美国"阳光带"的崛起对中国西部城市化战略的启示

美国西部开发以城市化为先导，中国西部大开发本质上也是西部城市化。西部大开发战略应以城市为中心组织与落实。本文通过透视美国“阳光带”城市崛起的历史，尤其是产业集群的成功经验，提出中国西部城市化战略实施中应将培育地方产业集群作为推动城市化的重要战略方式和地方重要的公共政策工具。     

Correcting method of eddy covariance fluxes over non-flat surfaces and its application in ChinaFLUX

Although Eddy Covariance (EC) technique is one of the best methods for estimating the energy and mass exchanges between underlying surface and atmosphere in micrometeorology, errors and uncertainties still exist without necessary corrections. In this paper, we will focus on the effect of coordinate system on the eddy fluxes. Based on the data observed over four sites (one farmland site, one grassland site and two forest sites), the effects of three coordinate system transforming methods (Double Rotation-DR, Triple Rotation-TR and Planar Fit-PF)on the turbulent fluxes are analyzed. It shows that (i) the corrected fluxes are more or less than the uncorrected fluxes, which is related mainly to the sloping degree of surface, wind speed and wind direction; and (ii) pitch angle has a sinusoidal dependence on wind direction, especially in the regular sloping terrain; and (iii) PF method is something like the simplification of TR or DR,and there are not obvious distinctions in correction in sloping grassland and flat farmland, but PF method is not suitable for uneven and irregular forest sites.     

Changes in the spatial scale of Beijing UHI and urban development

The seasonal and interannual variations of Beijing urban heat island (UHI) are investigated in this paper using the temperature data from 1960 to 2000 at 20 meteorological stations in the Beijing region, and then the relationship between the intensity and spatial scale of UHI and Beijing urbanization indices is analyzed and discussed. Main conclusions are the followings. First, Beijing UHI shows obvious seasonal variations, and it is strongest in winter, next in spring and autumn, and least in summer. The seasonal variation of the UHI mainly occurs in the urban area. The UHI intensity at the center of Beijing is more than 0.8℃ in winter, and only 0.5℃ in summer. Second, the intensity of Beijing HUI exhibits a clear interannual warming trend with its mean growth rate (MGR) being 0.3088℃/10 a. The MGR of HUI is largest in winter, next in spring and autumn, and least in summer, and the urban temperature increase makes a major contribution to the growth of HUI intensity. Third, since the Reform and Opening, the urbanization indices have grown several ten times or even one hundred times, the intensity of HUI has increased dramatically, and its spatial scale also expanded distinctively along with the expansion of urban architectural complexes. Fourth, the interannual variation of urbanization indices is very similar with that of HUI intensity, and their linear correlation coefficients are significant at a more than 0.001 confidence level.     

Least-squares wave-path migration

We present a new least-squares migration method called least-squares wave-path migration. The proposed method combines an iterative conjugate-gradient solver with a stationary-phase wave-path migration operator. Numerical tests demonstrate that (i) least-squares wave-path migration is computationally more efficient than and almost as accurate as Kirchhoff least-squares migration, and (ii) many of the artefacts seen in wave-path migration images are suppressed after several conjugate-gradient iterations. Previous results have shown that 3D wave-path migration is up to 100 times faster than a standard 3D Kirchhoff migration, but sometimes at the cost of reduced quality. With the proposed least-squares wave-path migration method, the image quality in wave-path migration can be improved at an acceptable increase in computational cost.     

GIS支持下的小城镇土地定级--以福建省天宝镇区为例

小城镇土地定级是小城镇土地管理的基础性工作,以福建省天宝镇区土地定级为例,就地理信息系统技术在城镇土地定级中的应用进行了探讨。着重论述了GIS环境下土地定级基础图件库和基础属性数据库的建立、评价单元的生成、单元分值和单元总分值的计算及成果图的生成等属性数据和空间数据的处理过程。     

纳米比亚罗辛地区矿化白岗岩铀矿物学研究及意义

罗辛矿床为世界级白岗岩型铀矿床,存在SJ、SH、SK、Z17、Z19等多个矿（化）带,各矿（化）带矿物组合存在较大差异,但系统的矿物学研究程度不高。本次工作通过岩矿鉴定、扫描电镜观察、电子探针分析等方法,系统研究罗辛地区主要矿（化）带铀矿物共生组合及赋存状态。结果显示,白岗岩矿化按矿物组合可划分为3类: ①晶质铀矿+锆石+磷灰石组合,主要分布在Z17、Z19、SJ矿床（带）;②铀石 、铀钍石+榍石+磷灰石组合,主要分布在SH矿床;③贝塔石组合,主要分布在SK、SH矿床。研究区铀成矿可划分为3个期次：岩浆期、热液期、表生淋积期。岩浆期为主成矿期,研究区晶质铀矿电子探针化学年龄为505±11 Ma,代表岩浆期成矿年龄。SH应进一步寻找铀石、铀钍石+榍石+磷灰石组合矿化白岗岩。     

乌兹别克斯坦铀资源勘查开发现状及投资环境分析

乌兹别克斯坦是中亚铀资源最具勘查开发潜力的地区之一,因此了解并分析乌兹别克斯坦境内铀资源基本情况以及铀资源的投资环境,可为我国天然铀长期可持续发展提供基础和信息支撑。本文在调研权威网站及报告、跟踪最新资讯基础之上,对乌兹别克斯坦铀矿资源的分布、资源量、勘查开发利用现状和对外合作政策等各类数据信息进行了深入的综合分析,并提出了“实时关注乌兹别克斯坦矿业政策,利用先进的核工业技术,与其建立铀资源的互利合作关系,寻求项目合作开发”的建议。本文介绍、综述了乌兹别克斯坦铀资源分布规律及开发现状,希能为我国天然铀企业“走出去”提供重要的基础数据及信息支撑。     

可解释性长短期记忆模型用于预测湖泊总磷浓度变化

对湖泊总磷的变化预测和来源识别对水资源调度和流域生态治理有着重要的意义,然而复杂的生化反应和水动力条件导致的非平稳性给湖泊总磷浓度的准确预测带来极大的困难。为克服这一挑战,本文引入了基于加权回归的季节趋势分解(seasonal and trend decomposition using Loess,STL)技术和夏普利加法(SHapley additive exPlanations,SHAP)结合长短期记忆网络(long short-term memory neural network,LSTM)和门控循环单元(gated recurrent unit,GRU)构建了一个可解释的预测框架,以增强对湖泊总磷浓度演变的预测并提高其可解释性。研究表明:(1)在骆马湖总磷浓度的预测中,该框架拥有较好的预报精度(R²=0.878),优于LSTM和卷积长短期记忆模型(convolutional neural networks and long short term memory network,CNN-LSTM)。当预测时间步长增加到8 h时,该框架有效提高了总磷浓度的预测精度,平均相对误差和均方根误差分别降低了47.1%和33.3%。从预测趋势来看,骆马湖在汛期的总磷平均浓度为0.158 mg/L,相较于非汛期的平均浓度,增加了202.1%。(2)运河来水是骆马湖总磷浓度最重要的影响因素,贡献权重为60.0%,并且不同断面(三湾、三场)的污染源受水动力、气象等因素的影响存在显著的时空差异。本文凸显了神经网络模型在预警水体污染方面的可实施性,并且为提高传统神经网络的学习能力和可解释性的开发与验证提供了重要方向。