Evaluation of Urban Expansion in Chongqing City based on the Nighttime Light Data

Urbanization is an important embodiment of regional economic development.Its progress reflects the level of economic development in the region.Since Chongqing being directly under the Central Government in 1997,it has enjoyed rapid economic growth and rapid urbanization.Looking for an intuitive and efficient method of urbanization is of great practical significance to correctly grasp the achievements of urbanization in Chongqing from the overall situation.Through the comparison of statistical data on night lighting data,we can extract the built-up area of Chongqing year after year.The city gravity model is based on the results.A night light index is established and used to calculate the speed of urban expansion.The result indicates that the urban distributions in Chongqing is spatially distributed and expanded in all directions.There are great differences between urban areas and rural areas and urban area urbanization level is higher.The city gravity gradually shifted from Yuzhong district to Yubei district.The speed of city expansion maintains high.Our study can afford refers for the planning and construction of the Chongqing city.     

Comparison of landscape patterns between metropolises and small-sized cities: a gradient analysis with changing grain size in Shanghai and Zhangjiagang,China

Quantifying the urban landscape pattern and its change is fundamental for monitoring and assessing the ecological and socio-economic consequences of urbanization. Using Indian Remote Sensing Panchromatic (IRS-PAN) imagery of 2002 and combining gradient analysis with landscape metrics, we compared the landscape patterns between metropolises and small-sized cities with increasing grain size. Landscape metrics were computed along a 51?×?9 km transect cutting across Shanghai and a 16?×?2 km transect cutting across Zhangjiagang with a moving window. The results showed that fragmentation indices (patch density (PD), total edge (TE), landscape division (LD)) in land use transects of the two cities had many similarities, indicating the common characteristics of urbanization in different-sized cities. There were, however, some striking dissimilarities between the two cities, which did not support the hypothesis that PD increases exponentially along a landscape modification gradient. These differences may have three explanations: the proportion of urban roads area, the width of urban roads and land use change in suburban and rural areas. The proportion of urban road area and the width of urban roads, which should be considered in future research, are two main factors that have been identified to influence the landscape pattern analysis. In younger and smaller cities, spatial competition between local interest groups and imperfect land managerial systems result in an increase in fragmentation in the suburbs, and policymakers should pay more attention to future city planning and management. A bridge linking the urbanization landscape pattern and the process of urban fragmentation will be a key to urban landscape studies and planning.     

Study of Urban Expansion and Driving Factors in Xi’an City based on Nighttime Light Data

The dynamic monitoring of urban expansion information is of great significance to understand the social and economic activities of cities and the implementation and feedback of urban planning.Using DMSP / OLS night-time light image as data source,the urban expansion data were corrected and extracted by using rational function model and threshold dichotomy.By using the light index,urban spatial expansion rate and intensity index and the index of center of gravity migration,The results show that the urban built-up area in Xi’an has expanded 2.2 times from 148 km² in 1993 to 473 km² in 2013.The direction of urban expansion expands from southwest to south and north,and the spatial expansion mode also increases from the early stage The single-core concentric expansion mode gradually transformed into a multi-level nuclear growth expansion mode;thus using gray relational analysis to analyze the socio-economic indicators of the suburbs in Xi’an in 2008~2013 (Weiyang district,Yanta district,Baqiao district and Chang’an district) It is confirmed that secondary industry,population density,tertiary industry and fixed assets of the whole society are the main driving factors of urban expansion in four districts respectively.     

