The development of computer networks: First results from a microeconomic model

 Computer networks like the Internet are gaining importance in social and economic life. The accelerating pace of the adoption of network technologies for business purposes is a rather recent phenomenon. Many applications are still in the early, sometimes even experimental, phase. Nevertheless, it seems to be certain that networks will change the socioeconomic structures we know today. This is the background for our special interest in the development of networks, in the role of spatial factors influencing the formation of networks, and consequences of networks on spatial structures, and in the role of externalities. This paper discusses a simple economic model – based on a microeconomic calculus – that incorporates the main factors that generate the growth of computer networks. The paper provides analytic results about the generation of computer networks. The paper discusses (1) under what conditions economic factors will initiate the process of network formation, (2) the relationship between individual and social evaluation, and (3) the efficiency of a network that is generated based on economic mechanisms. Received: 5 July 2000 / Accepted: 28 November 2000     

Exploring land use policy scenarios with the use of a cellular automata-based model: urban sprawl containment and sustainable development in Thessaloniki

This study addresses the issue of urban sprawl through the application of a cellular automata (CA)-based model in the area of Thessaloniki, Greece. The model integrates a multiple regression model at the regional level with a CA model at the local level. New urban land is allocated in a disaggregated field of land units (cells) taking into account a wide range of data. Particular emphasis is placed on the way zoning regulations and land availability data are inserted into the model, so that alternative land use policy scenarios could be examined. Thessaloniki, a typical Mediterranean city, is used as a case study. The model is used to compare two scenarios of urban growth up to year 2030; the first one assuming a continuation of existing trends, whereas the second one assuming the enactment of various land use zoning regulations in order to contain urban sprawl.     

Monitoring and modelling of urban sprawl using remote sensing and GIS techniques

The concentration of people in densely populated urban areas, especially in developing countries, calls for the use of monitoring systems like remote sensing. Such systems along with spatial analysis techniques like digital image processing and geographical information system (GIS) can be used for the monitoring and planning purposes as these enable the reporting of overall sprawl at a detailed level.     

Use of satellite data in urban sprawl and land use studies - a case of lucknow city

The Lucknow Urban Sprawl map for 1972-92 and land use/land cover map of Lucknow area for 1992 were prepared from the satellite imageries of different time period. The analysis has revealed that Lucknow City has been growing at a faster rate especially during the last decade. Most of growth has been towards north-east and South-West direction along major transport routes.     

Incorporating sprawl and adjacency measures in land‐use forecasting model: A case study of Collin County,TX

Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.     

Satellite remote sensing in urban sprawl mapping & monitoring a case study of Delhi

Visual interpretation of satellite data products coupled with field checking is a very useful technique of finding out the physical growth of urban centres. The expansion of urban centres is very fast and conventional ground methods are slow and in-accurate because by these methods, delineation of built-up area is difficult. Mapping and monitoring the urban sprawl, as a result of urban decay of city centre, at regular intervals is very essential for urban planners to understand the trend of development on the urban periphery and subsequently to regulate it. In this study, various data products like Landsat MSS, TM, Toposheets were used to find out the growth of Delhi urban area since 1975 to 1988. Thematic Mapper imagery was used to prepare a broad landuse/land cover map of Delhi and environs. This study was very useful in finding out the potential, as well as shortcomings of satellite data products in the study of various urban aspects.     

Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data

Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development. Urbanizat...     

基于TM影像的焦作市城市扩张与驱动力分析

从焦作市区建设用地扩张特征入手,利用2000年、2008年、2011年三期遥感影像数据,结合焦作市土地利用现状,监测焦作市建设用地及其他各类地物类型空间分异情况,分阶段研究焦作市空间演变格局。在此基础上,结合焦作市社会经济统计数据,利用主成分分析法,对焦作市城市发展进行量化分析,并给出合理化建议。     

Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle

Three-dimensional building models are important for various applications, such as disaster management and urban planning. The development of laser scanning sensor technologies has resulted in many different approaches for efficient building model generation using LiDAR data. Despite this effort, generation of these models lacks economical and reliable techniques that fully exploit the advantage of LiDAR data. Therefore, this research aims to develop a framework for fully-automated building model generation by integrating data-driven and model-driven methods using LiDAR datasets.The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based processing strategy because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time, the quality of the MBRs is examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. The parameters that define the model primitives are adjusted through a model-based boundary fitting procedure using LiDAR boundaries. The level of details in the final Digital Building Model is based on the number of recursions during the MBR processing, which in turn are determined by the LiDAR point density. The model-based boundary fitting improves the quality of the generated boundaries and as seen in experimental results, the quality depends on the average LiDAR point spacing. This research thus develops an approach which not only automates the building model generation, but also achieves the best accuracy of the model while utilizing only LiDAR data.     

