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(Stru...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。展开更多
multi-resolution TIN model is an important issue in the contexts of visu-alization,virtual reality (VR),and geographic information systems (GIS). This paper proposes a new method for constructing multi-resolution TIN ...multi-resolution TIN model is an important issue in the contexts of visu-alization,virtual reality (VR),and geographic information systems (GIS). This paper proposes a new method for constructing multi-resolution TIN models with multi-scale topographic features preservation. The proposed method is driven by a half-edge collapse operation in a greedy framework and employs a new quadric error metric to efficiently measure geometric errors. We define topographic features in a multi-scale manner using a center-surround operator on Gaussian-weighted mean curvatures. Experimental results demonstrate that the proposed method performs better than previous methods in terms of topographic features preservation,and is able to achieve multi-resolution TIN models with a higher accuracy.展开更多
文摘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。
基金the National Basic Research Program of China ("973") (Grant No. 2006CB705500)the National Natural Science Foundation of China (Grant No. 40571134)+1 种基金the National Hi-Tech Research and Development Program of China (Grant Nos. 2007AA12Z241, 2007AA12Z212)Outstanding Scholar of Ministry of Education of China (Grant No. NCET-07-0643)
文摘multi-resolution TIN model is an important issue in the contexts of visu-alization,virtual reality (VR),and geographic information systems (GIS). This paper proposes a new method for constructing multi-resolution TIN models with multi-scale topographic features preservation. The proposed method is driven by a half-edge collapse operation in a greedy framework and employs a new quadric error metric to efficiently measure geometric errors. We define topographic features in a multi-scale manner using a center-surround operator on Gaussian-weighted mean curvatures. Experimental results demonstrate that the proposed method performs better than previous methods in terms of topographic features preservation,and is able to achieve multi-resolution TIN models with a higher accuracy.
