利用遥感监测和分析珠江三角洲的城市扩张过程——以东莞市为例

伴随着经济的快速增长,珠江三角洲近年来出现了迅速的城市化以及乡村城市化的过程。沿着城镇边缘和公路两旁,大片的农田被侵占来单方面地满足城市开发的需要,忽略了粮食产量减少以及环境质量恶化等问题。利用遥感可以有效地监测珠江三角洲的城市扩张过程。在遥感多时相监测的基础上通过熵的计算,可以定量地描述城市扩张的空间规律及扩散过程。     

Crossing-over between land cover and land use: Exploring spatially varying relationships in two large US metropolitan areas

Difficulties in identifying actual uses of land space from remote sensing-based land cover products often result in lost opportunities to enhance the capacity of applied research on human settlements. In an attempt to address these difficulties, this study investigates how land cover and land use are interrelated with each other and what determines the relationship patterns by analyzing detailed land use and land cover data for two large US metropolitan areas – the five-county Los Angeles and six-county Chicago regions – where a broad spectrum of human settlements, ranging from urban cores to less-urbanized edges, coexist. The analysis shows that the land cover-land use relationship substantially varies not only across regions but across neighborhoods within each region. Through multivariate regression, it is also found that the intraregional variation is highly associated with the neighborhood's stage of urbanization, median housing age, and other development characteristics, suggesting that the relationship pattern can largely be shaped by the history and evolution of urban design/development.     

COMPARATIVE METROPOLITAN AREA ANALYSIS: MATCHING THE 1980 AND 1990 CENSUS PUBLIC USE MICRODATA SAMPLES FOR METROPOLITAN AREAS

The 1980 and 1990 Public Use Microdata Samples (PUMS) of the U.S. Census contain detailed information on individuals in large samples. The incompatible PUMS metropolitan geographies across these census years, however, compromise use of these data. In this note, we discuss a procedure to match the geography of the 100 most populous metropolitan areas in the 1980 and 1990 PUMS. Programmed in SAS, this set of matched metropolitan areas facilitates comparative urban analysis for 1980 and 1990. The code can be downloaded from a website (http://baja.sscnet.ucla.edu/εellis/metrocode.html).     

大都市区城市扩张过程及形态对比分析——以东京、纽约和上海为例

大都市区化是全球城市化进程中的普遍现象,研究大都市区域城市扩张进程对理解其未来增长趋势、区域可持续发展具有重要意义。大都市区土地扩张及区域间的对比分析,以及都市区发育过程中城市扩张的一般化空间模式还未被深入理解。论文选取东京、纽约和上海3个大都市区,获取1990—2015年间3期Landsat影像数据,使用梯度和格网分析法,采用城市土地密度函数和城市扩张指数,从建设用地数量变化及其时空分布、城市形态变化等方面,多角度对比分析各城市不同阶段建设用地增长的时空差异。结果表明：① 大都市区边界仍在不断扩展,建设用地在研究期内持续增长;20多年间东京、纽约和上海的建设用地面积分别增长了63%、53%和233%;上海一直处于高强度扩张状态,而纽约的城市扩张在后期几近停滞。② 大都市区建设用地密度从中心向外呈圈层递减式分布,城市核心区和边缘区半径的增长最明显;城市形态均趋向于紧凑。③ 新增建设用地时空异质性明显。东京的远郊新城不断建设,纽约一些尚有发展潜力的区域次中心仍在扩张但速率逐渐放缓,上海的核心区外围增长剧烈并逐渐向远城区推进。④ 大都市区域扩张先后经历高速期—缓慢期—停滞期,扩张进程表现为核心区膨胀—次中心及新城建设—逐步形成稳定的多中心结构。     

The Spatial Restructuring of Population in Metropolitan Beijing: Toward Polycentricity in the Post-Reform ERA

