Determination of depths to centroids of three-dimensional sources of potential-field anomalies with examples from environmental and geologic applications

A method is developed for determining the depth to the centroid (the geometric center) of ‘semi-compact' sources. The method, called the anomaly attenuation rate (AAR) method, involves computing radial averages of AARs with increasing distances from a range of assumed source centers. For well-isolated magnetic anomalies from ‘semi-compact' sources, the theoretical AARs range from 2 (close to the sources) to 3 (in the far-field region); the corresponding theoretical range of AARs for gravity anomalies is 1 to 2. When the estimated source centroid is incorrect, the AARs either exceed or fall short of the theoretical values. The levelling-off of the far-field AARs near their theoretical maximum values indicates the upper (deeper) bound of the centroid location. Similarly, near-field AARs lower than the theoretical minimum indicate the lower (shallower) bound of the centroid location. It is not always possible to determine usable upper and lower bounds of the centroids because the method depends on characteristics of sources/anomalies and the noise level of the data. For the environmental magnetic examples considered in this study, the determined deeper bounds were within 4% of the true centroid-to-observation distance. For the case of the gravity anomaly from the Bloomfield Pluton, Missouri, USA, determination of only the shallower bound of the centroid location (7 km) was possible. This estimate agrees closely with the centroid of a previously determined three-dimensional model of the Bloomfield Pluton. For satellite magnetic anomalies, the method is appropriate only for high-amplitude, near-circular anomalies due to the inherent low signal-to-noise ratio of satellite magnetic anomalies. Model studies indicate that the AAR method is able to place depths within ±20–30 km of actual center locations from a 400-km observation altitude. Thus, the method may be able to discriminate between upper crustal, lower crustal, and mantle magnetic sources. The results from the prominent Kentucky anomaly are relatively well-resolved (centroid depth 30 km below the Earth's surface). For the Kiruna Magsat anomaly, the deleterious effects from neighboring anomalies make a determination difficult (possible depth could be between 20 and 30 km). The centroid depths are deeper for the Kursk anomaly (40–50 km). These depths may indicate that magnetic anomalies from the near-surface Kursk iron formations (a known contributor) and deep crustal magnetic sources could combine to form the Kursk Magsat anomaly.     

秦岭山区大比例尺地形图测绘方法探讨

根据镇安县金洞沟1：1000地形图测绘作业的实践,提出适于秦岭山区特点的小区域大比例尺地形图测绘的方法．     

The edge-on spiral gravitational lens B1600+434

We present new observations of the gravitational lens (GL) system B1600+434, strongly suggesting that the lens is an edge-on spiral galaxy. These observations are used to constrain the mass model of the system, in particular the oblateness and velocity dispersion of the dark matter halo around the lensing galaxy. From an analytical model we find a lower limit on the halo oblateness q _halo=( c/a )_ρ≳0.4; more detailed numerical models give a lower limit of q _halo≳0.5. We determine an average halo velocity dispersion of σ_halo=190±15 km s⁻¹ over all non-singular isothermal elliptical (NIE) halo models. Constraining the models to larger and more massive discs decreases this average by only 10 km s⁻¹. A lower limit of σ_halo≳150 km s⁻¹ is found, even for disc masses larger than the mass inside the Einstein radius. This lower limit indicates the need for a massive dark matter halo, contributing at least half of the mass inside the Einstein radius. Time-delay calculations give (54±3)/ h ₅₀ d for the NIE halo model and (70±4)/ h ₅₀ d for the modified Hubble profile (MHP) halo model. Although the time delay for both NIE and MHP halo models is well constrained on our parameter grid, it strongly depends on the halo surface density profile. We furthermore find that the presence of a flat luminous mass distribution can severely alter the statistical properties of the lens.     

一个基于空间自相关性的土工参数推测公式

根据土的空间自相关性,提出一个表达简单且具有一定应用价值的土工参数推测公式,实测资料证明,该公式有比较高的推测精度。     

Globular cluster calibration of the peak brightness of the Type Ia supernova 1992A and the value of H0

We have determined the absolute magnitude at maximum light of SN 1992A by using the turnover magnitude of the globular cluster luminosity function of its parent galaxy, NGC 1380. A recalibration of the peak of the turnover magnitude of the Milky Way clusters using the latest Hipparcos results has been made with an assessment of the complete random and systematic error budget. The following results emerge: a distance to NGC 1380 of 18.6 ± 1.4 Mpc, corresponding to ( m  −  M )  31.35 ± 0.16, and an absolute magnitude of SN 1992A at maximum of M _B (max)  −18.79 ± 0.16. Taken at face value, SN 1992A seems to be more than half a magnitude fainter than the other SNe Ia for which accurate distances exist. We discuss the implications of this result and present possible explanations. We also discuss the Phillips relationship between rate of decline and the absolute magnitude at maximum, on the basis of nine SNe Ia, the individual distances of which have been obtained with Cepheids and the globular cluster luminosity function. The new calibration of this relationship, applied to the most distant SNe of the Calan–Tololo survey, yields H ₀ = 62 ± 6 km s⁻¹ Mpc⁻¹.     

星座图贴近度方法在广西北海近海水质监测优化布点上的应用

本文将星座图聚类、欧几里得距离贴近度、中国近海水质评价及t检验方法结合起来,对广西北海近海水质监测点进行分类、择优布点及检验。结果表明,这是一种实用的优化布点方法。     

一种北京城区避难场所可达性评价方法

针对传统两步移动搜寻法应用于避难场所可达性研究中存在的中心供给、统一阈值及无距离衰减的问题,提出了"入口供给、分段阈值、高斯距离衰减"的优化方案。入口供给更符合人类的认知规律,分段阈值则充分考虑了避难场所的面积因素,高斯距离衰减符合可达性随距离递减的规律。改良两步移动搜寻法能够较好地揭示城市应急避难场所与人口相互作用的规律。基于ArcGIS平台,将改良两步移动搜寻法应用于北京城区应急避难场所的可达性研究,获得更加真实、可靠的评价结果,展现了改良两步移动搜寻法在公共服务空间可达性评价方面的重要作用。     

控制点识别的全自动相机标定算法研究

针对现有相机标定环节中控制点需要手动选取,标定自动化程度不高,效率较低的问题。该文在圆心投影点精确定位研究成果的基础上,提出了一种基于角距的控制点自动识别算法,解决了三维高精度控制场下全自动相机标定的关键环节。初步实验表明,在同等条件下,基于该方法的全自动标定精度、效率和稳定性均优于传统人工选取控制点的标定方法。     

Social Distance metric: from coordinates to neighborhoods

Choice of a distance metric is a key for the success in many machine learning and data processing tasks. The distance between two data samples traditionally depends on the values of their attributes (coordinates) in a data space. Some metrics also take into account the distribution of samples within the space (e.g. local densities) aiming to improve potential classification or clustering performance. In this paper, we suggest the Social Distance metric that can be used on top of any traditional metric. For a pair of samples x and y, it averages the two numbers: the place (rank), which sample y holds in the list of ordered nearest neighbors of x; and vice versa, the rank of x in the list of the nearest neighbors of y. Average is a contraharmonic Lehmer mean, which penalizes the difference between the numbers by giving values greater than the Arithmetic mean for the unequal arguments. We consider normalized average as a distance function and we prove it to be a metric. We present several modifications of such metric and show that their properties are useful for a variety of classification and clustering tasks in data spaces or graphs in a Geographic Information Systems context and beyond.