Spatial metrics to study urban patterns in growing and shrinking cities

This article reviews existing literature on spatial metrics, presenting a portfolio of metrics addressing the spatial patterns of growing and shrinking cities and discussing their potential and limitations. A wide and diverse set of spatial metrics was found. While these metrics address most of the identified spatial patterns of urban growth, spatial metrics used in urban shrinkage studies are much scarcer and not nearly sufficient to provide a comprehensive assessment of its spatial patterns. The article concludes that there is great potential for the development of new spatial metrics or mixed indicators, particularly in shrinkage contexts. The article builds on recent literature focusing on reviewing and developing metrics for particular spatial patterns (notably patterns of urban sprawl), while considering a very broad and multidisciplinary set of metrics. It focuses not only on the outcomes of urban growth but also on those of the increasingly common shrinking phenomenon.     

Landscape metrics for three-dimensional urban building pattern recognition

Understanding how landscape pattern determines population or ecosystem dynamics is crucial for managing our landscapes. Urban areas are becoming increasingly dominant social-ecological systems, so it is important to understand patterns of urbanization. Most studies of urban landscape pattern examine land-use maps in two dimensions because the acquisition of 3-dimensional information is difficult. We used Brista software based on Quickbird images and aerial photos to interpret the height of buildings, thus incorporating a 3-dimensional approach. We estimated the feasibility and accuracy of this approach. A total of 164,345 buildings in the Liaoning central urban agglomeration of China, which included seven cities, were measured. Twelve landscape metrics were proposed or chosen to describe the urban landscape patterns in 2- and 3-dimensional scales. The ecological and social meaning of landscape metrics were analyzed with multiple correlation analysis. The results showed that classification accuracy compared with field surveys was 87.6%, which means this method for interpreting building height was acceptable. The metrics effectively reflected the urban architecture in relation to number of buildings, area, height, 3-D shape and diversity aspects. We were able to describe the urban characteristics of each city with these metrics. The metrics also captured ecological and social meanings. The proposed landscape metrics provided a new method for urban landscape analysis in three dimensions.     

Monitoring land changes in an urban area using satellite imagery,GIS and landscape metrics

Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.     

Spatial heterogeneity of urban land-cover landscape in Guangzhou from 1990 to 2005

Urbanization has been the most important process that changed land cover landscape in Guangzhou since reformation, especially since 1990. It is essential for monitoring and assessing ecological consequences of urbanization to understand landscape quantitative characteristics and its changes. Based on four land-cover type maps interpreted from remote sensing TM images of 1990, 1995, 2000 and 2005, combining gradient analysis with landscape metrics, the quantified spatial pattern and its dynamics of urbanization in Guangzhou was got. Three landscape metrics were computed within different regional areas including the whole study area, two transects along two highways (one N–S and the other W–E) and radiation zones with equal distance outwards the city center were set. Buffer zones for transects N–S and W–E were outlined along highways. The following questions should be answered in this paper: What responses were implied with changing spatial grain size or extent for landscape pattern analysis? Could gradient progress of urbanization be characterized by landscape pattern analysis? Did landscape metrics reveal urban expanding gradually? Were there directional differences in land cover landscape pattern during urbanizing development? The results gave some affirmative answers. Landscape pattern exhibited obviously scale-dependent to grain size and extent. The landscape metrics with gradient analysis could quantitatively approach spatial pattern of urbanization. A precise location for urbanized area, like city center and sub-center, could be identified by multiple landscape metrics. Multiple adjunctive centers occurred as indicated by analysis of radiation zones around the city center. Directional differences of landscape pattern along the two transects (N–S and W–E) came into being. For example, fragmentation of landscape in the transect W–E was obviously higher than that in the transect N–S. All in all, some interesting and important ecological implications were revealed under landscape patterns of two transects or radiation zones, and that was the important step to link pattern with processes in urban ecological studies and the basis to improve urban environment.     

