本文關(guān)鍵詞： 遙感 作物 算法 最大墑模型 葉面積指數(shù) 升尺度 尺度效應(yīng) 環(huán)境變量　出處：《農(nóng)業(yè)工程學(xué)報》2016年07期 　論文類型：期刊論文

【摘要】：葉面積指數(shù)(leaf area index,LAI)是表達農(nóng)作物冠層結(jié)構(gòu)的關(guān)鍵參數(shù)之一,準(zhǔn)確獲取LAI對于農(nóng)作物長勢監(jiān)測、估產(chǎn)等研究具有非常重要的意義。由于地物空間復(fù)雜性、數(shù)據(jù)源的不同以及遙感反演模型的非線性,LAI的反演結(jié)果會存在尺度效應(yīng),因此需要進行尺度轉(zhuǎn)換研究。理想的升尺度轉(zhuǎn)換應(yīng)該只是數(shù)據(jù)空間分辨率的降低,而數(shù)據(jù)內(nèi)在信息應(yīng)保存到低分辨率中。最大熵(maximum entropy,Max Ent)模型是基于多種環(huán)境因子的廣義學(xué)習(xí)模型,對分析因子的空間分布具有較高的估算精度,因此,該研究利用最大熵模型進行玉米冠層LAI升尺度方法研究,從而將野外實測的LAI點數(shù)據(jù)擴展到空間分辨率為30 m的面數(shù)據(jù),所使用的數(shù)據(jù)源是Landsat8 OLI遙感影像、氣象數(shù)據(jù)和野外樣點上測量的LAI數(shù)據(jù)。研究結(jié)果表明:利用最大熵模型升尺度轉(zhuǎn)換結(jié)果與實測LAI相比,R2為0.601、RMSE為0.898,說明兩者的相關(guān)性較高;由于玉米冠層葉片之間的相互遮擋,導(dǎo)致整體結(jié)果偏低,但偏低誤差在可接受范圍內(nèi)。因此,Max Ent模型可用于農(nóng)作物L(fēng)AI點數(shù)據(jù)到面數(shù)據(jù)的升尺度轉(zhuǎn)換。
[Abstract]:Leaf area index (Lai) is one of the key parameters to express the canopy structure of crops. The accurate acquisition of LAI is very important for the study of crop growth monitoring and yield estimation. The different data sources and the nonlinear inversion results of remote sensing inversion model will have scale effect, so scale conversion should be studied. The ideal scaling conversion should only reduce the spatial resolution of data. The maximum entropy maximum entropyMax Ent model is a generalized learning model based on a variety of environmental factors, which has a high estimation accuracy for the spatial distribution of analysis factors. In this study, the maximum entropy model was used to study the LAI scaling method of maize canopy, and the field measured LAI data was extended to the surface data with spatial resolution of 30 m. The data source was Landsat8 OLI remote sensing image. Meteorological data and LAI data measured on field samples. The results show that compared with the measured LAI, the RMSE of the maximum entropy model is 0.601g, which indicates that the correlation between them is relatively high, because of the mutual occlusion between maize canopy leaves, As a result, the overall result is low, but the error is within acceptable range. Therefore, Max Ent model can be used to transform crop LAI point data to surface data.
【作者單位】： 中國農(nóng)業(yè)大學(xué)信息與電氣工程學(xué)院;黑龍江省農(nóng)墾科學(xué)院科技情報研究所;
【基金】：國家自然基金項目(41371327)
【分類號】：S513;S127
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本文編號：1539348