本文選題：種植結(jié)構(gòu) + 遙感影像　； 參考：《福建農(nóng)業(yè)學(xué)報(bào)》2017年05期

【摘要】：在面向?qū)ο蠹夹g(shù)支持下,首先利用高空間分辨率ZY-3遙感影像提取農(nóng)田地塊專題信息;然后在地塊邊界控制下以地塊對(duì)象為單元融入HJ-1及GF-1中分傳感器的多時(shí)相光譜信息,獲取作物生長關(guān)鍵期內(nèi)的時(shí)間序列光譜特征;最后,結(jié)合不同作物的物候差異性規(guī)律構(gòu)建作物種植信息提取模型,對(duì)甘蔗和水稻進(jìn)行識(shí)別。結(jié)果表明,所有地類的總體分類精度為86.80%,Kappa系數(shù)為0.84,總體分類效果良好。甘蔗的制圖精度和用戶精度分別達(dá)到92.11%和90.91%,水稻的制圖精度和用戶精度分別達(dá)到88.89%和90.91%。說明協(xié)同利用國產(chǎn)衛(wèi)星的高空間和高時(shí)間分辨率影像數(shù)據(jù)提取作物種植信息確實(shí)可行,可作為作物種植面積和種植結(jié)構(gòu)的精細(xì)化、快速調(diào)查方法。
[Abstract]:With the support of object oriented technology, the special information of farmland block is extracted by high spatial resolution ZY-3 remote sensing image, and then the multi-phase spectral information of sub-sensor in HJ-1 and GF-1 is integrated into the block object unit under the control of block boundary. The spectral characteristics of the time series in the critical period of crop growth were obtained. Finally, combining with the phenological differences of different crops, the information extraction model of crop planting was constructed to identify sugarcane and rice. The results show that the overall classification accuracy of all ground classes is 86.80 and the Kappa coefficient is 0.84, and the overall classification effect is good. The mapping accuracy and user accuracy of sugarcane were 92.11% and 90.91% respectively, and the mapping accuracy and user precision of rice reached 88.89% and 90.91% respectively. The results show that it is feasible to extract crop planting information by using the high spatial and high time resolution image data of domestic satellites, which can be used as a fine and rapid investigation method for crop planting area and structure.
【作者單位】： 廣西農(nóng)業(yè)科學(xué)院農(nóng)業(yè)科技信息研究所;中國科學(xué)院遙感與數(shù)字地球研究所;中國科學(xué)院大學(xué);
【基金】：廣西科學(xué)研究與技術(shù)開發(fā)計(jì)劃項(xiàng)目(桂科合14125008-1-6)
【分類號(hào)】：S127

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