Based on data from the third (1982), fourth (1990), and fifth (2000) Population Census of China, this research examines the changing patterns of population distribution in the Beijing metropolitan area in the post-reform era. In the mid-1980s, China launched a series of urban land use reforms aimed toward achieving a market economy. A direct impact of these reforms in Beijing was the restructuring of land uses, evidenced by the relocation of central-city residents to the suburbs to make room for commercial development. This residential suburbanization trend emerged during the 1980s and accelerated in the 1990s. Population change rates varied significantly across subdistricts, and variation was much greater in the 1990s than in the 1980s, indicating an increasingly diverse set of growth trajectories across metropolitan Beijing over time. Various population density functions are tested. The population density pattern is best characterized by a monocentric model in 1982, a dual-centered model in 1990, and a seven-centered model in 2000. This transition in Beijing's urban form toward polycentricity is similar to trends in most Western cities.     

2000–2015年京津走廊耕地和建设用地变化监测研究（英文）

Rapid peri-urbanization has become a new challenge for sustainable urban-rural development worldwide. To clarify how unprecedented urban sprawl at the metropolitan fringe impacts urban-rural landscape, this study took the Beijing-Tianjin corridor of Beijing-Tianjin-Hebei metropolitan area, one of the largest urban clusters in China, as a typical example. By using Landsat-based landscape metrics and a practical methodology, we investigated the landscape changes and discussed the potential reasons in the context of rapid peri-urbanization of China. Specifically, multi-temporal land use maps derived from Landsat images were used to calculate landscape metrics and analyze their characteristics along the urban-rural gradients. The practical methodology was used to monitor spatio-temporal characteristics of landscape change in large metropolitan areas. The results showed that landscape patterns in the area had changed greatly from 2000 to 2015 with characteristics of construction land sprawl and arable land shrinkage. The intensity and scale of landscape changes varied along the urban-rural gradients. Sampled plots in urbanized areas and rural areas demonstrated distinguishable landscape patterns and significant differences. Urban areas had more heterogeneous and fragmented landscapes than rural areas. Peri-urban areas in general experienced higher levels of land diversification than rural areas. Rural residential land appeared to be more aggregated near Beijing and Tianjin cities. Besides, our findings also indicated that urban expansion was largely responsible for landscape patterns.The findings of this study potentially provide strategical insights into landscape planning around mega cities and sustainable coordinated urban-rural development.     

The validity of the monocentric city model in a polycentric age: US metropolitan areas in 1990, 2000 and 2010

In this article, we use local indicators of spatial association (LISA) and other spatial analysis techniques to analyze the distribution of centers with high employment density within metropolitan areas. We examine the 359 metropolitan areas across the United States at three points in time (1990, 2000, and 2010) to provide a spatio-temporal panoramic of urban spatial structure. Our analysis highlights three key findings. (1) The monocentric structure persists in a majority of metropolitan areas: 56.5% in 1990, 64.1% in 2000, and 57.7% in 2010. (2) The pattern of employment centers remains stable for most metropolitan areas: the number of centers remained the same for 74.9% of metropolitan areas between 1990 and 2000 and for 85.2% between 2000 and 2010. (3) Compared with monocentric metropolitan areas, polycentric metros are larger and more dense, with higher per-capita incomes and lower poverty rates.     

Declining Union Contract Coverage and Increasing Income Inequality in U.S. Metropolitan Areas

We focus on the association between the institutional factor of union contract coverage rates among workers and the variation in income inequality across a set of sixty-four metropolitan areas of the United States for the years 1990, 2000, and 2010. We use market variables of relative skills and relative education and demographic variables of race and gender as controls in our regression models. We also specify a set of models that substitute right-to-work status for union contract coverage rates. Our primary finding is that union contract coverage rates are temporally consistent and significant negative covariates of income inequality, as measured by Gini coefficients, across the metropolitan areas. Further, metropolitan areas in right-to-work states have consistently and significantly higher levels of inequality than expected given the control variable effects. Our interpretation of the primary finding is that issues of labor power and class play a clearly important role in contributing to income inequality in the set of metropolitan areas used in the analysis.     

