Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change

Understanding the spatial scale sensitivity of cellular automata is crucial for improving the accuracy of land use change simulation. We propose a framework based on a response surface method to comprehensively explore spatial scale sensitivity of the cellular automata Markov chain (CA-Markov) model, and present a hybrid evaluation model for expressing simulation accuracy that merges the strengths of the Kappa coefficient and of Contagion index. Three Landsat-Thematic Mapper remote sensing images of Wuhan in 1987, 1996, and 2005 were used to extract land use information. The results demonstrate that the spatial scale sensitivity of the CA-Markov model resulting from individual components and their combinations are both worthy of attention. The utility of our proposed hybrid evaluation model and response surface method to investigate the sensitivity has proven to be more accurate than the single Kappa coefficient method and more efficient than traditional methods. The findings also show that the CA-Markov model is more sensitive to neighborhood size than to cell size or neighborhood type considering individual component effects. Particularly, the bilateral and trilateral interactions between neighborhood and cell size result in a more remarkable scale effect than that of a single cell size.     

Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.     

Reliability of mooring lines and piles for a permanently manned vessel in a tropical cyclone environment

The factors of safety for stationkeeping systems in current standards (ISO, API) are not derived or validated using reliability analyses. As the oil and gas exploration and production is breaking new boundaries, deploying new floating systems and moving into regions with harsher environments, it is of paramount importance to understand what level of reliability these new marine structures are achieving. This paper presents a reliability analysis of the mooring system of a Floating LNG (FLNG) vessel permanently moored and permanently manned offshore North West Australia in a tropical cyclone environment. The reliability analysis addresses both the mooring chain and the pile foundation. The analysis accounts for the long term characteristics of the environment, including the short term variability, in response to a given sea state and the variability and uncertainty in strength of the mooring chain and the pile. The stationkeeping system was analysed using detailed time domain simulations, capturing system non-linearities and low frequency oscillations as well as wave frequency responses and, thereby, reducing modelling uncertainties to a minimum.It is found that for the conditions modelled, neither the chain nor the pile meet a target reliability of 10⁻⁴/annum using the factors of safety commonly used in design following current ISO and API standards. New factors of safety are proposed to achieve this target reliability. For the pile design, one complicating factor is that current design standards do not explicitly define the exceedance probability that should be associated with the characteristic value of the undrained shear strength to be used in the design. It is demonstrated that the required factor of safety is crucially dependent on the definition of this characteristic value and on the level and the type of uncertainty in the soil strength profile. A recommendation is made regarding the definition of this characteristic value and the associated factor of safety. Furthermore, it is found that designing the mooring system to an environmental condition with a return period of 10,000 yr (as an Abnormal Limit State event), and setting the factor of safety to unity, meets the target reliability of 10⁻⁴/annum for the pile, if the characteristic undrained shear strength is a lower bound, defined in this paper by the 10th percentile value. For the chain however, this target reliability is not achieved.     

北部湾典型海岛生态系统服务价值空间异质性对比研究

基于北部湾海域典型海岛高分1号数据,借助于CART决策树方法,获取了广西北部湾两个典型海岛的景观格局数据,并采用生态系统服务价值计量模型、空间自相关模型及地统计学中的变异函数模型对其生态系统服务价值进行了空间异质性分析。结果表明:团和岛单位面积生态系统服务价值是七星岛的1.08倍,但其变异系数低于七星岛;七星岛由于其地质背景为泥沙岛,景观格局受到人类活动以及自然环境的强烈干扰,趋向于复杂化和破碎化;而团和岛由于所处的外部环境以及自身的地质特征,景观格局呈现出整体斑块化分布状态;团和岛的景观格局主要受到结构性因素的控制,而七星岛则以随机性因素控制为主,选用变程和Moran’s指数来表征其复杂化和破碎化,来决定其优先开发时序,可对前者进行适当开发,而对后者适当进行生态保护;对受到结构性因素影响的岛屿在进行开发时,时序的识别选用变程和Moran’s指数来表征,若变程和Moran’s指数越小,说明海岛整体的景观分布格局趋向于复杂化和破碎化,反之生态系统较好,可进行优先开发。同时本文构建了北部湾海岛生态系统异质性评估与自然资源管理框架,并提出了海岛管理的建议与对策。     

