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農(nóng)作物種植格局對(duì)遙感分類精度的影響
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國(guó)家自然科學(xué)基金項(xiàng)目(41271419)


Effects of Crop Planting Structure on Remote Sensing Classification Accuracy
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    摘要:

    研究不同作物種植成數(shù)、田塊形狀和田塊破碎度對(duì)作物遙感分類精度的影響,是科學(xué)評(píng)價(jià)作物遙感分類精度的基礎(chǔ)。采用GF—1遙感數(shù)據(jù),以時(shí)序植被指數(shù)的主要農(nóng)作物分類結(jié)果為基礎(chǔ),對(duì)研究區(qū)冬小麥—夏玉米作物種植區(qū)的分類精度與種植成分、田塊形狀和破碎度的關(guān)系進(jìn)行了研究。結(jié)果表明,種植成數(shù)與分類精度呈正相關(guān),田塊破碎度、田塊形狀指數(shù)與分類精度呈負(fù)相關(guān)。

    Abstract:

    The study of effects of different crop acreage proportions, crop field shape index and crop field fragmentation on accuracy of crop classification by remote sensing provides a basis for scientific evaluation of the latter. Using GF—1 remote sensing data and based on the major crop classification results of the timeseries vegetation index, the relationship between classification accuracy of crops (including winter wheat and summer maize) and crop acreage proportion, crop field shape index as well as crop field fragmentation was studied. The research was based on 14 GF—1/WFV NDVI time series data. The timing vegetation indexbased crop classification knowledge rules were utilized on the basis of the best NDVI threshold interval of crops to be classified to complete the crops classification and make spatial distribution map. Then, totally 14 classical villages of Quzhou county were selected as sample plots, which included winter wheat—summer corn plots. The landuse ownership boundary map for the 14 classic villages was obtained according to 1∶50000 Quzhou county present landuse map, which was prepared by Quzhou County Land Resources Bureau and China Agricultural University jointly. The spatial distribution map of winter wheat—summer corn and landuse ownership boundary map among landuse survey maps were used to take image masking, and the lots and sample points of winter wheat—summer corn of each classical village region were obtained. Hence, the crop acreage proportion, crop field shape index and crop field fragmentation of winter wheat—summer corn in 14 villages were obtained, and classification accuracy, Kappa index were calculated. In addition, totally 14 groups of sample plot related data were acquired and graphs of relation between all influencing factors and classification accuracy were prepared. The results showed that the crop acreage proportion was positively correlated to classification accuracy, while the crop field fragmentation and crop field shape index were negatively correlated to classification accuracy.

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張榮群,王盛安,高萬(wàn)林,牛靈安,孫瑋健,溫利興.農(nóng)作物種植格局對(duì)遙感分類精度的影響[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2016,47(10):318-324. Zhang Rongqun, Wang Sheng’an, Gao Wanlin, Niu Ling’an, Sun Weijian, Wen Lixing. Effects of Crop Planting Structure on Remote Sensing Classification Accuracy[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(10):318-324.

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  • 收稿日期:2016-03-18
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  • 在線發(fā)布日期: 2016-10-10
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