逻辑回归元胞自动机模型的鸡西市城市扩张分析及预测

城市的快速扩张导致人地矛盾激化,土地利用效率下降.分析并预测城市发展状态,可以实现土地资源的合理配置,为城市发展提供合理规划.本文以鸡西市市辖区为例,利用Logistic-CA模型进行城市扩张模拟及趋势特征分析.结果表明:1)鸡西市在2005—2015年间城市处于低速扩张阶段,土地利用效率较低,城市发展较为分散;2)通...     

GIS-based sustainable city compactness assessment using integration of MCDM,Bayes theorem and RADAR technology

In recent decades, compact urban development and smart cities are recognised as most sustainable urban form in an effort to protect natural environment. Therefore, evaluation of existing compactness and sustainability of an area is an essential task before the real development takes place. In the literature, it is possible to see some studies on city’s compactness assessment and most of them have considered only a few aspects of compact development analysis. This paper aims to analyse urban sustainability of Kajang city (Malaysia) through a comprehensive city compactness assessment using geographical information system and radar remote sensing technology. To measure building density, a RADAR image of the study area was used to extract built-up areas with the aid of pixel-based and object-based classification schemes. Mixed land use development, urban density and intensity were the main indicators of the analysis. Finally, multicriteria decision-making and Bayes theorems were applied for overall compactness assessment. Building density analysis was validated using standard confusion matrix, which showed more than 90% accuracy. Similarly, the root-mean squared error showed 0.35 for object-based classification. The results classified the zones of the Kajang city in the range of least to most compact zones with the compactness value of 0.00273–0.0146, respectively. The results obtained in this study can help local government to improve the compactness of least compact zones to make Kajang city more sustainable. Furthermore, the results revealed that efficient public transportation and proper community facilities are the key factors to achieve sustainable urban development.     

成渝城市群城市建设用地扩张格局及规模体系分析

基于1990—2018年六期城市建设用地监测数据，本文利用城市用地年面积增长率指数、公共边测度、核密度估计、位序-规模法则等方法，刻画成渝城市群扩张演化特征及其发展规律，并对城市群规模体系进行分析。结果表明：成渝城市群城市建设用地扩张呈先快后慢的趋势，空间上呈“中部高速，南北低速”的特点，建设用地扩张密度高值主要集中在成都、重庆二市且城市群内部连片发展不明显。城市群新增城市用地呈现无序蔓延态势，并未趋于紧凑。2000—2010年，成渝城市群规模分布极化，呈现明显的双核首位特征，2010年后规模分布由非均衡趋于均衡。     

An Approach for the Classification of Urban Building Structures Based on Discriminant Analysis Techniques

Recognition of urban structures is of interest in cartography and urban modelling. While a broad range of typologies of urban patterns have been published in the last century, relatively little research on the automated recognition of such structures exists. This work presents a sample‐based approach for the recognition of five types of urban structures: (1) inner city areas, (2) industrial and commercial areas, (3) urban areas, (4) suburban areas and (5) rural areas. The classification approach is based only on the characterisation of building geometries with morphological measures derived from perceptual principles of Gestalt psychology. Thereby, size, shape and density of buildings are evaluated. After defining the research questions we develop the classification methodology and evaluate the approach with respect to several aspects. The experiments focus on the impact of different classification algorithms, correlations and contributions of measures, parameterisation of buffer‐based indices, and mode filtering. In addition to that, we investigate the influence of scale and regional factors. The results show that the chosen approach is generally successful. It turns out that scale, algorithm parameterisation, and regional heterogeneity of building structures substantially influence the classification performance.     