1990-2005年广州城市土地覆被景观变化

Urbanization has been the most important process that changed land cover landscape in Guangzhou since reformation, especially since 1990. It is essential for monitoring and assessing ecological consequences of urbanization to understand landscape quantitative characteristics and its changes. Based on four land-cover type maps interpreted from remote sensing TM images of 1990, 1995, 2000 and 2005, combining gradient analysis with landscape metrics, the quantified spatial pattern and its dynamics of urbanization in Guangzhou was got. Three landscape metrics were computed within different regional areas including the whole study area, two transects along two highways (one N-S and the other W-E) and radiation zones with equal distance outwards the city center were set. Buffer zones for transects N-S and W-E were outlined along highways. The following questions should be answered in this paper: What responses were implied with changing spatial grain size or extent for landscape pattern analysis? Could gradient progress of urbanization be characterized by landscape pattern analysis? Did landscape metrics reveal urban expanding gradually? Were there directional differences in land cover landscape pattern during urbanizing development? The results gave some affirmative answers. Landscape pattern exhibited obviously scale-dependent to grain size and extent. The landscape metrics with gradient analysis could quantitatively approach spatial pattern of urbanization. A precise location for urbanized area, like city center and sub-center, could be identified by multiple landscape metrics. Multiple adjunctive centers occurred as indicated by analysis of radiation zones around the city center. Directional differences of landscape pattern along the two transects (N-S and W-E) came into being. For example, fragmentation of landscape in the transect W-E was obviously higher than that in the transect N-S. All in all, some interesting and important ecological implications were revealed under landscape patterns of two transects or radiation zones, and that was the important step to link pattern with processes in urban ecological studies and the basis to improve urban environment.     

中心城区城市增长的情景模拟与空间格局演化

基于1993-2008 年间4 个时相的遥感影像,应用SLEUTH模型模拟与预测自组织和规划引导两类情景下泉州中心城区的城市用地增长过程,并借助空间关联法分析其城市增长的空间格局演化特征,为“两规”空间协调提供科学依据。结果表明：① SLEUTH模型适用于研究区的城市增长模拟与预测,其对城市用地扩展的数量拟合要优于空间匹配,可作为多方案情景模拟的一个技术手段。② 规划引导预案的MPS、ED、AWMSI、MPI 四类景观指数均优于自组织预案,城市用地斑块的整体性、连接性较优,未来城市发展较为紧凑,利于实现土地的集约利用与城市的集聚发展。③ 随预测时间推移,研究区城市用地扩展的速率以及空间集聚性将有所减弱,城市增长的热点区也会发生演变与迁移。2008-2020 年,热点区分布总体呈现“圈层式”结构,局部以“跨江发展”为主要特征;2020-2030 年,热点区总体布局较为发散,局部则呈“环湾发展”与“孤立分布”特征。本研究将情景模拟、景观指数、空间分析等方法有效结合,有助于深刻理解研究区的城市空间增长过程,可为城市管理工作提供决策支持。     

An Extended Minimum Spanning Tree method for characterizing local urban patterns

Detailed and precise information on urban building patterns is essential for urban design, landscape evaluation, social analyses and urban environmental studies. Although a broad range of studies on the extraction of urban building patterns has been conducted, few studies simultaneously considered the spatial proximity relations and morphological properties at a building-unit level. In this study, we present a simple and novel graph-theoretic approach, Extended Minimum Spanning Tree (EMST), to describe and characterize local building patterns at building-unit level for large urban areas. Building objects with abundant two-dimensional and three-dimensional building characteristics are first delineated and derived from building footprint data and high-resolution Light Detection and Ranging data. Then, we propose the EMST approach to represent and describe both the spatial proximity relations and building characteristics. Furthermore, the EMST groups the building objects into different locally connected subsets by applying the Gestalt theory-based graph partition method. Based on the graph partition results, our EMST method then assesses the characteristics of each building to discover local patterns by employing the spatial autocorrelation analysis and homogeneity index. We apply the proposed method to the Staten Island in New York City and successfully extracted and differentiated various local building patterns in the study area. The results demonstrate that the EMST is an effective data structure for understanding local building patterns from both geographic and perceptual perspectives. Our method holds great potential for identifying local urban patterns and provides comprehensive and essential information for urban planning and management.     

Detecting multi-scale urban growth patterns and processes in the Algarve region (Southern Portugal)

The importance of urban growth processes and their spatial characteristics has led to a growing interest in monitoring these phenomena. Spatial metrics are widely employed for this purpose, appearing in an increasing number of studies where they are used to characterise growth patterns and their evolution over time. This paper presents an analysis of urban growth patterns using spatial metrics in the Algarve (southern Portugal), an area of considerable urban dynamics associated with tourism. Two datasets were used (CORINE 1:100,000 maps and COS 1:25,000 maps) and two time periods (1990 and 2006–2007) in order to compare the different urban land use patterns detected and their evolution over time. The results show differences in urban land use patterns and associated processes at each scale, with stable land use patterns predominating at the 1:100,000 scale whereas the 1:25,000 scale showed a move towards more dispersed patterns. These results have enabled an assessment of the principal differences in urban growth patterns observed at both scales, and the implications for planning these entail.     

