土地利用现状和规划数据建库容差浅析

通过对第二次全国土地调查(以下简称"二调")和土地利用总体规划数据建库过程中误差的产生和传播分析,通过误差理论和容差设置实际研究。提出现行数据建库容许误差(以下简称容差)设置不合理,设置过高引起大量无用的数据处理工作。建议合理设置容差参数,提高数据库建设和更新效率。     

Weak GPS signal tracking using FFT discriminator in open loop receiver

An open loop tracking architecture, which tracks GPS signals under weak and challenging conditions, is analyzed. The in-phase and quadrature-phase integration pair is regarded as a single tone complex signal. An FFT-based method is used as a frequency discriminator to estimate the Doppler frequency residual of the single tone signal. Another FFT-based method applies complex squaring to eliminate the effect of the navigation data bits polarities. The performance of the FFT-based discriminators is assessed in three criteria. Those criteria are the signal strength and dynamic range that can be tracked and the accuracy of the estimated Doppler frequency. In addition, the performance of the discriminators is analyzed to provide the theoretical and simulated peak detection probability. The results indicate that the FFT discriminator can track signals about 5 dB weaker than the signals that can be tracked by the complex squared FFT discriminator. In a quasi-static environment, the Doppler frequency residual can be assumed to be around zero, which can enable the FFT-based discriminators to track signals with approximately 2 dB less power. Moreover, the performance of the FFT-based discriminators is compared with the performance of two other frequency discriminators, namely the fast–slow and power-based. The comparison results indicate that these two frequency discriminators give higher frequency estimation accuracy, but they have a narrower dynamic range.     

Validation of MODIS Vegetation Continuous Fields for monitoring deforestation and forest degradation: two cases in Mexico

This study assesses whether MODIS Vegetation Continuous Fields percent tree cover (PTC) data can detect deforestation and forest degradation. To assess the usefulness of PTC for detecting deforestation, we used a data set consisting of eight forest and seven non-forest categories. To evaluate forest degradation, we used data from two temperate forest types in three conservation states: primary (dense), secondary (moderately degraded) and open (heavily degraded) forest. Our results show that PTC can differentiate temperate forest from non-forest categories (p = 0.05) and thus suggests PTC can adequately detect deforestation in temperate forests. In contrast, single-date PTC data does not appear to be adequate to detect forest degradation in temperate forests. As for tropical forest, PTC can partially discriminate between forest and non-forest categories.     

A support vector machine classifier based on a new kernel function model for hyperspectral data

The kernel function is a key factor to determine the performance of a support vector machine (SVM) classifier. Choosing and constructing appropriate kernel function models has been a hot topic in SVM studies. But so far, its implementation can only rely on the experience and the specific sample characteristics without a unified pattern. Thus, this article explored the related theories and research findings of kernel functions, analyzed the classification characteristics of EO-1 Hyperion hyperspectral imagery, and combined a polynomial kernel function with a radial basis kernel function to form a new kernel function model (PRBF). Then, a hyperspectral remote sensing imagery classifier was constructed based on the PRBF model, and a genetic algorithm (GA) was used to optimize the SVM parameters. On the basis of theoretical analysis, this article completed object classification experiments on the Hyperion hyperspectral imagery of experimental areas and verified the high classification accuracy of the model. The experimental results show that the effect of hyperspectral image classification based on this PRBF model is apparently better than the model established by a single global or local kernel function and thus can greatly improve the accuracy of object identification and classification. The highest overall classification accuracy and kappa coefficient reached 93.246% and 0.907, respectively, in all experiments.     

Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.     

Laboratory Estimation of Rock Joint Stiffness and Frictional Parameters

Numerical modeling of complex rock engineering problems involves the use of various input parameters which control usefulness of the output results. Hence, it is of utmost importance to select the right range of input physical and mechanical parameters based on laboratory or field estimation, and engineering judgment. Joint normal and shear stiffnesses are two popular input parameters to describe discontinuities in rock, which do not have specific guidelines for their estimation in literature. This study attempts to provide simple methods to estimate joint normal and shear stiffnesses in the laboratory using the uniaxial compression and small-scale direct shear tests. Samples have been prepared using rocks procured from different depths, geographical locations and formations. The study uses a mixture of relatively smooth natural joints and saw-cut joints in the various rock samples tested. The results indicate acceptable levels of uncertainty in the calculation of the stiffness parameters and provide a database of good first estimates and empirical relations which can be used for calculating values for joint stiffnesses when laboratory estimation is not possible. Joint basic friction angles have also been estimated as by-products in the small scale direct shear tests.     

天津市地热资源开发利用特征及存在问题分析

天津地区的地热地质条件良好,蕴藏着丰富的地热资源。在地热资源的开发利用过程中,每年可产生可观的经济、社会和环境效益,但由于开发方式的不尽合理,带来诸多问题。文章阐述了天津开发利用地热资源的特征,分析了存在的问题。认为不同热储层间水力联系的存在和地热井间距的过小,造成开采层间相互影响较大;地热井布局不合理、开采层位相对集中、回灌程度不高导致局部热储层压力大幅度下降,持续的大幅度压力下降将引发吊泵和地面沉降;超标准排放地热尾水会造成资源浪费和热污染;采、灌井间距的过小和相对位置的不合理,存在冷突破风险。针对不同问题,给出了针对性解决问题的建议。     

南水北调中线突发水污染事件的快速预测

依据南水北调中线干渠资料,开展了正常输水情况下串联明渠内可溶污染物浓度分布规律数值模拟研究。采用数值模拟、数学归纳和统计分析方法,提出表征污染物输移扩散特征的峰值输移距离、污染带长度和峰值浓度的快速预测公式;通过示范工程验证了快速预测公式的可行性。结果表明:①串联明渠内,峰值输移距离随渠道流速减小而减小,并且污染带长度增加值随明渠内流速减小而减小,但是峰值浓度随明渠流速减小而增加;②快速预测公式计算结果与现场试验实测结果的误差均不到15%,证明了快速预测公式的合理性和可行性。这些研究结果为南水北调中线工程突发可溶性水污染事件应急预警方案的制定提供了科学依据。     

同步辐射软X射线吸收谱与发射谱测定天然针铁矿能带结构

天然半导体矿物由于成分、缺陷复杂,传统测试方法如紫外可见漫反射等难以准确测定其禁带宽度.本文以针铁矿为例,通过第一性原理计算得到纯针铁矿及掺Al针铁矿的电子结构.计算结果显示,纯针铁矿导带底与价带顶均由Fe3d与O2p轨道组成,而当含杂质Al时,Al2p与O2p发生杂化参与了价带组成.在此基础上,利用同步辐射X射线氧的K边吸收谱与发射谱对纯针铁矿及天然针铁矿的能带结构进行了测定.结果表明,天然含Al的针铁矿禁带宽度为2.30eV,小于纯针铁矿(2.57eV).本研究提供了一种测定天然氧化物矿物禁带宽度的新方法,为深入研究天然半导体可见光催化活性产生机制提供了理论依据.