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兼顧面積屬性與不確定性信息的樣本點權重調整方法
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自然資源部國土衛(wèi)星遙感應用重點實驗室開放基金項目(KLSMNR-G202219)和國家重點研發(fā)計劃項目(2021YFD1500203)


Weight Adjustment Method of Sampling Sites Integrating Area Attribute and Uncertainty Information
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    摘要:

    樣本點權重調整是遙感分類精度評價中樣本點空間分配的關鍵環(huán)節(jié)。以北京市順義區(qū)精度評價樣本點為例,提出了一種兼顧面積屬性與不確定性信息的樣本點權重調整方法——模糊調整權重法,用于布設精度評價樣本點。首先,構建用于表達不確定性信息的模糊中和指數及其權重,融合模糊中和指數權重和面積權重構建模糊調整權重,并計算各個分層的模糊調整權重結果,完成樣本點特征空間分配;其次,設置不同梯度樣本點集,結合平均最短距離最小化準則和空間模擬退火算法實現樣本點地理空間優(yōu)化布設;最后,構建權重調整效果評價指標,進行模糊調整權重效果評價,并與其他權重調整方法和未進行權重調整的布點方法進行對比分析。結果表明:順義區(qū)不確定性大、中、小的層模糊調整權重分別為0.45、0.37、0.18,與面積權重相比,不確定性大的層權重顯著增加、中層權重稍微增加、小層權重明顯降低;5個不同數據集樣本點權重調整的精度評價總體精度、相對精度、均方根誤差和標準偏差結果分別為69.90%~73.48%、96.28%~99.82%、0.01和0.01;模糊調整權重布點方法評價效果優(yōu)于面積權重、模糊中和指數權重、不確定性空間分層權重布點方法,以及空間均勻抽樣和簡單隨機抽樣方法,樣本點權重調整更加準確可靠。設計的模糊調整權重法布設精度評價樣本點,能夠兼顧面積屬性和不確定性信息,又可以避免權重調整過度,提高了各個分層樣本點空間分配的合理性。

    Abstract:

    Weight adjustment of sampling sites is a key aspect for spatial allocation of samples in the accuracy evaluation of remote sensing classification. Taking accuracy evaluation of sampling sites in Shunyi District of Beijing as an example, a weight adjustment method of sampling sites integrating area attribute and uncertainty information was proposed and named fuzzy adjustment weight method, which was used for sampling sites layout of accuracy assessment. Firstly, the fuzzy neutral index and its weight were constructed to stand for uncertainty information, and the fuzzy adjustment weight was constructed by fusing the fuzzy neutral index weight and area weight, and the fuzzy adjustment weight results of each stratum were calculated to achieve spatial allocation of samples in the feature space. Secondly, different gradient sample sets were drawn, and spatial-simulated annealing and the minimization of the mean of the shortest distances criterion were used to optimize sampling sites in geographical space. Finally, the indexes of weight adjustment evaluation were constructed to assess the effect of fuzzy adjustment weights. The comparative analysis was achieved between fuzzy adjustment weight and the other weight adjustment methods and the methods without weight adjustment. The results showed that the fuzzy adjustment weights of large, medium and small uncertainty strata in Shunyi District were 0.45, 0.37 and 0.18, respectively. Compared with the area weights of each stratum, the weights of large and medium uncertainty strata were increased significantly and slightly, respectively, and the weight of small uncertainty stratum was decreased significantly. The overall accuracy, relative accuracy, root mean square error and standard deviation of the accuracy evaluation results for weight adjustment of five different sample sets were 69.90%~73.48%, 96.28%~99.82%, 0.01 and 0.01, respectively. The evaluated effect of fuzzy weight adjustment method was better than the methods with area weight, fuzzy neutral index weight, uncertainty stratification weight, and the spatial even sampling and simple random sampling methods. The weight adjustment of sampling sites for the developed method was more accurate and reliable. The developed fuzzy adjustment weight method used for sampling sites layout of accuracy assessment can integrate the area attribute and uncertainty information, and avoid excessive weight adjustment, which was used to improve the rationality for spatial allocation of sampling sites in each stratum.

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李安娜,馬慶偉,董士偉,周鵬娜,李西燦,劉玉.兼顧面積屬性與不確定性信息的樣本點權重調整方法[J].農業(yè)機械學報,2023,54(5):219-226. LI Anna, MA Qingwei, DONG Shiwei, ZHOU Pengna, LI Xican, LIU Yu. Weight Adjustment Method of Sampling Sites Integrating Area Attribute and Uncertainty Information[J]. Transactions of the Chinese Society for Agricultural Machinery,2023,54(5):219-226.

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  • 收稿日期:2023-02-01
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  • 在線發(fā)布日期: 2023-05-10
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