Spatio-temporal pattern of urban land cover evolvement with urban renewal and expansion in Shanghai based on mixed-pixel classification for remote sensing imagery

Research into pixel unmixing in remote sensing imagery led to the development of soft classification methods. In this article, we propose a possibilistic c repulsive medoids (PCRMdd) clustering algorithm which attempts to find c repulsive medoids as a minimal solution of a particular objective function. The PCRMdd algorithm is applied to predict the proportion of each land use class within a single pixel, and generate a set of endmember fraction images. The clustering results obtained on multi-temporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+) images of Shanghai city in China reveal the spatio-temporal pattern of Shanghai land use evolvement and urban land spatial sprawl in course of urbanization from 1989 to 2002. The spatial pattern of land use transformation with urban renewal and expansion indicates the urban land use structure is gradually optimized during vigorous urban renewal and large-scale development of Pudong area, which will have an active influence on improving urban space landscape and enhancing the quality of the ecological environment. In addition, accuracy analysis demonstrates that PCRMdd represents a robust and effective tool for mixed-pixel classification on remote sensing imagery to obtain reliable soft classification results and endmember spectral information in a noisy environment.     

基于GIS的西安市城镇建设用地扩展研究

基于1988年TM影像、2002年ETM影像和2007年TM影像提取了西安市主城区和远郊区城镇建设用地信息,利用GIS技术对三期城镇建设用地进行了叠加得到西安市城镇扩展数据。利用主要道路交通图和行政边界图对扩展数据进行裁切,得到了西安市绕城高速内和远郊区的城镇扩展信息。运用扩展强度指数、城镇建设用地相对变化率和分形维数等模型对西安市的城镇扩展进行了分析研究。研究结果表明,研究区内的城镇建设用地面积从1988年的151 796 493.8 m2增加到2007年的365 180 608.0 m2,总体扩展了2.4倍。其中主城区的扩展主要集中在二环与绕城高速之间,二环内的城镇建设用地面积扩展速度相对较慢;西安市的3个远郊区中长安区扩展倍数最大,在1988~2007年扩展了7.39倍,其次为临潼区和阎良区;1988~2002年西安市的主城区和远郊区的分形维数都呈增加的趋势,城市边缘形态趋于复杂,而2002~2007年分形维数呈减少的趋势。西安市远郊区的城镇建设用地相对变化率高于主城区,未来城市发展的格局逐渐呈现为主城区城镇扩展速度的相对放缓和远郊区的规模不断增大的趋势。     

基于高分辨率遥感影像的城市建筑容积率估算方法研究——以上海市中心城区为例

在总结目前常用的建筑容积率估算方法基础上，以高分辨率遥感影像为数据基础，提出了一种新的、适用于大范围建筑容积率估算的方法——阴影面积法。以上海市中心城区为例，详细阐述了阴影面积法在图像处理软件及GIS技术支撑下的实施方案。对估算中可能产生的问题以及估算精度进行了分析。实验表明：阴影面积法对大都市区的建筑容积率估算具有速度快、效率高的特点，基本能够满足中尺度大都市空间建设动态监测的需要。     

IBI and CA Model based Extraction of Urban Built\|up Areaand Its Application：A Case Study in Shanghai

At present,the automatic extraction of urban built\|up area is still a problem.Taking Shanghai city as an example,this research uses the binary image,which was derived from an IBI(index\|based built\|up index)image,as the geographical cellular automaton initial input data.This was then imported to the extended cellular automata model for further processing.After a series of processing such as thresholding,corrosion and connectivity test,the urban built\|up area was simulated and can be extracted.Based on this method,the urban built\|up area of Shanghai in five different years between 1987 and 2015 was extracted using multi\|temporal Landsat images of Shanghai.In addition,the urban growth intensity index,the concentric buffers analysis and radar chart analysis were calculated and used to analysis spatiotemporal pattern of Shanghai urban expansion in the 28 study years.The result shows that the built\|up area of Shanghai was expanded from 195 km² in 1987 to 1759 km² in 2015,which is eight times as large as that in 1987.In the period between 1987 and 2002,the urban built\|up area expanded mainly along the North\|South axis of the Huangpu River.However,after 2002 the expansion rate was increased more quickly,and the direction of the expansion was shifted to an east to west direction.Generally speaking,Shanghai has experienced a rapid urban expansion in the recent three decades.     