LAND‐USE DYNAMICS BEYOND THE AMERICAN URBAN FRINGE*

ABSTRACT. A deficiency common to both the historical debates over loss of agricultural land and the current discussions of urbanization and sprawl is a limited understanding of land‐use dynamics beyond the urban fringe. Data aggregated at the county level poorly capture the fine‐grained pattern of land‐use change beyond the dynamic urban‐rural interface. Furthermore, current urban‐based definitions are poorly suited to delineate these areas, and low‐density, exurban land use is difficult to measure using existing land‐cover databases. Urbanization and the conversion of once‐agricultural or other natural resource lands to other uses has traditionally been tracked using urban areas, as delimited in the U.S. census. Urban densities are typically defined as areas with more than 1,000 people per square mile, or 1.6 people per acre (U.S. Census Bureau 2000). Assuming an average of 2.5 people per housing unit, this translates to roughly 0.7 units per acre, or approximately 1 unit per 1.6 acres. The analytical units used in the census, however, both overbound and underbound areas with urban densities. About one‐third of urban areas in 1990 comprised lower‐than‐urban housing density, thanks to overbounding. But, then, one‐third of locations that had urban‐level housing densities failed to be included in urban areas as a result of underbounding, which, if counted, would have constituted another 18 million acres of urban area. An increase over time of the average number of acres required per housing unit in exurban and higher‐density locations occurred in roughly one‐third of U.S. counties from 1960 to 1990 and persisted from 1990 to 2000. In 2000 roughly 38 million acres were settled at urban densities, and nearly ten times that much land was settled at rates from low, exurban density (as low as one house per 40 acres) to higher rates (up to one per 10 acres). This represents a continuing encroachment on land previously given over to other uses—habitat or agriculture. Practitioners of natural resource management need to recognize the ubiquity of exurban development and better incorporate the fine‐scale patterns of land use beyond the urban fringe.     

The impact of Hurricane Katrina on urban growth in Louisiana: an analysis using data mining and simulation approaches

ABSTRACT

Understanding human dynamics after a major disaster is important to the region’s sustainable development. This study utilized land cover data to examine how Hurricane Katrina has affected the urban growth pattern in the Mississippi Delta in Louisiana. The study analyzed land cover changes from non-urban to urban in three metropolitan areas, Baton Rouge, New Orleans-Metairie, and Hammond, for two time periods, pre-Katrina (2001–2006) and post-Katrina (2006–2010). The study first applied a focal filter to extract continuous urban areas from the scattered urban pixels in the original remote sensing images. Statistical analyses were applied to develop initial functions between urban growth probability and several driving factors. A genetic algorithm was then used to calibrate the transition function, and cellular automata simulation based on the transition function was conducted to evaluate future urban growth patterns with and without the impact of Hurricane Katrina. The results show that elevation has become a much more important factor after Hurricane Katrina, and urban growth has shifted to higher elevation regions. The elevation most probable for new urban growth increased from 10.84 to 11.90 meters. Moreover, simulated future urban growth in this region indicates a decentralized trend, with more growth occurring in more distant regions with higher elevation. In the New Orleans metropolitan area, urban growth will continue to spill across Lake Pontchartrain to the satellite towns that are more than 50 minutes away by driving from the city center.     

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-temporal change in urban agricultural land use efficiency from the perspective of agricultural multi-functionality: A case study of the Xi’an metropolitan zone