基于地理标记照片的城市旅游意象空间分异研究

城市旅游感知意象与投射意象的匹配程度是城市旅游形象建设与宣传效果的重要评价,景观尺度下旅游感知与投射意象的空间分异特征可以有效评估游客对城市旅游意象的感知偏差,以此把握旅游者的旅游动机与景观偏好,更好地提升旅游地形象建设。本研究以五大世界著名旅游城市为例,以Flickr网站的地理标记照片数据和政府旅游网站宣传的旅游信息为数据源,利用ArcGIS空间分析技术分析城市旅游感知意象与投射意象的要素构成和空间分异特征。结果表明,城市旅游感知与投射意象的差异既体现在要素构成的偏差上,也体现在空间分布特征的差异方面。除东京旅游感知与投射意象要素结构基本一致以外,其他城市均存在一定程度的偏差。局部空间聚集异常值可视化了五大城市旅游感知意象与投射意象的空间分布偏差,相比城市旅游投射意象的空间集聚,城市旅游感知意象的范围更为离散。同时,双变量空间自相关指数分析结果验证了五大城市旅游感知意象与投射意象均呈显著的空间正相关,但是相关程度和依赖度并不高,说明了从感知与投射视角进行旅游意象空间特征分析的重要性,应以需求为导向进行城市旅游景观规划与宣传。结合地理标记照片数据的空间分析方法为城市旅游感知意象与投射意象的空间分异研究提供了普适性的方法,以服务于城市可持续发展和旅游形象建设。     

基于地理标记照片的城市旅游意象空间分异研究——以五大世界著名旅游城市为例

城市旅游感知意象与投射意象的匹配程度是城市旅游形象建设与宣传效果的重要评价,景观尺度下旅游感知与投射意象的空间分异特征可以有效评估游客对城市旅游意象的感知偏差,以此把握旅游者的旅游动机与景观偏好,更好地提升旅游地形象建设。本研究以五大世界著名旅游城市为例,以Flickr网站的地理标记照片数据和政府旅游网站宣传的旅游信息为数据源,利用ArcGIS空间分析技术分析城市旅游感知意象与投射意象的要素构成和空间分异特征。结果表明,城市旅游感知与投射意象的差异既体现在要素构成的偏差上,也体现在空间分布特征的差异方面。除东京旅游感知与投射意象要素结构基本一致以外,其他城市均存在一定程度的偏差。局部空间聚集异常值可视化了五大城市旅游感知意象与投射意象的空间分布偏差,相比城市旅游投射意象的空间集聚,城市旅游感知意象的范围更为离散。同时,双变量空间自相关指数分析结果验证了五大城市旅游感知意象与投射意象均呈显著的空间正相关,但是相关程度和依赖度并不高,说明了从感知与投射视角进行旅游意象空间特征分析的重要性,应以需求为导向进行城市旅游景观规划与宣传。结合地理标记照片数据的空间分析方法为城市旅游感知意象与投射意象的空间分异研究提供了普适性的方法,以服务于城市可持续发展和旅游形象建设。     

基于GIS场模型的城市餐饮服务热点探测及空间格局分析

餐饮服务是城市生活的重要组成部分,提取城市餐饮服务热点并识别其空间分布模式,对于理解城市形态结构具有重要意义。针对过去基于POI进行城市形态特征定量分析的不足,利用GIS场模型对城市特征要素的空间分布模式进行识别,并采用地学信息图谱对其模式进行可视化和分析。以济南市主城区4.71万个餐饮服务POI作为主要数据源,首先基于密度场热点探测模型提取餐饮服务热点并按照密度值进行等级划分;然后采用广义对称结构图谱和数字场层次结构图谱表达餐饮服务热点的空间分布结构特征和规模等级结构特征,并构建其分布模式图谱;最后对结果展开讨论。研究表明：① 数字场热点探测模型能够有效地从POI中识别出不同等级的热点。② 广义对称结构图谱和基于GIS场模型的层级结构图谱能够分别从纵横两个方面分析和表达餐饮热点的空间分布结构和层次等级结构特征。综上所述,本研究为基于POI的城市特征要素提取和城市形态研究提供了一种有效的定量分析思路,其方法也可以推广至其他城市特征要素的提取、分析和表达当中。     

