地理信息在智慧城市系统中的地位刍议——以阿勒泰地区应用为例

地理信息系统是智慧城市建设中的重点项目。地理信息是大部分智慧城市应用系统的基础信息。倾斜摄影测量技术的发展,使得获取三维地理信息的成本大大降低,数据应用更加广泛。地理信息实时共享是开拓智慧城市应用领域的关键。因此,如何部署数据、计算、软件和软件模块资源,如何建设地理信息服务平台,对各种应用开发会产生重大影响。各种资源在网络中的部署、信息服务"供给侧"设计、网络业务的高效无缝集成,是对智慧城市设计者的新挑战。     

Multiple Discriminant Analysis of Marine Sediment Data

A multivariate statistical approach was used in the analysis of inter-relationships among marine benthic infaunal structure, physical and chemical characteristics of sediment samples and toxicity data derived from laboratory tests at 16 locations in shallow, inshore waters of Hong Kong. The method involved classification (cluster analysis using the Bray–Curtis similarity index) and ordination (multi-dimensional scaling) of infaunal patterns and the use of multiple discriminant analysis to relate groupings of the locations to the selected environmental and toxicity data. Analysis of the combined sediment physical, biological, chemical and toxicity dataset by stepwise multiple discriminant analysis allowed identification of those variables most sensitive for discriminating location groups. The use of multiple discriminant analysis in sediment quality characterization was evaluated against the Sediment Quality Triad approach and other statistical techniques.     

Assessment of soil factors controlling ephemeral gully erosion on agricultural fields

The soil factor is crucial in controlling and properly modeling the initiation and development of ephemeral gullies (EGs). Usually, EG initiation has been related to various soil properties (i.e. sealing, critical shear stress, moisture, texture, etc.); meanwhile, the total growth of each EG (erosion rate) has been linked with proper soil erodibility. But, despite the studies to determine the influence of soil erodibility on (ephemeral) gully erosion, a universal approach is still lacking. This is due to the complex relationship and interactions between soil properties and the erosive process. A feasible soil characterization of EG erosion prediction on a large scale should be based on simple, quick and inexpensive tests to perform. The objective of this study was to identify and assess the soil properties – easily and quickly to determine – which best reflect soil erodibility on EG erosion. Forty‐nine different physical–chemical soil properties that may participate in establishing soil erodibility were determined on agricultural soils affected by the formation of EGs in Spain and Italy. Experiments were conducted in the laboratory and in the field (in the vicinity of the erosion paths). Because of its importance in controlling EG erosion, five variables related to antecedent moisture prior to the event that generated the gullies and two properties related to landscape topography were obtained for each situation. The most relevant variables were detected using multivariate analysis. The results defined 13 key variables: water content before the initiation of EGs, organic matter content, cation exchange capacity, relative sealing index, two granulometric and organic matter indices, seal permeability, aggregates stability (three index), crust penetration resistance, shear strength and an erodibility index obtained from the Jet Test erosion apparatus. The latter is proposed as a useful technique to evaluate and predict soil loss caused by EG erosion. Copyright © 2018 John Wiley & Sons, Ltd.     

Extracting water-related features using reflectance data and principal component analysis of Landsat images

This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4–5–7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.     

地理信息科学方法论的理论体系研究

地理信息科学是地理学的一个分支,其方法论研究受到科学哲学和地理学方法论的指导,同时也从大量的该学科研究成果、工程项目和软硬件产品中提炼的案例中总结和归纳而来。本文在本学科的时代需求和国家前瞻布局的背景下开展研究。首先阐述了地理信息科学方法论的哲学观和实用观,提出了研究中应该处理好的六个关系;其次,建立了方法论的结构体系,由地理信息本体论、六个科学方法和七个技术方法组成;再次,分析和论证了地理信息的本体特征及其与方法论的关系,最后讨论了地理信息科学方法论的创新机制和策略。     

基于多元自回归样条的液化侧移灾害评估模型

为了将液化侧移计算方法本土化,本文基于Youd等人收集的液化侧移数据库,采用擅长处理复杂参数维度问题的多元自适应样条回归法（MARS）建立液化侧移计算模型。经验证,该方法建立的模型精度和可靠性都可以通过检验。本文主要内容包括：（1）在本土化过程中,本文选取峰值加速度PGA作为地震动参数,替代现有模型中的M和R,计算结果并未影响液化侧移计算精度;（2）在MARS方法进行建模过程中,对临空和缓坡两种情况的影响因素进行重要性程度计算和筛选;（3）建立两种情况下的液化侧移计算模型,并用F检验法和t检验以及新西兰2010—2011年系列地震中液化侧移数据进行检验,证明本文方法的合理性和可靠性。本文的结果能满足我国相关规范、工程师以及岩土地震工程防灾减灾等方面的需求,还可为地震液化侧移灾害小区划提供理论基础。     

MULTIVARIATE GEOMORPHIC ANALYSIS OF FOREST STREAMS: IMPLICATIONS FOR ASSESSMENT OF LAND USE IMPACTS ON CHANNEL CONDITION

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10 disturbed from 13 undisturbed reaches with 90 per cent and 92 per cent correct classification respectively. These variables are the total number of pools per reach, the ratio of mean residual pool depth to mean bankfull depth, and the ratio of critical shear stress of the median surface grain size to bankfull shear stress. The last variable can be dropped without a decrease in rate of correct classification; however, the resulting two-variable model may be less robust. Analysis of the distribution of channel units, including pool types, can also be used to discriminate disturbed from undisturbed reaches and is particularly useful for assessment of aquatic habitat condition. However, channel unit classification and inventory can be subject to considerable error and observer bias. Abundance of pool-related large woody debris is highly correlated with pool frequency and is an important factor determining channel morphology. Results of this study yield a much needed, objective, geomorphic discrimination of pristine and disturbed channel conditions, providing a reference standard for channel assessment and restoration efforts.     