Assessing environmental impacts of urban growth using remote sensing

ABSTRACT

This paper provides a study of the changes in land use in urban environments in two cities, Wuhan, China and western Sydney in Australia. Since mixed pixels are a characteristic of medium resolution images such as Landsat, when used for the classification of urban areas, due to changes in urban ground cover within a pixel, Multiple Endmember Spectral Mixture Analysis (MESMA) together with Super-Resolution Mapping (SRM) are employed to derive class fractions to generate classification maps at a higher spatial resolution using an Artificial Neural Network (ANN) predicted Wavelet method. Landsat images over the two cities for a 30-year period, are classified in terms of vegetation, buildings, soil and water. The classifications are then processed using Indifrag software to assess the levels of fragmentation caused by changes in the areas of buildings, vegetation, water and soil over the 30 years. The extents of fragmentation of vegetation, buildings, water and soil for the two cities are compared, while the percentages of vegetation are compared with recommended percentages of green space for urban areas for the benefit of health and well-being of inhabitants. Changes in Ecosystem Service Values (ESVs) resulting from the urbanization have been assessed for Wuhan and Sydney. The UN Sustainable Development Goals (SDG) for urban areas are being assessed by researchers to better understand how to achieve the sustainability of cities.     

Modelling of urban growth boundary using geoinformatics

Abstract

Urban growth boundary (UGB) is a regulatory measure of local government for delineating limits of urban growth over a period of time. Land within the UGB allows urban development, while the land outside of this boundary remains primarily non-urban. The increasing popularity of UGB demands an easy and effective method to design this boundary. This article introduces a new concept, Ideal Urban Radial Proximity (IURP), to designate a spatial UGB using geoinformatics in the digital environment. The Kolkata urban agglomeration was considered to demonstrate this model. Remotely sensed imageries of three temporal instants (years 1975, 1990 and 2005) were considered to determine the information on urban extent and growth of the city. These data were then used as inputs to model the UGB for the years 2020 and 2035. The proposed model discourages scattered development and increase in urban growth rate. It preserves urban vegetation, water bodies and any other important non-urban areas within the inner city space. The IURP concept will also be useful to make the cities circular and polycentric urban blobs into a monocentric tract. Apart from the proposed model and derived results, this research also proves the potential of geoinformatics in modelling a UGB.     

典型海岸带城市扩张的多源遥感监测与预测——以青岛市为例

本文利用自1995年以来的4期DMSP-OLS、NPP-VIIRS夜光遥感影像与Landsat多光谱遥感影像,分析了青岛市近25年的城市建成区范围、各市区边界形态与扩展趋势,并结合土地利用分类、路网、POI、DEM等多源驱动因子及元胞自动机-马尔可夫（CA-Markov）模型,模拟并预测了2027年青岛市土地利用分类。结果表明,近25年青岛建成区扩展主要以外延式为主,其他城区总体上沿胶州湾方向扩展,四周向青岛主城区汇集,主城区建设用地向西北侧发展。本文验证了夜光遥感在监测与预测典型海岸带城市扩张方面的适用性,为城市化发展进程管理与决策提供了重要依据。     

Spatio-temporal analysis for monitoring urban growth – a case study of Indore City

Urban sprawl is characterized by haphazard patchwork of development, which leads to an improper development in any city. To prevent this kind of sprawl in future, it is necessary to monitor the growth of the city. Hence, an attempt has been made in the present study to monitor the urban growth over a period of time by employing Remote Sensing and Geographic Information System techniques in conjunction with Shannon entropy. Shannon entropy is a measure to determine the compactness or dispersion of built-up land growth in the urban areas. The growth patterns of urban built-up land have been studied initially by dividing the area into four zones. The observations have been made with respect to each zone. Then, the study area has been divided into concentric circles of 1 km buffers and the growth patterns have been studied based on urban built-up density with respect to each circular buffer in all four zones. These observations have been integrated with road network to check the influence of infrastructure on haphazard urban growth. It has been found from the study that Shannon entropy is a good measure to determine the spatial concentration or dispersion of built-up land in the city. The study also proved the potential of RS and GIS techniques in the spatio-temporal analysis of urban growth trends and their consequences in the lands adjoining to urban areas.     