A linear tessellation model to identify spatial pattern in urban street networks

Street patterns reflect the distribution characteristics of a street network and affect the urban structure and human behavior. The recognition of street patterns has been a topic of interest for decades. In this study, a linear tessellation model is proposed to identify the spatial patterns in street networks. The street segments are broken into consecutive linear units with equal length. We define five focal operations using neighborhood analysis to extract the geometric and topological characteristics of each linear unit for the purpose of grid-pattern recognition. These are then classified by Support Vector Machine, and the result is optimized based on Gestalt principles. The experimental results demonstrate that our method is effective for mining grid patterns in a street network.     

A comparative approach towards ethnic segregation patterns in Belgian cities using multiscalar individualized neighborhoods

Levels of spatial segregation in Western European cities are persistent over space and time. To demonstrate the degree or appearance of spatial segregation, most studies on urban residential patterns still rely on fixed spatial units, aspatial measures and single scales. However, a spatial or temporal comparison of patterns and levels of segregation based on such units or metrics is not without problems. To that end, this paper takes an explicit geographic approach and considers individualized neighborhoods using EquiPop-software, allowing various scales. Using the k-nearest neighbors for all individuals increases international comparability and facilitates interpretation, so far often hampered in segregation research. This multiscalar, multigroup comparative approach on ethnic urban geographies – using Belgium as a case study – provides an empirical illustration of a valuable method and tool applicable in segregation research, thereby furthering the comprehension of the increasingly diverse urban geographies and building on emerging work in the US, Europe and beyond.     

Characterizing mixed-use buildings based on multi-source big data

To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking.     

A spatial cognition-based urban building clustering approach and its applications

This article presents a spatial cognition analysis technique for automated urban building clustering based on urban morphology and Gestalt theory. The proximity graph is selected to present the urban mrphology. The proximity graph considers the local adjacency among buildings, providing a large degree of freedom in object displacement and aggregation. Then, three principles of Gestalt theories, proximity, similarity, and common directions, are considered to extract potential Gestalt building clusters. Next, the Gestalt features are further characterized with seven indicators, that is, area difference, height difference, similarity difference, orientation difference, linear arrangement difference, interval difference, and oblique degree of arrangement. A support vector machine (SVM)-based approach is employed to extract the Gestalt building clusters. This approach transforms the Gestalt cluster extraction into a supervised discrimination process. The method presents a generalized approach for clustering buildings of a given street block into groups, while maintaining the spatial pattern and adjacency of buildings during the displacement operation. In applications of urban building generalization and three-dimensional (3D) urban panoramic-like view, the method presented in this article adequately preserves the spatial patterns, distributions, and arrangements of urban buildings. Moreover, the final 3D panoramic-like views ensure the accurate appearance of important features and landscapes.     

广州市重要通道高峰期交通模式聚类分析

基于广州市重要通道2016年11-12月的交通指数,通过划分重要通道的拥堵与非拥堵状态,确定拥堵状态通道的中心趋势值,建立交通模式的聚类分析模型,采取变异系数对模型进行评价,得出交通模式聚类优选模型。结果显示：广州市重要通道早高峰呈现向心型交通拥堵模式,处于交通拥堵状态的通道可划分为6种交通模式,共3种几何形态类型：滞后型、对称型和递增型。晚高峰的交通拥堵通道分布广泛,区际主干道和天河商业区内的主干道交通拥堵更加严重;处于交通拥堵状态的通道可将其划分为9种交通模式,共4种几何形态类型：前锋型、滞后型、平缓型和对称型。     

北京城市认知的空间关联模式——城市地名认知率的空间分析

论文通过空间聚类分析方法,在基于认知率和位置关系划分认知地点类型、街道类型的基础上,讨论了北京城市地名认知率的空间差异性、基于地点-街道的空间认知关联模式,并得出三方面的结论.第一,北京城市空间认知差异性明显.从地点类型来看,城区南部中心城区和近郊区的认知率低且分布集中,东北部近郊区认知率低且离散性强,西部中心城区和近郊区认知率高且集中,东南中心城区认知率高且离散.从街道类型看,中心城区街道认知率高,外围街道认知率低,表现为中心-边缘结构.第二,各类型街道对23地点的认知率与距离之间表现为不同的结合型式,有近距离一低认知率型、近距离-高认知率型、中距离-中认知率型、远距离-低认知率型、远距离-高认知率型.不同结合型式中距离对认知率的影响因结合型式而异.第三,北京城市空间的认知曲线存在双峰,一峰表现为近距离、高认知率特征,具体位置随认知地点而异;另一峰表现为远距离、高认知率特征,主要是城市中心区认知地点.     