基于GIS的玛纳斯河灌区信息系统设计与应用

为进一步提高水资源利用的效率和灌区管理水平，本文针对玛纳斯灌区的实际情况，提出空间信息与灌区业务管理信息有机融合的理念，依据业务管理需求，设计了灌区信息系统的体系结构并定义了系统功能。在对灌区的量测水方法进行研究的基础上，玛纳斯灌区信息系统实现了灌区信息管理中的监测监控、量水测水、配水调度、水费计收以及防汛和工程运行管理等业务工作的自动化和智能化。     

封闭型小区交通开放对城市交通的影响

随着交通需求的增加,城市交通问题日益严重,能否通过开放现有封闭型小区的道路以缓解城市交通拥堵是一个值得研究的问题.本文针对这一问题,建立了基于最短路的交通分流线性规划网络模型,提出了交通量改善因子、路段饱和度均值以及路段饱和度标准差等三个评价指标,以评价和对比封闭性小区开放前后的交通量与道路占用程度,从而反映了封闭性小区的开放对城市交通的具体影响.本文对两种不同的交通网络及交通流量数据进行了仿真与模型求解,结果表明：尽管小区开放后路网密度提高,有可能使得总交通负荷降低,但并非任何小区开放均能缓解城市交通拥堵.小区面积、位置、外部及内部道路状况等诸多因素都能影响路网的交通状态,所以,是否开放封闭型小区,需要用针对具体的小区与周边道路状况进行评估后再进行决策.     

长三角城市群城市扩张区环境质量变化遥感评价

加强城市动态扩张与环境质量变化监测对促进长三角城市群高质量一体化协同发展具有重要意义。基于DMSP/OLS夜间灯光数据、多源环境遥感数据等,运用趋势线分析、综合评价指数（Comprehensive Evaluation Index,CEI）构建等方法,对长三角城市群2001~2013年的城市扩张模式、扩张区内环境质量变化特征及二者的协调性情况进行分析。结果表明：①46.24%的城市显著扩张,上海—苏锡常城市化水平和一体化程度最高,其次为环杭州湾城市群和沿江发展带,此外未形成多区域规模化的城市高速扩张模式,经济总量、对外开放程度和用电水平是长三角城市高速扩张的主要驱动因素;②46.35%的显著扩张区环境逐步恶化,集中在江苏省和安徽省,环境恶化型集聚在合肥主城区周围,浙江省城市环境最优,上海市基本未变,多数城市环境变化主要由PM2.5增长所致;③城市扩张与环境变化叠加结果可反映区域城市发展与生态环境建设的协调程度。上海市嘉定区、浦东新区和崇明岛,苏锡常及沿江地区协调性较弱,浙江省城市的“渐变”分布模式体现其高协调性,合肥市城区表现为环境质量远落后于城市化进程的双系统非协调发展状态。谷歌影像定位结果表明结合DMSP/OLS与CEI可有效检测出区域内由人类活动所产生的环境破坏型地表覆盖类型变化情况。该研究成果可揭示区域可持续发展状况,对长三角双系统动态发展协调性的空间转移研究具有指示作用。     

城市热岛效应地表通量空间分布研究

城市化进程的加快促使更多大中城市的产生以及城市面积的扩展,导致更加严重的城市热岛现象。为了更加深入理解城市热岛效应产生根源,以西安市城区为例采用美国陆地卫星遥感数据反演或估算地表温度、植被指数以及地表通量等变量,不仅采用传统的地表温度参数理解城市热岛现象,还着重分析城市建成区和郊区的地表通量空间分布格局及其与地表温度的关系。研究发现西安城市建成区与郊区之间热环境存在显著的差异,地表温度不仅与植被覆盖状况具有密切的关系,还与地表潜热通量和实际蒸散发变量存在显著的反相关关系。详细分析表明拥有众多工厂企业的西安市莲湖区热岛效应尤为显著,而位于市中心的新城区次之,具有较大面积郊区的灞桥区热岛效应并不明显。因此城市绿地不仅影响城市建成区的地表温度空间分布,还对地表通量以及实际蒸散发的空间格局产生重要的影响,在调节城市热岛效应方面具有重要的作用。
     