The excessive expansion of urbanized areas has resulted in haphazard land utilization, immoderate consumption of superior agricultural land and water resources, significant fragmentation of agricultural landscape, and gradual deterioration of the agro-ecological environment. Combined, these factors cause poor land use efficiency. Under these circumstances, comprehensively assessing land use efficiency for urban agriculture is a key issue in land use research. Currently, evaluation methods for agricultural land use efficiency narrowly concentrate on aspects of economic input and output. However, urban agro-ecosystems can provide diverse economic, social, and ecological services and functions. In particular, the social and ecological services and functions originating from agricultural land, which have a higher value than economic services, play a significant role in ensuring regional social, ecological, and environmental security. However, recent research has rarely taken these benefits into consideration. Therefore, land use value has been greatly underestimated, which has resulted in mishandled and poor land use policies. In this study, we apply Landsat imagery and social and economic statistical data for the Xi’an metropolitan zone (XMZ) to investigate agricultural multi-functionality. We develop an evaluation framework for urban agricultural land use efficiency and identify agro-ecosystem services and functions as important outputs from agricultural land. The land use efficiency of urban agriculture is then evaluated using ecosystem services models, providing a mechanism for assessing spatial-temporal changes in land use efficiency in the XMZ from 1999 to 2015. Four important conclusions are reached from this analysis. First, the rapid urbanization and agricultural transformation from traditional cereal cultivation to modern urban agriculture has resulted in steadily increasing costs, outputs, and land use efficiency of urban agriculture. The total output value increased 41% and land use efficiency per hectare increased by 33.13% on average. Second, the spatial patterns of comprehensive output and land use efficiency were dominated by economic outputs from agricultural land. Areas near cities, which are dominated by orchard and arable land, provide more economic functions. These areas support and regulate services due to the transformation from extensive cereal production to intensive modern urban agriculture; therefore, they have higher output value and land use efficiency. In contrast, areas distant from cities, towns, and high traffic roads, namely, remote rural areas, provide more support and regulating services, but have relatively lower economic function due to inaccessibility to urban markets and slow agricultural transformation. Therefore, these areas have lower output value and land use efficiency. The spatial change in agricultural output and land use efficiency in urban areas is strongly dependent on the degree of urbanization and agricultural transformation. Third, the total output value and land use efficiency of urban agriculture measured with our approach are much higher than evaluations using traditional methods. However, the spatial patterns measured using the two approaches are in agreement. The evaluation framework integrates ecological services and economic and social functions into a comprehensive output from agricultural land. This approach is more methodical and accurate for evaluating the comprehensive efficiency of land use based on quantities and spatial scale because they are at the pixel scale. Finally, the evaluation results have important implications for enhancing current agricultural subsidies and even implementing ecological payment policies in China. Most importantly, they can be directly applied to agricultural transformation regulations, decision- making, and guidance for rational land utilization.     

南京大都市区建设用地扩张特征与机理

作为全球城市化最快的地区之一,中国建设用地的扩张引起了广泛的关注。以长三角北翼中心城市南京为例,利用遥感、土地利用调查等数据研究大都市区建设用地扩张的过程、格局与机理。研究表明,1985-2007年南京市在工业化、城市化和国际化的推动下经济快速增长,引致了建设用地的扩张,年均增长率为3.14%。2001年后随着城市发展模式由单中心向多中心转换,建设用地呈加速扩展趋势。南京市建设用地扩展具有明显的沿长江和南北交通走廊轴向发展的特征。开发区和新城建设是南京市建设用地扩张的主要方式。区、县尺度的回归分析表明,人口增加、全球化是城镇工矿用地扩张的重要推手;经济的服务业化有利于土地集约利用,减少对用地的需求,这种影响在城区更大;在分权化竞争中,都市区政府具有更强的控制力。     