一种利用TM图像自动提取城镇用地信息的有效方法

如何快速、准确与客观地提取城镇用地信息,以获得城镇用地的分布范围和面积资料,是有关城镇问题研究中经常涉及到的一个基本问题,现代遥感技术为这个问题的有效解决提供了强有力的保证,运用提出的归一化建筑指数,从TM图像进行了无锡市城镇用地信息的自动提取,研究结果表明,与传统的计算机分类和手工屏幕数字化方法相比,归一化建筑指数法是一种非常行之有效的方法。     

Spatio-temporal analysis of urban growth in selected small,medium and large Indian cities

This study attempts to ascertain the spatial and temporal variations in the evolution of Indian cities using multi-date remote sensing data. A two-stage object-based nearest neighbour classification approach with hierarchical segmentation was used to extract built-up area in selected small, medium and large cities, whereas object-based temporal inversion was applied for change analysis. The temporal trend of net population density, degree of scattered development and compactness of urban core in each city was determined using the built-up area. The study observed a declining trend in growth rate of built-up area in small and medium sized-cities, in contrast to large cities. However, the net population density in cities of all types is decreasing as urban growth has outpaced the corresponding population growth. Furthermore, small and medium cities indicated greater tendency for scattered development in comparison to large cities, whereas the core urban areas of the later appeared relatively less compact.     

基于资源三号卫星影像的城市绿地信息提取方法探讨

我国高分遥感卫星的发展为城市绿地的规划、建设和改造提供有力的技术支持。研究利用资源三号卫星全色和多光谱影像,以国内某城市为例,采用基于规则的面向对象分类技术获取城市绿地。研究提出的技术方案,简单易行,具有较好的应用性。对于推动资源三号卫星在国土资源和城市规划方面的应用具有重要意义。     

Object-based urban land cover classification using rule inheritance over very high-resolution multisensor and multitemporal data

Very high spatial and temporal resolution remote sensing data facilitate mapping highly complex and diverse urban environments. This study analyzed and demonstrated the usefulness of combined high-resolution aerial digital images and elevation data, and its processing using object-based image analysis for mapping urban land covers and quantifying buildings. It is observed that mapping heterogeneous features across large urban areas is time consuming and challenging. This study presents and demonstrates an approach for formulating an optimal land cover classification rule set over small representative training urban area image, and its subsequent transfer to the multisensor, multitemporal images. The classification results over the training area showed an overall accuracy of 96%, and the application of rule set to different sensor images of other test areas resulted in reduced accuracies of 91% for the same sensor, 90% and 86% for the different sensors temporal data. The comparison of reference and classified buildings showed ±4% detection errors. Classification through a transferred rule set reduced the classification accuracy by about 5%–10%. However, the trade-off for this accuracy drop was about a 75% reduction in processing time for performing classification in the training area. The factors influencing the classification accuracies were mainly the shadow and temporal changes in the class characteristics.     

The grey-green divide: multi-temporal analysis of greenness across 10,000 urban centres derived from the Global Human Settlement Layer (GHSL)

ABSTRACT

The presence of green spaces within city centres has been recognized as a valuable component of the city landscape. Vegetation provides a variety of benefits including energy saving, improved air quality, reduced noise pollution, decreased ambient temperature and psychological restoration. Evidence also shows that the amount of vegetation, known as ‘greenness’, in densely populated areas, can also be an indicator of the relative wealth of a neighbourhood. The ‘grey-green divide’, the contrast between built-up areas with a dominant grey colour and green spaces, is taken as a proxy indicator of sustainable management of cities and planning of urban growth. Consistent and continuous assessment of greenness in cities is therefore essential for monitoring progress towards the United Nations Sustainable Development Goal 11. The availability of multi-temporal greenness information from Landsat data archives together with data derived from the city centres database of the Global Human Settlement Layer (GHSL) initiative, offers a unique perspective to quantify and analyse changes in greenness across 10,323 urban centres all around the globe. In this research, we assess differences between greenness within and outside the built-up area for all the urban centres described by the city centres database of the GHSL. We also analyse changes in the amount of green space over time considering changes in the built-up areas in the periods 1990, 2000 and 2014. The results show an overall trend of increased greenness between 1990 and 2014 in most cities. The effect of greening is observed also for most of the 32 world megacities. We conclude that using simple yet effective approaches exploiting open and free global data it is possible to provide quantitative information on the greenness of cities and its changes over time. This information is of direct interest for urban planners and decision-makers to mitigate urban related environmental and social impacts.     