辽宁省海洋服务新业态培育与法律保障研究

海洋服务业已成为海洋经济发展的重要引擎,"十三五"时期是辽宁省海洋经济加快转型升级的关键期,要求培育新动能、发展新模式。因此,培育海洋服务新业态对辽宁省海洋经济发展具有重要意义。文章针对辽宁海洋服务业发展滞后,规模偏小、区域发展不平衡,同质化严重、科技含量低,层次相对低下、与其他产业融合不足,资源整合较差等问题,提出培育海洋服务新业态重要路径为:积极发展四大产业,提高经济规模总量;优化产业区域布局,形成错位发展;提高科技含量,提升海洋服务业层次;促进海洋服务业与其他行业融合协调,提升资源整合度。法律保障措施为:完善法规体系、严格项目审批、提高执法水平、健全应急管理。     

一种海洋混合层深度的智能识别方法研究

文章提出了一种识别混合层深度的人工智能方法。该方法在温度(密度)与压强(或深度)间建立线性模型, 并且将其系数和方差做成一组表征廓线特征的统计量。初始时为模型设定一个主观的先验分布, 在一个自海表向下移动的窗口内通过贝叶斯链式法则和最小描述长度原理学习新数据, 得到系数均值的最大后验概率估计。用F-检验识别系数发生突变的位置, 以此确定混合层的存在性及其深度。通过2017年2月太平洋海域的地转海洋学实时观测阵(Array for Real-time Geostrophic Oceanography, ARGO)数据进行测试, 并且以质量因子(Quality Index, QI)值作为判断识别混合层深度结果准确性的依据, 发现该方法相比于梯度法、阈值法、混合法、相对变化法、最大角度法和最优线性插值法在识别结果上具备更大的QI值。表明该方法能够准确识别混合层深度。     

钙质土中重力串锚水平承载力特性有限元研究

目前没有规范给出串锚的水平承载力计算公式,为了利用有限元法研究串锚水平承载力特性,采用相关理论计算以及室内试验的方法来验证有限元法模拟计算的可靠性。实践证明,有限元法具有较高的计算精度。利用有限元分析软件ABAQUS建立了串锚-土体模型,模拟串锚在水平荷载作用下破坏过程,研究了串锚在水平荷载作用下破坏机理,从而得到了串锚水平承载力特性。在相同的工况条件下,串锚的水平承载力与其锚链长度有关,在一定范围内,增加锚链的长度可以提高串锚的水平承载力;串锚的水平承载力不是相应的单个锚的水平承载力相加,其水平承载力小于相应的单个锚水平承载力之和,在进行串锚水平承载力设计计算时应给与相应的考虑。     

一体化综合减灾智能服务系统研究

针对目前我国减灾服务重决策轻预警,减灾服务技术、系统、应用集成不够,尚缺乏完善的一体化综合减灾智能服务体系现状。该文从测绘地理信息视角,分析了室内外一体化应急定位、多源应急数据融合、灾害场景可视化、灾害模型分析服务等关键技术,构建了一体化综合减灾智能服务原型系统,并在国家基础地理信息中心和陕西省的相关应急部门进行了实际应用,实现了应急信息的一体化感知、定位、融合、分析、服务,为我国综合减灾决策分析提供了技术支撑。     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

基于多模CORS的网络RTK服务性能测试

从北斗地基增强系统建设出发,分析多模CORS实验网,提供多模网络RTK服务,增强北斗卫星导航系统的应用。根据实时测量精度、定位服务的时效性、时间可用性、空间可用性和实用性测试,评价实验网提供的网络RTK服务性能。测试结果表明通过加入北斗导航卫星系统信号,定位精度略为提高,可有效改善电离层模型,提高流动站固定的效率,可以解决困难环境的作业问题,提高作业效率。