四川師范大學(xué)西南土地資源評(píng)價(jià)與監(jiān)測(cè)教育部重點(diǎn)實(shí)驗(yàn)室;四川省農(nóng)業(yè)科學(xué)院遙感應(yīng)用研究所;
【基金】:國(guó)家自然科學(xué)基金項(xiàng)目“基于LUCC擾動(dòng)影響的成都平原土地生態(tài)安全維持機(jī)理”(41371125)
【分類(lèi)號(hào)】:S127;S511
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