Big spatial data for urban and environmental sustainability

ABSTRACT

Eighty percent of big data are associated with spatial information, and thus are Big Spatial Data (BSD). BSD provides new and great opportunities to rework problems in urban and environmental sustainability with advanced BSD analytics. To fully leverage the advantages of BSD, it is integrated with conventional data (e.g. remote sensing images) and improved methods are developed. This paper introduces four case studies: (1) Detection of polycentric urban structures; (2) Evaluation of urban vibrancy; (3) Estimation of population exposure to PM2.5; and (4) Urban land-use classification via deep learning. The results provide evidence that integrated methods can harness the advantages of both traditional data and BSD. Meanwhile, they can also improve the effectiveness of big data itself. Finally, this study makes three key recommendations for the development of BSD with regards to data fusion, data and predicting analytics, and theoretical modeling.     

Defining the geochemical baseline: a case of Hong Kong soils

A geochemical baseline provides the means to distinguish between the pedogenic origin and the anthropogenic origin of the trace element in the environmental compartments. We collected 271 soil samples representative of different parent rocks and soil types from the whole territory of Hong Kong and analyzed the composition of clay mineralogy and the contents of 15 chemical elements (Fe, Cd, As, etc.) for these samples. The baseline was predicted with the method of the normalization procedure combined with the relative cumulative frequency curve. The result indicated that Fe was the best reference element for the normalization procedure among the five potential reference elements (Fe, Al, Sc, Ti, and Mn), followed by Sc and Ti. A poor correlation was found between Sc, Ti, and Cu. The predicted baseline was much lower than the A-value of the Dutch List used usually in screening the polluted soil of Hong Kong, implying that the extent of heavy metal pollution might have been underestimated with respect to local lands. We also applied the cluster analysis to distinguish the geochemical associations of the trace elements due to its importance to the baseline. Approximately three major associations including the Fe–Mn-oxides related, Al oxides or Al-bearing-clay-mineralogy related and sulfide- related associations were observed from the dendrogram.     

最高最低气温突升突降概念模型预报工具初探

通过数理统计和气候分析的方法,得出百色单站24h最高最低气温突升突降的分布特征,进行区间划分和分型.利用概念模型预报方法进行研究,得出最高最低气温突升突降的概念模型预报工具.     

全国最大之一的供热厂工程的设计和服务介绍

介绍一些新技术，新经验，新设备在大型供热厂工程设计中的应用，由于此类工程与一般工程不同，具有当年设计，当年施工，当年投产的特性，故设计配合施工服务显得尤为重要，本文对服务中及时妥善处置相关问题的工作方法和体会也进行了介绍，这对于今天快节奏设计，工程总承包和改企建制，无疑都有一定的帮助和启示。     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

Environmental Radioxenon Levels in Europe: a Comprehensive Overview

Activity concentration data from ambient radioxenon measurements in ground level air, which were carried out in Europe in the framework of the International Noble Gas Experiment (INGE) in support of the development and build-up of a radioxenon monitoring network for the Comprehensive Nuclear-Test-Ban Treaty verification regime are presented and discussed. Six measurement stations provided data from 5 years of measurements performed between 2003 and 2008: Longyearbyen (Spitsbergen, Norway), Stockholm (Sweden), Dubna (Russian Federation), Schauinsland Mountain (Germany), Bruyères-le-Châtel and Marseille (both France). The noble gas systems used within the INGE are designed to continuously measure low concentrations of the four radioxenon isotopes which are most relevant for detection of nuclear explosions: ^131mXe, ^133mXe, ¹³³Xe and ¹³⁵Xe with a time resolution less than or equal to 24 h and a minimum detectable concentration of ¹³³Xe less than 1 mBq/m³. This European cluster of six stations is particularly interesting because it is highly influenced by a high density of nuclear power reactors and some radiopharmaceutical production facilities. The activity concentrations at the European INGE stations are studied to characterise the influence of civilian releases, to be able to distinguish them from possible nuclear explosions. It was found that the mean activity concentration of the most frequently detected isotope, ¹³³Xe, was 5–20 mBq/m³ within Central Europe where most nuclear installations are situated (Bruyères-le-Châtel and Schauinsland), 1.4–2.4 mBq/m³ just outside that region (Stockholm, Dubna and Marseille) and 0.2 mBq/m³ in the remote polar station of Spitsbergen. No seasonal trends could be observed from the data. Two interesting events have been examined and their source regions have been identified using atmospheric backtracking methods that deploy Lagrangian particle dispersion modelling and inversion techniques. The results are consistent with known releases of a radiopharmaceutical facility.     

Variability of soil moisture and its relationship with surface albedo and soil thermal parameters over the Loess Plateau

Data from July 2006 to June 2008 observed at SACOL(Semi-Arid Climate and Environment Observatory of Lanzhou University,35.946°N,104.137°E,elev.1961 m),a semi-arid site in Northwest China,are used to study seasonal variability of soil moisture,along with surface albedo and other soil thermal parameters, such as heat capacity,thermal conductivity and thermal diffusivity,and their relationships to soil moisture content.The results indicate that surface albedo decreases with increases in soil moisture content,s...     

Practical implementation of Hilbert-Huang Transform algorithm

Hilbert-Huang Transform (HHT) is a newly developed powerful method for nonlinear and non-stationary time series analysis. The empirical mode decomposition is the key part of HHT, while its algorithm was protected by NASA as a US patent, which limits the wide application among the scientific community. Two approaches, mirror periodic and extrema extending methods, have been developed for handling the end effects of empirical mode decomposition. The implementation of the HHT is realized in detail to widen the application. The detailed comparison of the results from two methods with that from Huang et al. (1998, 1999), and the comparison between two methods are presented. Generally, both methods reproduce faithful results as those of Huang et al. For mirror periodic method (MPM), the data are extended once forever. Ideally, it is a way for handling the end effects of the HHT, especially for the signal that has symmetric waveform. The extrema extending method (EEM) behaves as good as MPM, and it is better t     

新疆地区地震目录最小完整性震级和台网科学布局研究

地震目录的最小完整性震级M.是地震学中最基础、最重要的研究内容之一,也是地震观测台网效能评估的关键.本文对构造活动剧烈、地震活动水平高、台站地理分布复杂的新疆地区开展M研究,试图为该地区的地震危险性评估和台站科学布局等研究提供参考资料.基于新疆地震台网发展的5个阶段划分,采用基于G-R关系的交互式分析方法,研究了M.的...     

Numerical studies of upwelling in coastalareas of the East China Sea——Ⅰ The tide-induced upwelling

ＮｕｍｅｒｉｃａｌｓｔｕｄｉｅｓｏｆｕｐｗｅｌｌｉｎｇｉｎｃｏａｓｔａｌａｒｅａｓｏｆｔｈｅＥａｓｔＣｈｉｎａＳｅａ－ⅠＴｈｅｔｉｄｅ－ｉｎｄｕｃｅｄｕｐｗｅｌｌｉｎｇＬｕｏＹｉｙｏｎｇ,ＹｕＧｕａｎｇｙａｏ,ＨｕａｎｇＺｕｋｅ（ＲｅｃｅｉｖｅｄＯｃ...