Knowledge Transfer for Large‐Scale Urban Growth Modeling Based on Formal Concept Analysis

Cellular automata (CA) are useful for studies on urban growth and land‐use changes. Although various methods have been developed to define transition rules, modeling urban growth of large areas remains a tough challenge owing to heterogeneous geographical features. To address the problem, we present a novel method based on the combination of Formal Concept Analysis (FCA) and knowledge transfer techniques. FCA is used to solicit association rules among cities within a large area. This method can provide a theoretical basis for the knowledge transfer process. A cutting‐edge algorithm called TrAdaBoost is then integrated with the commonly‐used Logistic‐CA as the modeling framework. The proposed method is applied to the urban growth modeling of Guangdong Province, a large region with 21 cities in China, from 2005 to 2008. Compared with traditional methods, this method can achieve better results at the provincial and local levels, according to the experiments. The combination of FCA and knowledge transfer is expected to provide a useful tool for calibrating large‐scale urban CA models.     

Classifying Human Activity Patterns from Smartphone Collected GPS data: A Fuzzy Classification and Aggregation Approach

Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone‐measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone‐collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g. up to 96% in activity identification) using of this method. Two examples are provided in the Appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.     

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.     

阿根廷米纳毕戈塔地区水系沉积物采样粒度试验研究

中国地质调查局与阿根廷地质矿产调查局合作在阿根廷西北部米纳毕戈塔地区进行1︰25万水系沉积物测量,该区属于干旱-半干旱高寒山区,为突出找矿效果,消除或减少风积物干扰,需要确定适合于该区的水系沉积物采样粒度。为此,在该区选择一个有已知矿床的1︰5万图幅进行采样粒度试验,分别选择10~60目、-60目、60~80目、-80目4个粒度级进行粒度试验;根据我国区域地球化学勘查规范,每个粒度分析39种元素。结果表明,大部分元素在4种粒度水系沉积物中的分布形态基本一致,都能够较好地反映出区内已知矿床,说明采用的采样方法可以有效地避免风成砂干扰;金、银、铜、锡等成矿元素在4种粒度中的分布略有差异,10~60目的金、铜和锡异常对已知矿体的反应更清晰准确。因此,本区水系沉积物地球化学测量的最佳采样粒度是10~60目。根据本次试验结果,中-阿地调局在本区联合开展1︰25万水系沉积物地球化学测量时采用了10~60目水系沉积物作为采样介质,取得了很好的效果。这是本区第一次进行水系沉积粒度试验,对本区将来的地球化学调查和研究具有指导意义。     

松花江白山河段冰情数值计算及分析

根据水动力学、河流动力学、热力学、河冰水力学及固体力学等原理,针对松花江上游白山河段具体特征,建立了河冰数学模型,并应用有限差分计算方法,对白山河段冬季冰情演变进行了精确模拟。应用该河段1958-1973年共15年完整的地形、气象、水文、热力、冰情等原型观测资料,分别进行了模型参数率定及冰情数值模拟。研究结果表明:白山河段的封冻首先开始于白山坝址下游4 km的大崴子河段,然后封冻边缘逐渐上溯,最终到达松14断面;计算的白山河段冰花堆积体外形与河床纵剖面呈相似趋势;各种水力及冰情要素的数值计算结果和实测值吻合较好,所建立的数值模型能较好地模拟该河道的冰情。研究结果对东北地区河流冬季冰情研究及冰害防治具有一定的借鉴意义。     

Study on the Temporal-Spatial Evolution of Prehistoric Settlements and Its Correlation with Subsistence Strategy and Climate History in the Western Liao River Area

Western Liao River area is one of the most important birthplaces of agricultural civilization in northern China. With recent works like relics survey, site excavation and environmental archaeology going further, the time sequence, cultural content and subsistence strategy history of this area are getting explicit. Questions like ancient exploiting history of natural resources, climate background and cultural impact of subsistence strategy have been paid great attention. Traditional environmental archaeology methods like plant and animal remains analysis are mostly utilized to conduct in-site investigation, current studies rarely adopt quantitative methods to examine the sites’ macro temporal-spatial distribution and aggregation pattern. Based on abundant digitized relic survey data, GIS methods like kernel density analysis are utilized to indicate the temporal-spatial distribution and aggregation pattern of prehistoric cultures in Western Liao River area. The latitudinal, longitudinal and altitudinal migrations of site distributional core are indicated by 3D perspective shift and elevation statistics. By referencing existing studies on subsistence strategy and paleoclimate history, results of spatial analysis are used to reveal the correlation among sites’ temporal-spatial distribution, subsistence strategy adopted and climate variation. This also contributes to our understanding and utilization of massive locational information of prehistoric sites in ancient man-land relationship study.     

基于峰值因子最大化的鬼波压制方法

针对传统拖缆采集得到的海上地震资料受鬼波影响而导致频带宽度变窄,笔者提出一种去鬼波方法,可以压制鬼波效应,拓宽频带。首先在频率-空间域推导出镜像数据生成公式,并基于峰值因子最大化的参数搜索方法来估计最优的鬼波延迟时间,将最优的鬼波延迟时代入镜像记录生成公式,获得最优的镜像记录,利用联合反褶积算法得到最优的去鬼波结果。将本文中的方法应用于模拟的变深度采集数据和海上实测的变深度采集数据,证实该方法可以有效地压制鬼波,消除频谱中的陷波点,得到宽频数据。     

甘肃宝积山盆地中侏罗世石拐茨康叶表皮构造及古环境意义

甘肃宝积山盆地中侏罗统窑街组发现茨康类植物化石,通过对其外部形态和表皮构造研究,认定为石拐茨康叶(Czekanowskia(Vachrameevia)shiguaiensis)。对比当前化石及其现存最近对应种(the nearest living equivalent species)—Ginkgo biloba L.的气孔比率,得到宝积山盆地在中侏罗世的古大气CO_2体积分数为1.55×10~(-3),数值接近GEOCARBⅢ碳平衡模型的拟合曲线,表明茨康叶属植物也是恢复古大气CO_2体积分数的良好材料。同时,通过角质层特征进行古环境重建,结果表明宝积山盆地在中侏罗世时期气候较为温和湿润。     

贵州独山地区富硫铁矿分布规律及找矿意义

独山箱状背斜上富硫铁矿床(点)星罗棋布,且常与锑、铅锌、汞相伴出现,矿体赋存于北西向与北东东向、北东向共轭剪切断裂带及其旁侧影响带内,含矿围岩主要为中泥盆统独山组灰岩、白云岩及下泥盆统丹林组和舒家坪组石英砂岩。因围岩岩性的不同,而使硫铁矿与锑、铅锌、汞之间形成不同的矿产组合,因此本区富硫铁矿不仅自身具有重要的经济价值,而且还是锑、铅锌、汞矿的间接找矿标志。