基于农业多功能视觉的都市农业用地效益时空变化研究——以西安都市圈为例（英文）

The excessive expansion of urbanized areas has resulted in haphazard land utilization, immoderate consumption of superior agricultural land and water resources, significant fragmentation of agricultural landscape, and gradual deterioration of the agro-ecological environment. Combined, these factors cause poor land use efficiency. Under these circumstances, comprehensively assessing land use efficiency for urban agriculture is a key issue in land use research. Currently, evaluation methods for agricultural land use efficiency narrowly concentrate on aspects of economic input and output. However, urban agro-ecosystems can provide diverse economic, social, and ecological services and functions. In particular, the social and ecological services and functions originating from agricultural land, which have a higher value than economic services, play a significant role in ensuring regional social, ecological, and environmental security. However, recent research has rarely taken these benefits into consideration. Therefore, land use value has been greatly underestimated, which has resulted in mishandled and poor land use policies. In this study, we apply Landsat imagery and social and economic statistical data for the Xi'an metropolitan zone(XMZ) to investigate agricultural multi-functionality. We develop an evaluation framework for urban agricultural land use efficiency and identify agro-ecosystem services and functions as important outputs from agricultural land. The land use efficiency of urban agriculture is then evaluated using ecosystem services models, providing a mechanism for assessing spatial-temporal changes in land use efficiency in the XMZ from 1999 to 2015. Four important conclusions are reached from this analysis. First, the rapid urbanization and agricultural transformation from traditional cereal cultivation to modern urban agriculture has resulted in steadily increasing costs, outputs, and land use efficiency of urban agriculture. The total output value increased 41% and land use efficiency per hectare increased by 33.13% on average. Second, the spatial patterns of comprehensive output and land use efficiency were dominated by economic outputs from agricultural land. Areas near cities, which are dominated by orchard and arable land, providemore economic functions. These areas support and regulate services due to the transformation from extensive cereal production to intensive modern urban agriculture; therefore, they have higher output value and land use efficiency. In contrast, areas distant from cities, towns, and high traffic roads, namely, remote rural areas, provide more support and regulating services, but have relatively lower economic function due to inaccessibility to urban markets and slow agricultural transformation. Therefore, these areas have lower output value and land use efficiency. The spatial change in agricultural output and land use efficiency in urban areas is strongly dependent on the degree of urbanization and agricultural transformation. Third, the total output value and land use efficiency of urban agriculture measured with our approach are much higher than evaluations using traditional methods. However, the spatial patterns measured using the two approaches are in agreement. The evaluation framework integrates ecological services and economic and social functions into a comprehensive output from agricultural land. This approach is more methodical and accurate for evaluating the comprehensive efficiency of land use based on quantities and spatial scale because they are at the pixel scale. Finally, the evaluation results have important implications for enhancing current agricultural subsidies and even implementing ecological payment policies in China. Most importantly, they can be directly applied to agricultural transformation regulations, decision-making, and guidance for rational land utilization.     

Spatial Variations of Single-Family Residential Water Consumption in Portland,Oregon

Although water demand theories identify price structures, technology, and individual behavior as determinants of water demand, limited theoretical or empirical evidence suggests a link between urban development patterns and water use. To assess the role of urban development patterns on water demand, we used GIS and statistical models to analyze single-family residential water consumption in the Portland, Oregon, metropolitan area. Our results show that residential water consumption per household at the census block group scale is best explained by average building size, followed by building density and building age, with low water consumption areas clustering together and typically located in high-density and older neighborhoods. Accounting for spatial dependence among residuals, explanatory variables explain up to 87% of variations in water consumption. Our results help to develop a water demand framework that incorporates existing factors with urban development policies to more effectively manage limited water and land resources.     

中国与美国大都市区城市内部土地覆盖结构时空差异

城市内部土地覆盖结构对城市生态服务功能和人居环境质量产生重要影响。中国与美国不同发展阶段城市不透水地表和绿地时空分布格局存在显著差异。本文基于Landsat TM/MSS影像获取1978、1990、2000、2010 年城市内部土地覆盖和不透水地表分类信息,监测并比较中国和美国六个特大城市扩展时空动态、土地覆盖结构差异及城市不同功能区特征。研究表明,在过去30 多年以来,中国城市以相对紧凑形态发展,美国城市较为离散;美国三大城市植被所占的比例是中国的2.21 倍;中国城市内部结构土地利用功能类型更加复杂,不透水地表密度更高,而美国城市CBD和居住区功能相对独立,特别居住区以镶嵌式低不透水地表和高绿地比例结构为主。     