重庆市浅丘带坝区土地利用与景观空间格局分析

选取重庆市沙坪坝区陈家镇为研究区,采用其建立的土地利用现状数据库,运用GIS的图形处理与空间分析功能,生成6种景观格局图并输入Fragstats for ArcView3.X软件,提取景观格局指数,借助于景观格局指数在生态过程与土地利用间所建立的一种关联,分析并探讨土地利用诱发下景观空间格局特征的响应.其结果:水田景观在景观类型中占据着绝对优势,其连接度表现较高,是景观类型明显的基质,受人类活动干扰强;冬水田景观要素接近于水田景观本底,且冬水田景观要素斑块个数、类型面积随着河流缓冲区距离的增大而增加;旱地景观中各景观要素斑块总体上分布比较零散,规律性不强;农村居民点景观要素是建设用地景观的主要类型,其斑块几何形状简单、规整,各斑块间的相似性强,外围边界接近于正方形或者矩形.     

深圳市不透水表面的遥感监测与时空格局

定量监测城市不透水表面扩展过程,是分析城市景观格局动态,深入剖析城市地区空间镶嵌体内部异质性景观相互转化的重要基础。以深圳市为例,通过定量划分城市不透水表面等级体系,计算不透水表面的转移矩阵与景观格局指数,分析不透水表面的时空动态,结果表明:1990～2005年间,高盖度及极高盖度的不透水表面持续增加,中盖度及低盖度不透水表面先增加后减少,而自然地表及极低盖度的不透水表面则为先减少后恢复,反映了城市化进程对城市地表覆被的结构性影响。景观格局变化显示景观多样性程度较高,且经历了低-高-低-高的变化;斑块在1990年以自然地表为主,1995年以后以中盖度等级为主,高盖度等级显著增加。自然地表和中等盖度的不透水表面变化分别主导着前期和中后期的变化过程。城市建设的迅速扩张,将林地、农田、水体及滩涂等自然地表快速地转变为不同功能的建设用地,主导着不透水表面等级分布的梯度性变化。     

基于多源数据的长沙市人居热环境效应及其影响因素分析

针对城市人居热环境效应研究缺乏从自然—人文多维因子组合综合评价分析的现状,本文基于多源空间数据（Landsat 5、Landsat 8卫星影像数据、POI空间大数据、数字高程模型等）反演长沙市2000年、2009年和2016年城市地表温度格局,并快速获取与城市热环境密切相关的自然和人文因素共12个影响因子。应用标准差椭圆、空间主成分分析（PCA）等方法多角度分析了城市人居热环境效应及影响因素的联动关系。结果表明：① 2000—2016年共16年间热岛面积共增加547 km²、地表最高温度差达到10.1 ℃。城市热岛区的空间分布主要集中在城市建成区,如工商业集中和人口密集的城市中心地区,并呈现出地表温度从城市中心向郊区逐渐降低的热岛的空间分布格局,出现多个高温中心点,如五一广场商圈、长沙县星沙经济技术开发区、望城工业区、岳麓工业集中区、天心工业区等;② 2000—2016年热岛空间发展主轴保持在东北—西南方向,2000—2009年热岛重心向西南偏移了2.7 km,偏转角度为54.9°,2009—2016年热岛重心向东北偏移了4.8 km,偏转角度为60.9°。整体上,长沙市热环境空间格局的变化和城市的建设强度的变化存在一定的关联;③ 通过主成分分析得出影响长沙城市热环境格局的因子为景观格局、城市建设强度、地形地貌3个主因子;④ 人文因素对于当前加剧热岛效应形成产生的促进作用明显大于自然因素的抑制作用,综合作用下地区将升温0.293 ℃。影响城市人居热环境的因素众多,多源数据有助于揭示城市热环境空间格局及演变规律,深化对城市热岛效应成因分析认知,明确人文和自然影响因素间相关关系和相关程度,以此为改善城市人居环境质量提供科学依据。