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951.
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根据两空间的不同特性和两空间模糊度之间的匹配关系 ,提出了双空间搜索算法 ,使两空间的模糊度候选值明显减少 ,因此可以加快模糊度的搜索速度 ,并用车载试验数据验证了方法的正确性。车载“动对动”定位结果与常规RTK结果比较 ,精度达到mm级 相似文献
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Megan L. Blatchford Chris M. Mannaerts Sammy M. Njuki Hamideh Nouri Yijian Zeng Henk Pelgrum Steven Wonink Poolad Karimi 《水文研究》2020,34(15):3200-3221
The Food and Agricultural Organization of the United Nations (FAO) portal to monitor water productivity through open-access of remotely sensed derived data (WaPOR) offers continuous actual evapotranspiration and interception (ETIa-WPR) data at a 10-day basis across Africa and the Middle East from 2009 onwards at three spatial resolutions. The continental level (250 m) covers Africa and the Middle East (L1). The national level (100 m) covers 21 countries and 4 river basins (L2). The third level (30 m) covers eight irrigation areas (L3). To quantify the uncertainty of WaPOR version 2 (V2.0) ETIa-WPR in Africa, we used a number of validation methods. We checked the physical consistency against water availability and the long-term water balance and then verify the continental spatial and temporal trends for the major climates in Africa. We directly validated ETIa-WPR against in situ data of 14 eddy covariance stations (EC). Finally, we checked the level consistency between the different spatial resolutions. Our findings indicate that ETIa-WPR is performing well, but with some noticeable overestimation. The ETIa-WPR is showing expected spatial and temporal consistency with respect to climate classes. ETIa-WPR shows mixed results at point scale as compared to EC flux towers with an overall correlation of 0.71, and a root mean square error of 1.2 mm/day. The level consistency is very high between L1 and L2. However, the consistency between L1 and L3 varies significantly between irrigation areas. In rainfed areas, the ETIa-WPR is overestimating at low ETIa-WPR and underestimating when ETIa is high. In irrigated areas, ETIa-WPR values appear to be consistently overestimating ETa. The relative soil moisture content (SMC), the input of quality layers and local advection effects were some of the identified causes. The quality assessment of ETIa-WPR product is enhanced by combining multiple evaluation methods. Based on the results, the ETIa-WPR dataset is of enough quality to contribute to the understanding and monitoring of local and continental water processes and water management. 相似文献
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Previous studies comparing sediment fingerprinting un-mixing models report large differences in their accuracy. The representation of tracer concentrations in source groups is perhaps the largest difference between published studies. However, the importance of decisions concerning the representation of tracer distributions has not been explored explicitly. Accordingly, potential sediment sources in four contrasting catchments were intensively sampled. Virtual sample mixtures were formed using between 10 and 100% of the retrieved samples to simulate sediment mobilization and delivery from subsections of each catchment. Source apportionment used models with a transformed multivariate normal distribution, normal distribution, 25th–75th percentile distribution and a distribution replicating the retrieved source samples. The accuracy and precision of model results were quantified and the reasons for differences were investigated. The 25th–75th percentile distribution produced the lowest mean inaccuracy (8.8%) and imprecision (8.5%), with the Sample Based distribution being next best (11.5%; 9.3%). The transformed multivariate (16.9%; 17.3%) and untransformed normal distributions (16.3%; 20.8%) performed poorly. When only a small proportion of the source samples formed the virtual mixtures, accuracy decreased with the 25th–75th percentile and Sample Based distributions so that when <20% of source samples were used, the actual mixture composition infrequently fell outside of the range of uncertainty shown in un-mixing model outputs. Poor performance was due to combined random Monte Carlo numbers generated for all tracers not being viable for the retrieved source samples. Trialling the use of a 25th–75th percentile distribution alongside alternatives may result in significant improvements in both accuracy and precision of fingerprinting estimates, evaluated using virtual mixtures. Caution should be exercised when using a normal type distribution, without exploration of alternatives, as un-mixing model performance may be unacceptably poor. 相似文献
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无人机以机动灵活、作业周期短和成本低等优势被广泛应用于基础测绘等领域。然而无人机航摄系统采集像片通过传统方法需要密集分布控制点,导致作业成本增加及生产效率下降影响经济效益。为此,在考虑到航测相机曝光延迟的基础上提出基于GPS辅助空中三角测量的稀无地面控制点的无人机遥感影像高精度几何定位方法,并通过实际测试生产数字线划图(DLG)和数字正射影像图(DOM),可满足1∶1000地形图测绘的技术要求,其高效率、低成本的生产模式较常规方法更具有推广意义,尤其是在西部测图以及岛礁测量人烟稀少人员很难或无法到达且使用常规测量方法无法满足成图要求的区域。 相似文献
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刘忠豹 《大地测量与地球动力学》2019,39(5):528-532
提出自适应粒子群神经网络(ADPPSO-BP)算法,并加入自适应变异算子,提高粒子跳出局部搜索的能力,实现对坝体位移的精准预测。以丰满大坝为例进行验证,建立PSO-BP(粒子群神经网络)、LPSO-BP(线性粒子群神经网络)、改进ADPPSO-BP(改进自适应粒子群神经网络)3种模型,对大坝进行变形预测。结果表明,ADPPSO-BP预测误差最小。 相似文献
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多频率InSAR提取沼泽湿地DEM精度对比分析 总被引:1,自引:1,他引:0
选取3种波长的干涉SAR数据对提取沼泽湿地区域的DEM,并随机从1:10 000地形图中选取111个点数据进行精度验证,最后对比分析了沼泽湿地植被对于不同SAR波长的干涉相干性差异。结果表明:L-band ALOS-1 PALSAR精细模式的HH单视复数数据与1:10 000地形图数据吻合度较好,76.58%的高程值差异在3 m以内,其相干系数比C-band Sentinel-1A IW模式的VV单视复数数据和X-band TerraSAR HH单视复数数据要高;更适合利用雷达干涉测量技术提取沼泽湿地的DEM;不同湿地植被类型的相干系数有较大差异,岛状林和灌草结合的湿地植被分布区相干系数值较大,而浅水沼泽植被区和深水沼泽植被区相对较低。 相似文献