Urban land use change detection using sequential aerial photographs and spot image case study: Chiangmai,Thailand

In most of the developing countries, cities are expanding due to urbanization. To cope-up with problem, planners/decision makers need up-to-date physical data base for proper planning and management of the cities. Such data base can be generated quickly through aerial/satellite remote sensing techniques. In this ‘Case Study’ of Chiangmai, Thailand, sequential aerial photographs and SPOT image were used for urban landuse change studies. A comparison was also made for the growth studies of SPOT and aerial photographs. The analysis of study revealed that maximum agriculture land was converted to urban landuse. Urban growth of the city found to be 3.5 times less in case of SPOT results compared to aerial photographs. Urban landuse change was observed all around the city.     

基于遥感技术的城市发展变化分析

应用遥感技术对城市发展变化进行分析,可为城市规划建设提供辅助依据。本文在前人研究的基础上,将某市4个时期的遥感影像作为研究数据,进行了城区范围、城区植被和土地覆盖信息的提取与分析。研究结果表明,伴随着城市的发展,城区的面积逐年增加,城区植被出现先减少、后增加的现象,而在土地覆盖信息方面也发生了巨大变化。     

山地城市建设用地遥感动态监测研究

为了准确掌握重庆两江新区城市建设情况,有效支撑新区规划编制及规划管理工作,利用高分辨率遥感影像,采用面向对象的遥感分类方法,结合相关辅助资料,对2009年和2010年重庆两江新区的城市建设用地现状进行了遥感监测,获取了区内的城市建设用地规模、结构和布局现状及其变化信息,并对其城市建设用地特征进行了分析,为城市精细化管理提供了技术支撑。     

Spatial-temporal impacts of urban land use land cover on land surface temperature: Case studies of two Canadian urban areas

The surface fabric of urbanized areas, (i.e. its constituent land covers and land uses) plays an essential role in the generation of the urban/rural temperature differences, i.e. the Urban Heat Island (UHI) effect. Land surface information, derived from satellite imagery, and complementary information such as demographics can be used as the basis for an understanding of the atmospheric and surface thermal variations within cities. The results of comprehensive land surface characterizations of two major Canadian urban areas, the Greater Toronto Area and Ottawa-Gatineau, are described. Spatial information, including land cover fraction maps, land use and its historic changes, population density maps are compared with intra-urban surface temperature variations derived from satellite thermal imagery. Three aspects of the impacts of land cover and land use on urban land thermal characteristics are addressed, namely, (a) the relationships between surface temperature and subpixel land cover and population density (b) intra-city seasonal temperature variations and (c) the intensification of the urban heat island effect due to urban built-up land growth.     

基于GIS的山东省中心城市发展水平综合评价

城市在区域发展中占有主导地位,中心城市的综合发展是带动周边地区发展的重要动力,通过城市的优先发展来带动周围区域的发展是国际经验。本文运用主成分分析法和聚类分析的方法,对山东省17个中心城市发展水平做了综合评价,主要成果是:首先,建立中心城市发展水平指标体系,共4个影响因素,20个评价指标;其次,用主成分分析法得出17个中心城市相应的得分并排出名次;最后,用聚类分析的方法将17个城市分成4类。     

基于信息熵的城市边缘区的界定方法研究——以南京市为例

城市边缘区是城乡共同作用的地域单元。如何及时、准确地划分城市边缘区,是目前研究在GIS和RS相关软件的支持下,以南京地区2003年的Landsat TM遥感影像为计算依据,以信息熵理论为基础,结合分析城市边缘区土地利用特征,改进了传统的土地利用信息熵模型,分析熵值分布特点,最后采用突变检测的方法,以熵值60和68确定南京城市边缘区内、外边界的位置,划定了南京城市边缘区的大致范围。研究认为城市边缘区边界是动态变化的;在城乡断面上城市边缘区的景观紊乱度明显高于城市核心区和城市影像区,这为客观划分城市边缘区和利用遥感影像监测城市边缘区的动态变化提供了一个新的途径。