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杜蒙蒙,李瀚远,金鑫,等.基于无人机遥感图像提取农田微地形特征[J].农业工程,2023,13(2):77-81. DOI: 10.19998/j.cnki.2095-1795.2023.02.013
引用本文: 杜蒙蒙,李瀚远,金鑫,等.基于无人机遥感图像提取农田微地形特征[J].农业工程,2023,13(2):77-81. DOI: 10.19998/j.cnki.2095-1795.2023.02.013
DU Mengmeng,LI Hanyuan,JIN Xin,et al.Extracting micro-topographical features of farmland by using UAV remote sensing image[J].Agricultural Engineering,2023,13(2):77-81. DOI: 10.19998/j.cnki.2095-1795.2023.02.013
Citation: DU Mengmeng,LI Hanyuan,JIN Xin,et al.Extracting micro-topographical features of farmland by using UAV remote sensing image[J].Agricultural Engineering,2023,13(2):77-81. DOI: 10.19998/j.cnki.2095-1795.2023.02.013

基于无人机遥感图像提取农田微地形特征

Extracting Micro-topographical Features of Farmland by Using UAV Remote Sensing Image

  • 摘要: 近年来极端暴雨天气与自然灾害频发,导致农田损毁,影响耕作。该研究利用高精度农田数字地形模型(Farmland Digital Terrain Model,FDTM),基于地形因子综合属性提出一种识别农田微地形特征(凸起特征及洼地特征)的方法。首先,基于SfM(Structure from Motion)技术处理试验田的航拍图像,获取高精度农田FDTM,分析FDTM的高程方差随局部窗口尺度的变化趋势,确定分析窗口的尺度区间为31像素×31像素至51像素×51像素。其次,选择高程、地形起伏度和坡度综合评价在51像素×51像素窗口下提取的315个高程极值点,获取多窗口地形因子综合隶属度。最后,根据斯特吉斯公式确定阈值为0.627,提取16个农田凸起特征顶点,并结合等高线图识别凸起特征的外形轮廓;同理,建立反转数字地形模型(Reverse-FDTM,RFDTM),将FDTM中的洼地特征转变为RFDTM中的凸起特征,识别9个农田洼地特征。研究结果可为农田复垦及精准土地平整作业提供理论依据与方法支持。

     

    Abstract: In recent years, extreme rainstorms and natural disasters have occurred frequently, which causing severe damage to farmland.A method of identifying hump and concave features of farmland using Farmland Digital Terrain Model(FDTM)was proposed.First, aerial image of experimental plot was handle based on SfM(Structure from Motion)technology and high precision farmland FDTM was obtained.Variation trend of elevation variance of FDTM with local window scale was analyzed, and scale interval of analysis window as 31×31 to 51×51 pixels was determined.Second, 315 elevation extremes were extracted under local window of 51×51 pixels, which were further evaluated by using 3 topographical factors of elevation, topographic relief and slope to obtain multi-windows comprehensive membership degrees.Finally, threshold value of multi-windows comprehensive membership degrees was determined as 0.627 according to Sturgis method.16 elevation extremes were confirmed as hump features’ vertices, and outline of hump features were obtained by combining with contour map.Similarly, a Reverse Farm Digital Terrain Model(RFDTM)was developed to transform concave features into hump features, and 9 farmland concave features were identified.Research results could provide theoretical basis and methodological support for farmland reclamation and precise land leveling operations.

     

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