Comparisons of several evaporation/precipitation datasets for the Bohai Sea based on salinity simulation

Evaporation (E) rate and precipitation (P) rate are two significant meteorological elements required in the ocean baroclinic modeling as external forcings. However, there are some uncertainties in the currently used E/P rates datasets, especially in terms of the data quality. In this study, we collected E/P rates data from ERA-40, NCEP/NCAR Reanalysis, HOAPS for the Bohai Sea and nine routine stations around Laizhou Bay, and made comparisons among them. It was found that the differences in E/P rates between land and sea are remarkable, which was due to the difference in underlying surfaces. Therefore, the traditional way of using E/P rates acquired on land directly at sea is not correct. Since no final conclusion has been reached concerning the net water transport between the Bohai Sea and the Yellow Sea, it is unfeasible to judge the adequacy of the four kinds of data by using the water budget equation. However, the E/P rates at ERA-40 sea points were considered to be the optimal in terms of temporal/spatial coverage and resolution for the hindcast of salinity variation in the Bohai Sea. Besides, using the 3-D hydrodynamic model HAMSOM (HAMburg Shelf Ocean Model), we performed numerical experiments with different E/P datasets and found that the E/P rates at sea points from ERA-40 dataset are better than those from NCEP/NCAR Reanalysis dataset. If NCEP/NCAR Reanalysis E/P rates are to be used, they need to be adjusted and tested prior to simulation so that more close-to-reality salinity values can be reproduced.     

桃源土地二调的超前思维

(编者按]桃源县位于湖南省西北部,东西直线距离75公里,南北直线距离118公里,土地面积4447平方公里,居全省第四,耕地面积141万亩,居全省第一,全县辖40个乡镇、878个村(居)委会.在全省第二次土地调查实施方案中,桃源县被列为全市唯一的第二批土地调查单位.     

地球空间信息相关论文摘要

基于球面投影的单站地面激光扫描点云构网方法;应用聚类分析方法进行实测重力数据的选点优化;产生最佳Tuned模板的蜜蜂交配算法;移动道路测量系统及其在科技奥运中的应用;三维工程勘察信息系统建设及其应用     

微软和ESRI联合推出数据融合解决方案

近日,在加利福尼亚州圣地亚哥举行的ESRI全球用户大会上,微软公司和ESRI公司联合推出了数据融合解决方案。这是一个支持公共安全与国土安全解决方案的体系结构。该解决方案由两个业界领导者开发,用于帮助公共安全和国土安全领域的专业人员更加有效地防御当前不断增加的有形和无形的安全威胁。此外,该解决方案还可以增强政府机构预测、评估和应对自然灾害的能力。     

Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors ： an input vector and a class codebook vector. When a training sample is input into the model, Kohonen＇s competitive learning rule is applied to selecting the winning neuron from the Kohouen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training sam- ples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.     

基于多传感器遥感数据和改进的单类随机森林的滑坡提取

提出一种利用面向对象多特征和改进的单类随机森林分类器（improved one-class random forest classifier,iOCRF）从多传感器遥感数据提取滑坡的新方法。从两时相高分辨率多光谱图像和中分辨率数字高程模型（DEM）数据中提取的图像对象多特征,来定量表达滑坡引起地表变化和滑坡区地形特征,利用iOCRF对所有特征图像进行分类以提取滑坡。据研究区两时相高分辨多光谱图像和30 m分辨率的ASTER全球DEM数据对提出的方法进行评价。结果表明,所提出方法的提取精度优于只利用部分特征提取和利用传统随机森林的提取精度;利用iOCRF计算不同特征的重要性,并分析不同特征对滑坡提取的贡献。     

低频甚低频传播突然扰动

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