Fine spatial resolution residential land-use data for small-area population mapping: a case study in Riyadh,Saudi Arabia

Rapid growth in the world’s urban population presents many challenges to planning and service provision. Conventional sources of population data often fail to provide spatially and temporally detailed information on changing urban populations. While downscaling methods have helped bridge this gap, use of fine spatial resolution data coupled with object-based image analysis (OBIA) methods is relatively novel, and few studies exist outside the western, developed world. This article presents a study in Riyadh, Saudi Arabia, in which population distribution estimates were obtained by downscaling using detailed residential land-use classes derived from the application of OBIA to fine spatial resolution remotely sensed imagery. To assess the utility of these data for population downscaling, three statistical regression models (using built area, residential built area, and detailed residential built area) and two dasymetric areal interpolation models (using residential built area and detailed residential built area) were applied to downscale the density of dwelling units, prior to estimating the population distribution through a simple transform. The research suggests that, for regression, the proportion of residential land use (Model 2) increased the accuracy over built area proportion (Model 1), and, in a multivariate extension, the proportions of six separate residential land-use classes (Model 3) increased the accuracy further, thereby demonstrating the value of the fine spatial resolution imagery. For example, the actual number of dwelling units was 7771 and the estimated numbers of dwelling units of Models 1 and 3 were 10,598 and 8759, respectively. Moreover, the root mean square error (RMSE) was 5.9 for Model 1 and 2.6 for Model 3. Additionally, six-class dasymetric mapping was evaluated in comparison to the conventional binary dasymetric mapping approach. The six-class dasymetric mapping approach was found to be slightly more accurate than binary dasymetric mapping.     

Exploring the tidal effect of urban business district with large-scale human mobility data

Business districts are urban areas that have various functions for gathering people, such as work, consumption, leisure and entertainment. Due to the dynamic nature of business activities, there exists significant tidal effect on the boundary and functionality of business districts. Indeed, effectively analyzing the tidal patterns of business districts can benefit the economic and social development of a city. However, with the implicit and complex nature of business district evolution, it is non-trivial for existing works to support the fine-grained and timely analysis on the tidal effect of business districts. To this end, we propose a data-driven and multi-dimensional framework for dynamic business district analysis. Specifically, we use the large-scale human trajectory data in urban areas to dynamically detect and forecast the boundary changes of business districts in different time periods. Then, we detect and forecast the functional changes in business districts. Experimental results on real-world trajectory data clearly demonstrate the effectiveness of our framework on detecting and predicting the boundary and functionality change of business districts. Moreover, the analysis on practical business districts shows that our method can discover meaningful patterns and provide interesting insights into the dynamics of business districts. For example, the major functions of business districts will significantly change in different time periods in a day and the rate and magnitude of boundaries varies with the functional distribution of business districts.     

Spatialization of China’s Population Data based on Multi-source Data

The population data is usually calculated by administrative districts. When comprehensive analysis is carried out with other spatial data, there are often many problems such as different scales. The spatial data of population data is the process of exploring the spatial distribution of population. The final result can be other spatial correlation research. It lays the foundation and can also be directly applied to disaster impact assessment and other fields, which has important academic significance and application value. The population spatialization model is based on the spatial relationship between population and land use and traffic road network data. The population is divided into urban population and rural population. The land use type is empowered by the relative weight method, and the traffic network data is used to correct it. Spatial distribution of rural population; analysis of different ways of affecting different levels of traffic road network data, comprehensive distribution of urban population, and finally through the planning and other methods to superimpose and integrate different types of data. The results of population data spatialization results show that China's population is very sensitive to altitude and topography. Low-altitude plains and terraces only account for 16.49% of China's land area, while the population living on it accounts for 54.88% of the total population. On the contrary, China's mountains The proportion of hills is 55.78%, but only 22.11% of the population is distributed. The eastern population is concentrated in the Huanghuaihai area, the Sichuan Basin, the Yangtze River small and medium-sized tourist, and the Northeast Plain. The urban population in China presents a typical “point-axis” distribution. The distribution along the main traffic lines is more prominent.     

