不同影像处理系统的空三数据处理比较研究

系统介绍了像素工厂和海拉瓦数字摄影测量系统的空中三角测量特点,并通过实验比较了二者的性能。实验比较发现,基于两个系统的空中三角测量精度基本相同;执行效率方面,当测区数据量较大时,像素工厂更具有整体优势;而在小区域数据处理上,SOCET GXP更具灵活性。当测区影像超过150景时,建议在像素工厂中进行空中三角测量。     

建筑物白模多边形的自动合并

建筑物白模多边形数据可广泛应用于许多领域,但在实际应用中,由于数据太过细致,且目前使用的建筑物白模多边形数据存在拓扑关系错误,不满足生产要求,这给地图综合中建筑物群的自动合并提出了新的要求.因此提出了一种基于约束性Delaunay三角网的建筑物白模多边形自动合并方法,在保持建筑物整体结构和视觉效果的前提下减少不必要的细...     

城镇黑臭河道治理:多水塘活水链人工湿地的应用

随着现代工业的发展,城市黑臭河道问题日趋严重,严重影响了城市形象、生态环境和居民身心健康。利用多水塘活水链人工湿地技术净化江苏常州永胜河河水水质。监测结果显示:该技术使水体总氮浓度削减了92.0%、总磷浓度削减了82.9%,处理后的水体总氮、总磷含量达到地表IV类水标准。项目年处理水量约30万t,每年以较低的成本(平均水处理费用约为0.03元/t),削减总氮、总磷和氨氮量分别为1496.6 kg、176.0 kg和1408.6 kg。通过引植多种浮叶植物、挺水植物、沉水植物,该湿地修复工程为当地营造了优美的湿地景观。多水塘活水链人工湿地是集经济效益、生态效益、环境效益于一体的新型水体生态治理技术,为我国城镇黑臭河道治理提供了一条新的途径。     

浅谈提高空中三角测量数据成果质量的3个关键环节

空中三角测量数据主要是为摄影测量提供定向框架数据,其质量决定最终产品的质量。笔者结合生产实践中遇到的实际问题,对提高空中三角测量数据成果质量的3个关键环节——航外控制测量,航内控制点量测,外业控制点的残差分析、空中三角测量成果检查及评定的重要性进行了阐述。     

传统村落景观基因信息链与自动识别模型构建——以陕西省为例

传统村落作为活的文化遗产,承载了大量历史记忆,是地域文化景观基因识别与模型构建研究的重要切入点。以陕西省71个国家级传统村落为例,基于景观基因理论建立陕西省传统村落景观基因识别体系,识别出陕西省传统村落景观基因特征;运用类型学原理和N级编码理论对景观基因进行编码,构建陕西省传统村落景观基因信息链并生成基因谱系;借鉴生物学中“胞-链-形”DNA碱基序列模型,提取出环境基因、建筑基因、农耕文化基因和宗族文化基因四个公共基因作为景观基因元（胞）,以村内道路系统作为基因链,构建传统村落景观基因DNA模型与自动识别模型,以此对传统村落的区位、类型、特征和文化基因进行自动识别。为传统村落景观基因信息有效传承与存储,以及乡村建设动态发展提供理论借鉴。     

一种基于GA-BP-MC神经网络的高铁桥墩沉降预测模型

提出一种基于马尔科夫链修正的遗传BP神经网络预测模型（GA-BP-MC）,利用遗传算法的全局寻优能力初始化BP神经网络权值和阈值,初步建立GA-BP神经网络预测模型,结合马尔科夫链的无后效性修正模型预测值,形成高精度GA-BP-MC神经网络变形预测模型。结合高铁桥墩沉降数据,分别与BP神经网络、GA-BP神经网络预测模型进行对比,结果表明,该预测模型精度最高。     

苹果手机零部件全球价值链的价值分配与中国角色演变

产品内分工已成为支配当代企业分工与产品生产的重要模式。研究智能手机生产网络价值分配格局,对辨析中国大陆企业在移动通讯产业价值链中所处地位与演进具有重要意义。论文利用2012—2017年苹果公司供应商数据,以其零部件价值含量与技术要求为测度标准,分析了苹果手机零部件全球价值链的分配特征以及中国大陆企业在其中的地位变化。发现：高价值环节的供应商主要以美国、日本、韩国为主,而中低价值环节则以中国台湾、日本和中国大陆供应商为主,且中国大陆与中国台湾在中间环节占据重要地位。处于价值链高端的供应商分支数量在中国大陆和美国缩减明显,日本、韩国较为稳定,中国台湾增加明显。在价值链的中低端环节,供应商分支趋向中国大陆集中。印度、巴西以及越南等地成为新的中低端价值环节转移承接地。近年来,中国大陆在苹果手机价值链的高端环节得到了提升,长三角、珠三角、京津冀、成渝、中原地区等地逐渐形成了苹果供应商分支的集聚区域,呈现出零部件生产的区域分工特征。长三角(上海-苏州为核心)与珠三角(深圳-东莞为核心),承接了价值链多个生产环节,是中国大陆嵌入苹果手机生产网络的主要阵地。成渝地区既承接了芯片类企业布局,也承接了价值链低端的组装代工和包装服务环节,呈现出在价值链两端双向承接的特征。环渤海、福建及湖南等地主要承接苹果手机价值链的中间环节,而中原地区主要以苹果手机组装与包装服务为主,承接价值链的低端环节。最后,论文从创新驱动、政府作用与外资等方面探讨了影响中国大陆地位提升的因素。     

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.