排序方式： 共有34条查询结果，搜索用时 46 毫秒
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Comment on ‘Positional accuracy of the Google Earth terrain model derived from stratigraphic unconformities in the Big Bend region, Texas, USA’ by S.C. Benker, R.P. Langford and T.L. Pavlis (Geocarto Int. 26:291–303, doi: 10.1080/10106049.2011.568125). 相似文献
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Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R2 for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected. 相似文献
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利用LAPS系统,分别针对华中、华南两个区域,将2008—2010年5—7月采集的观测资料进行融合同化分析,设计几种敏感性试验方案,以探空资料为客观标准,对比分析各种观测资料对LAPS分析场各要素误差的作用。将LAPS分析资料和FNL再分析资料做比较,给出融合多种观测资料后LAPS分析场的误差精度。结果表明,LAPS融合同化雷达资料、探空资料、地面观测资料后所得到的分析场误差最小;雷达资料和探空资料的融合对于改善风场及温度场的分析具有正效果,并可减小低层相对湿度误差;融合地面资料后能改善低层的温度场和湿度场分析,但对中高层无影响。对比试验期间各要素总均方根误差可发现,LAPS分析的温度、风向和风速较FNL再分析资料有明显改善,各要素误差在观测误差范围内;高度误差在中低层小于10 m,高层小于20 m;温度误差在1℃左右;相对湿度误差在中低层小于20%,高层误差较大;850hPa以上风向误差较小,不超过20°,风速误差小于2m·s-1。 相似文献
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数字高程模型DEM精度研究 总被引：2，自引：0，他引：2
用不同地貌类型地区的实验数据对数字高程模型(规则格网DEM)的格网间距与中误差(RMSE)、平均高程、剖面曲率的关系进行研究,采用比较分析的方法,得到格网间距与中误差的数学模型,可以用通式:Y=A BX CX2表示,并且把地形因子(平均高程、剖面曲率)作为自变量,进一步分析通式中3个系数与地形因子的关系,发现两个地形因子与系数函数关系比较相似,并得到Y=A BX CX2 DX3的数学模型。由验证结果表明,所得模型效果良好。 相似文献
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混合像元的存在是传统像元级遥感分类和面积量测精度难以达到实用要求的主要原因,为了提高遥感应用精度,须解决混合像元分解问题。传统的方法主要通过改进分解模型提高分解精度,该文在不改变线性分解模型的条件下,分析不同分辨率尺度对于线性分解精度的影响。实验中运用像元合并的方法,得到不同分辨率的TM系列遥感图像,分别选取植被、裸地、水体3种典型地物进行线性分解;以分辨率更高的Quickbird图像分类结果作为真值进行精度评价。实验结果表明:随着图像分辨率的降低,植被的RMSE值不断缩小,在30 m分辨率尺度上均值为0.36,在150 m尺度上均值为0.17,分解精度提高了1倍左右;但随着分辨率进一步降低,由于混合像元现象加剧,RMSE值上升,分解精度随之降低。 相似文献
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在机器视觉和图像处理领域中,图像去噪是一个极其重要的问题,但在消除噪声的同时也丢失了图像中的纹理边缘信息。针对这一缺点,分析了图像去噪的难点,以UINTA(unsupervised,information-theoretic,adaptive filtering)方法为基础,对其作了改进,以信号能量为准则,分别从时域和频域的角度提出了一种纹理特征检测算子,利用该算子对滤除的残余图像重新识别,提取出被误判的纹理细节信息,然后把它补偿到滤波后的图像中,获得最终的去噪图像。实验结果表明,该方法在保留图像纹理特征的同时,有效地去除了图像中的噪声信息,提高了图像的信噪比,降低了均方误差,显著改善了图像的视觉效果,具有很强的实用性。 相似文献
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针对局部重力异常向上延拓计算复杂、耗时长的问题,该文基于泊松积分离散化的基本原理,提出一种快速的局部格网重力异常向上延拓的实用算法;并结合中国东北和青藏高原地区大地水准面的重力异常格网数据,采用该延拓方法分别计算了空中10、50、100km处的重力异常,将其与等高度的EIGEN-6C4模型结果对比分析。实验结果表明:在顾及边界效应影响的情况下,相对于EIGEN-6C4模型,中国东北和青藏高原地区重力异常向上延拓的最大均方根误差分别优于1.5和3.5mGal;在保证精度可用的前提下,计算效率可以有大幅度提高,证明了该方法解算局部重力异常向上延拓的适用性。 相似文献
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Optical remote sensing satellites obtain MS and Pan images simultaneously over the same coverage area. Remote sensing and image processing communities are working on different pan-sharpening methods capable of taking advantage of MS and Pan images. Each remote sensing system has its own advantages and disadvantages, leading to the question ‘Which pan-sharpening method should be used for which type of imagery?’ The aim of this research is to investigate the pan-sharpening performance of PLÉIADES-1A images. For this purpose, pan-sharpened images were generated using PCA, IHS and Brovey Transform which are the most popular pan-sharpening methods. Then, the pan-sharpened images were evaluated quantitatively using Correlation Coefficient, Root Mean Square Error, Relative Average Spectral Error, Spectral Angle Mapper and Erreur Relative Globale Adimensionnelle de Synthése. In addition, pan-sharpened images were evaluated qualitatively by taking object availability and completeness into consideration. 相似文献