基于多源地理大数据的城市空间结构研究

以东莞市主城区为研究区,利用夜光遥感数据、POI数据与手机定位强度数据,采用核密度分析、数据格网化与双因素组合制图方法,获得3种数据空间耦合相同或相异区域,并比较其与城市空间结构的关系.研究表明,3种数据的空间分布趋势总体一致,部分区域出现空间耦合相异:①受交通、功能区与夜光遥感数据的"溢出"效应等因素影响,城市道路、...     

A multi-scale approach to urban thermal analysis

An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater assessment of the overall urban thermal pattern, including an analysis of the thermal properties of individual land covers, is needed. This study examines the surface thermal pattern by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal and Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis.Results show that a ground-level heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for comparison with more coarse spatial resolution studies.     

多源数据融合的中国人口数据空间化研究

人口数据通常是以行政区为单元进行统计,在与其他空间数据进行综合分析时往往存在尺度不一等诸多问题。人口数据空间化研究是探究人口空间分布规律的过程,其最终成果可为人口分布与其他数据的空间关联研究奠定基础,同时也可直接应用于灾害影响评估等领域,具有重要的学术意义和应用价值。基于人口分布和土地覆盖、交通路网数据的空间关系构建人口空间化模型,将人口划分为城镇人口和农村人口,通过相关权重法（Relative Weight）对土地覆盖类型赋权,利用交通路网数据修正,对农村人口进行空间展布;分析不同等级交通路网数据影响方式的不同,对城镇人口进行展布,最后通过规划求解等方法将不同类型数据叠加融合。人口数据空间化结果表明：我国人口分布对海拔地形十分敏感,低海拔平原和台地面积仅占我国国土面积的16.49%,而生活在其上的人口却占总人口的54.88%,相反,我国山地丘陵面积占比为55.78%,但是仅分布22.11%的人口;东部人口集中于黄淮海地区、四川盆地、长江中小游以及东北平原等地;中国城镇人口呈现典型的“点轴”分布特点,沿主要交通线的集中分布比较明显。     

Evaluation method of urban land population carrying capacity based on GIS—A case of Shanghai,China

Although research on population carrying capacity has made significant progress, research on urban carrying capacity still has a weak theoretical basis and uses, imperfect regulation mechanisms and estimation methods. This study proposes a new method for evaluating urban population carrying capacity based on spatial analysis with GIS, which utilizes spatial classification and spatial grading of land use. The results demonstrate that urban construction and industrial development subspaces have most of the population, accounting for about 86.4% of the total population carrying capacity, across 40.7% of the total land area. Therefore, urban construction and industrial development subspaces are the centers of the population concentration, industrial agglomeration and wealth concentration in the Shanghai metropolis. The agricultural production and ecological protection subspaces, as noncommercial and ecological conservation areas of the metropolis, should not carry too much industrial development or added-value activities. In addition, under the current conditions of socio-economic and technological development in China, the gross population carrying capacity of Shanghai is estimated to be about 27.1732–30.3308 million persons, based on 2009 data. The actual population of Shanghai was 22.1028 million persons in 2009; thus, the population can continue to grow before reaching the population carrying capacity. The estimation in this paper takes into account both the internal disparities in carrying capacity of heterogeneous land spaces and composite factors such as natural resources, the environment, economic resources and social resources. Consequently, this method not only addresses defects in the existing research and estimation methods but also improves the credibility of the estimate.