全球气候变化背景下基于土地利用的人类活动对城市热环境变化归因分析——以京津冀城市群为例

近年来全球气候变化已经影响到人类生活的所有地区,气候系统变化的规模和现状是数千年来前所未有的。与此同时,中国城镇化进程显著加快,尤其以城市建设用地扩张主导的土地城镇化最为突出,导致城市热环境脆弱性加剧。已有研究探索了特定类型土地利用变化对于城市热环境的影响,但忽视了全球气候变化背景下自然气候和人类活动共同作用城市热环境变化的双重过程。因此,本研究提出一种基于土地利用类型的城市热环境变化贡献度算法,旨在厘清自然气候（表征为土地利用平均温度变化）和人类活动（表征为土地利用类型转变）对于区域热环境变化的单独贡献。本研究使用中分辨率成像光谱仪（Moderate-Resolution Imaging Spectroradiometer,MODIS）地表温度及发射率数据,定量计算2005—2020年四季和昼夜京津冀城市群各城市土地利用类型平均温度和面积变化对于城市热环境变化的分别贡献。该算法计算各城市四季和昼夜地表温度变化与MODIS LST产品误差在1 K以内。2005—2020年各城市地表平均温度大多数呈增长态势,其中冬季白天增温幅度最高。耕地、城市建设用地和农村居民点对城市热环境变化的贡献度较其他土地利用类型突出。京津冀城市群中各城市人类活动对城市热环境变化的单位贡献强度远高于自然气候（4.03~648.07倍）,而人类活动的贡献总量（-0.25~0.92 K）低于自然气候（-2.40~6.50 K）。研究结果对于京津冀城市群空间协同发展和适应及减缓气候变化等具有重要的科学意义和实践价值。     

北京大都市土地开发的乘数效应和增长模式研究

本依据1992－2000年北京地区2000多个土地开发项目统计资料，通过实证对城市土地空间开发的理论模式进行研究。结果表明，城市特定区域的土地开发，表现为乘数效应作用下的逻辑斯蒂增长。根据模型对各环线和扇面模拟的相关系数高达0．95以上。在此基础上，结合北京举办奥运会带来的巨大投资规模，预测北京大市土地开发的趋势。     

Comparative tempo‐spatial pattern analysis: CTSPA

A new method is illustrated for describing the characteristics of urban pattern changes over different time periods. This method employs vector geometry, paired centroids, shared boundary lines, and overlain polygons. Three new statistics are proposed for characterizing local polygon feature changes in quantity, shape, and size. These statistics are standardized, based on conventional theories from urban geography such as directional concentric zones and user‐designated corridors to document both regional and global patterns of land‐use change. This method is used to analyse land‐use changes in metropolitan Detroit between 1990 and 2000. The Detroit case study indicates that the CTSPA statistics are effective in describing urban spatial pattern changes and in characterizing the evolution of discrete urban landscapes over selected periods.     

Calibrating a neural network‐based urban change model for two metropolitan areas of the Upper Midwest of the United States

We parameterized neural net‐based models for the Detroit and Twin Cities metropolitan areas in the US and attempted to test whether they were transferable across both metropolitan areas. Three different types of models were developed. First, we trained and tested the neural nets within each region and compared them against observed change. Second, we used the training weights from one area and applied them to the other. Third, we selected a small subset (～1%) of the Twin Cities area where a lot of urban change occurred. Four model performance metrics are reported: (1) Kappa; (2) the scale which correct and paired omission/commission errors exceed 50%; (3) landscape pattern metrics; and (4) percentage of cells in agreement between model simulations. We found that the neural net model in most cases performed well on pattern but not location using Kappa. The model performed well only in one case where the neural net weights from one area were used to simulate the other. We suggest that landscape metrics are good to judge model performance of land use change models but that Kappa might not be reliable for situations where a small percentage of urban areas change.