导航卫星信号湿延迟参数化模型和数值模式的比较

对高精度导航卫星处理软件(GAMIT)确定的卫星信号湿延迟和香港天文台中尺度数值模式(ORSM)所计算的湿延迟进行了比较,发现二者相关系数为0.99,偏差为3mm,平均绝对偏差为26.7mm,基本不存在系统性的偏差。卫星在天顶时,两者偏差最小,随着卫星仰角的降低,偏差增大,在天顶角70-80°时,两者确定信号湿延迟平均绝对偏差可达30mm。     

CGCS2000与独立坐标系转换模型适用性研究

针对CGCS2000与城市独立坐标系转换中,如何根据需要选择合适转换模型,使产生的转换坐标具有高精度或者高符合性问题,利用CGCS2000与独立坐标系边长差和方位角差比较方法,分析转换模型特性。并通过实例对常用转换模型进行验证,归纳出模型的适用性,解决坐标转换中不同需求模型选择问题。文中方法对其它坐标转换有一定借鉴作用。     

A method for monitoring building construction in urban sprawl areas using object-based analysis of Spot 5 images and existing GIS data

Urban sprawl has been identified as one of the most negative effects of global population growth on the environment and biodiversity. Frequent monitoring of urban sprawl is needed to limit the impact of this ongoing phenomenon. This paper proposes precise monitoring of building construction using an object-based classification methodology applied to Spot 5 images with a 2.5 m resolution. An application at a regional scale on Reunion Island in the Indian Ocean shows that this building extraction methodology has limitations in the production of reference urban maps because of difficulties in defining the shape and the number of buildings compared to classical photo-interpretation of aerial photography. However, these results are of great value for planning in urban sprawl areas where up-to-date information is lacking because of the rapid pace of house construction and residential development.     

盾构施工参数与沉降变形关系模型构建

针对盾构施工参数变化对施工引起的地表变形的重要影响,该文构建了盾构施工参数与地表沉降变形关系模型。以北京市某地铁盾构区间施工过程中的实测数据为基础,分析了不同盾构施工参数与地表沉降变形的关联度和相关性,得到不同参数对沉降变形贡献值的大小;之后,利用多元回归模型方法建立主要影响参数与地表变形的关系模型,并进行模型的合理性检验;最后,利用该模型得到的沉降量与实测数据进行对比分析,结果显示符合性较好。     

群组目标空间方向关系形式化描述模型

针对目前群组目标空间方向关系模型在描述方向关系方面存在的不精确及复杂性等问题,该文提出一种形式化描述模型。该模型采用"剥皮"法计算得到源目标群的边界多边形,较好地顾及了空间形状及分布范围对方向关系的影响;并通过方向关系矩阵模型计算源目标群的边界多边形与各方向区域之间的交,借助矩阵形式化描述源目标群相对于参考目标群的空间方向关系。实验结果表明,该模型较好地克服了现有方法中存在的缺陷,能够准确判断地理空间中两个群组目标之间的空间方向关系。     

基于加权的伪距和历元间相位差分模型GPS单点定位方法

在星载GPS精密定轨或单点定位中,尤其单频接收机的情况下,仅利用相位观测值,由于需要解算模糊度方程通常奇异,仅利用伪距观测资料,由于伪距观测值的噪声影响使得难以实现高精度定位要求。鉴于此,本文讨论了基于加权的伪距和历元间相位差分模型的GPS单点定位方法,该方法既能改善方程奇异性,又无需考虑模糊度因素,能确保观测值的精度。本文分别探讨了伪距观测方程和历元间差分相位观测方程,并给出了联合误差模型,推导了权值的计算公式和参数解算公式,最后基于动态单点定位考虑,探讨了基于加权的伪距和历元间相位差分模型的序贯最小二乘参数解算一般表达式。     

数字地图图像的形态分解与表示

本文论述了目标图像的形态分解、形态分布函数和形态谱函数的基本概念和具体算法，它们是研究数字地图图像的形态分解与表示的主要内容。     

一种人群疏散模型的改进及轻量实现

针对传统人群疏散模拟中基于多智能体模型不能准确表达人群躲避行为和缺少轻量级实现形式的问题,该文提出了一种改进的BOIDS模型躲避规则算法并实现基于WEB形式的人群疏散模拟。先用线球相交方法设置智能体的定义区域;再用球球相交方法计算智能体与障碍物间的距离;最后实现了智能体躲避障碍物行为,并实现针对具体疏散区域空间特征的人群疏散模拟轻量级表示。实验结果表明:改进算法能够准确地表达智能体躲避障碍物时的行为习性,研究成果可为相关管理者进行应急疏散指挥工作的开展提供信息化服务。     

Fractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model

ABSTRACT

A fractional vegetation cover (FVC) estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed, which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarse-resolution FVC pixel were all assumed to have the same vegetation growth model. However, this assumption does not hold over heterogeneous areas, meaning that the method cannot be applied to large regions. Therefore, this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite (GLASS) FVC product. The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data. Then, independent dynamic vegetation models were built for each finer-resolution pixel. Finally, the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale. Validation results indicated that the proposed method (R²?=?0.7757, RMSE?=?0.0881) performed better than either the previous method (R²?=?0.7038, RMSE?=?0.1125) or a commonly used method involving look-up table inversions of the PROSAIL model (R²?=?0.7457, RMSE?=?0.1249).     

Estimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model

Accurately estimating the spatial distribution of forest aboveground biomass (AGB) is important because of its carbon budget forms part of the global carbon cycle. This paper presented three methods for obtaining forest AGB based on a forest growth model, a Multiple-Forward-Mode (MFM) method and a stochastic gradient boosting (SGB) model. A Li-Strahler geometric-optical canopy reflectance model (GOMS) with the ZELIG forest growth model was run using HJ1B imagery to derive forest AGB. GOMS-ZELIG simulated data were used to train the SGB model and AGB estimation. The GOMS-ZELIG AGB estimation was evaluated for 24 field-measured data and compared against the GOMS-SGB model and GOMS-MFM biomass predictions from multispectral HJ1B data. The results show that the estimation accuracy of the GOMS-MFM model is slightly higher than that of the GOMS-SGB model. The GOMS-ZELIG and GOMS-MFM models are considerably more accurate at estimating forest AGB in arid and semiarid regions.