黄海中南部近岸海域春季鱼类浮游生物群落空间格局研究

根据2015年春季在黄海中南部近岸海域进行的鱼类浮游生物大型浮游生物网水平拖网数据,采用生态多样性指数和多元统计分析等方法,研究了该海域鱼类浮游生物的种类组成和群落空间格局及其与环境因子的关系。结果表明,本次调查共采集到鱼类浮游生物35种,其中鱼卵21种,仔稚鱼23种。鱼类浮游生物隶属于8目18科34属,优势种为鳀（Engraulis japonicus）、鲬（Platycephalus indicus）、鱼衔属（Callionymus spp.）和小黄鱼（Pseudosciaena polyactis）。其中,鳀和鱼衔属主要分布于海州湾渔场海域,鲬主要分布于吕泗渔场海域,小黄鱼多分布于吕泗渔场北部海域。生态类型包括半咸水型、沿岸型和近海型种类。聚类分析表明,鱼类浮游生物群落可划分为以鱼衔属、鳀为优势种的站位组A（主要分布于海州湾海域）、以小黄鱼、黄鲫（Setipinna taty）等为优势种的站位组B（主要位于江苏沿岸海域）和以鲬为优势种的站位组C（主要位于江苏沿岸-近海海域）,以站位组B的群落物种多样性指数和均匀度指数最高。各站位组的鱼类浮游生物的生态类型和适温类型组成不同,这与其所处的海域生境有关。典范对应分析（CCA）表明,影响春季黄海中南部鱼类浮游生物群落空间结构的主要环境因子为水深和表层温度。同时也受洋流、底质类型等多种因素的综合影响。研究结果初步揭示了黄海中南部近岸海域鱼类浮游生物群落的空间格局,可为今后科学制定该海域水产种质资源保护区、资源量化管理等资源养护管理措施提供科学依据与技术支撑。     

Statistical models for shear strength of RC beam‐column joints using machine‐learning techniques

This paper proposes a new set of probabilistic joint shear strength models using the conventional multiple linear regression method, and advanced machine‐learning methods of multivariate adaptive regression splines (MARS) and symbolic regression (SR). In order to achieve high‐fidelity regression models with reduced model errors and bias, this study constructs extensive experimental databases for reinforced and unreinforced concrete joints by collecting existing beam‐column joint subassemblage tests from multiple sources. Various influential parameters that affect joint shear strength such as material properties, design parameters, and joint configuration are investigated through tests of statistical significance. After performing a set of regression analyses, the comparison of simulation results indicates that MARS approach is the best estimation method. Moreover, the accuracy of analytical predictions of the derived MARS model is compared with that of existing joint shear strength relationships. The comparison results show that the proposed model is more accurate compared to existing relationships. This joint shear strength prediction model can be readily implemented into joint response models for evaluation of earthquake performance and inelastic responses of building frames. Copyright © 2014 John Wiley & Sons, Ltd.     

Empirical prediction of coseismic landslide dam formation

In this study we develop an empirical method to estimate the volume threshold for predicting coseismic landslide dam formation using landscape parameters obtained from digital elevation models (DEMs). We hypothesize that the potential runout and volume of landslides, together with river features, determine the likelihood of the formation of a landslide dam. To develop this method, a database was created by randomly selecting 140 damming and 200 non‐damming landslides from 501 landslide dams and > 60 000 landslides induced by the M_w 7.9 2008 Wenchuan earthquake in China. We used this database to parameterize empirical runout models by stepwise multivariate regression. We find that factors controlling landslide runout are landslide initiation volume, landslide type, internal relief (H) and the H/L ratio (between H and landslide horizontal distance to river, L). In order to obtain a first volume threshold for a landslide to reach a river, the runout regression equations were converted into inverse volume equations by taking the runout to be the distance to river. A second volume threshold above which a landslide is predicted to block a river was determined by the correlation between river width and landslide volume of the known damming landslides. The larger of these two thresholds was taken as the final damming threshold. This method was applied to several landslide types over a fine geographic grid of assumed initiation points in a selected catchment. The overall prediction accuracy was 97.4% and 86.0% for non‐damming and damming landslides, respectively. The model was further tested by predicting the damming landslides over the whole region, with promising results. We conclude that our method is robust and reliable for the Wenchuan event. In combination with pre‐event landslide susceptibility and frequency–size assessments, it can be used to predict likely damming locations of future coseismic landslides, thereby helping to plan emergency response. Copyright © 2014 John Wiley & Sons, Ltd.