共查询到20条相似文献，搜索用时 15 毫秒
1.
《地理信息系统科学与遥感》2013,50(4):426-442
Based on remote sensing and GIS, this study models the spatial variations of urban growth patterns with a logistic geographically weighted regression (GWR) technique. Through a case study of Springfield, Missouri, the research employs both global and local logistic regression to model the probability of urban land expansion against a set of spatial and socioeconomic variables. The logistic GWR model significantly improves the global logistic regression model in three ways: (1) the local model has higher PCP (percentage correctly predicted) than the global model; (2) the local model has a smaller residual than the global model; and (3) residuals of the local model have less spatial dependence. More importantly, the local estimates of parameters enable us to investigate spatial variations in the influences of driving factors on urban growth. Based on parameter estimates of logistic GWR and using the inverse distance weighted (IDW) interpolation method, we generate a set of parameter surfaces to reveal the spatial variations of urban land expansion. The geographically weighted local analysis correctly reveals that urban growth in Springfield, Missouri is more a result of infrastructure construction, and an urban sprawl trend is observed from 1992 to 2005. 相似文献
2.
Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly. 相似文献
3.
Dimitrios Triantakonstantis Poulicos Prastacos Aikaterini Tsoukala 《Journal of the Indian Society of Remote Sensing》2014,42(3):601-610
Analysis of urban sprawl is an issue that has been continuously attracting attention in the planning and research community. Τhis paper presents the results of an analysis of the growth of the city of Rethymno during the 1997–2010 time period. Rethymno is a city in the island of Crete in Greece with population of about 35,000 people, in which developed land has expanded at a rate that is double the growth of the population during the study period. A qualitative analysis was first performed to identify growth patterns in the different parts of the city, how these are related to planning regulations and the extent of cohesiveness of the development. A logistic regression model was estimated using various variables influencing the expansion of the built up area. Variables such as slope, distance from main roads, distance from the University, distance from coastline, as well as variables describing the proximity to other developed areas were used as independent variables in the logistic regressions. Planning constraints with respect zoning were also considered. The accuracy/goodness of fit of the simulation results were also tested using Receiver Operating Characteristic (ROC) curve. The results revealed high (performance) accuracy, which can support the applicability of the proposed method in urban sprawl modeling. Once the equations were estimated they were applied using data from 2010 to identify future trends of urbanization. The methodology adopted in this study can result in a tool that can be of use to urban planning authorities in identifying areas of future urban growth and therefore, adopt zoning policies encouraging or discouraging growth in these areas according to the sustainability objectives of the local community. 相似文献
4.
Abubakr A.A. Al-sharif 《国际地球制图》2015,30(8):858-881
Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved. 相似文献
5.
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades. 相似文献
6.
Apostolos Lagarias 《国际地球制图》2015,30(9):1033-1051
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. 相似文献
7.
根据1957与1982年两个时期的地形冈并结合1995与2008年的遥感卫星影像提取城镇建设用地专题信息。利用ArcGIS建立广佛都市区城镇建设用地数据库．采用分形维度的计锋方法,对广佛都市区城市蔓延的情况进行测度和分析。结果表明广佛都市区三个发展阶段城镇建设用地面积增长速度并不均匀,具有加速发展的特点。四个测度年份的分形维数分别为1．6454,1．6285,1．5586和1．5270,均在1-2之间．分形维数呈递降趋势,总体下降了0．1184,城市发展模式由紧凑型逐渐向松散型演变,存在城市蔓延情况,而且城市发展模式以年均0．14％的速度从紧凑型向松散型演变。广佛都市区城市蔓延的地域分异较为明硅,具有较强的空间集聚性和中心向心件,广州和佛山毗邻地区以及中心城区是城市蔓延的活跃区和集中区,1982—1995年问研究区内蔓延速度比1995．2008年间要快。通过深入分析发现,经济快速发展、城市人口的持续增长、交通道路网络的建设是广佛都市区快速扩张和城市蔓延的基本动力因素之一,开发区土地扩张,进一步加剧了无序扩张和城市蔓延。 相似文献
8.
随着城市化进程的推进,城市建成区范围不断扩大,在此过程中也出现了诸多问题。为更好地了解城市发展规律,本文选取1992、1997、2002、2007、2012年5期的DMSP/OLS数据和2017、2019年2期的NPP-VIIRS两种夜间灯光影像作为数据源,采用统计数据比较法提取太原市建成区范围,通过对太原市建成区形态扩张指数的分析,得出城市扩张规律。研究结果表明:①太原市建成区从1992-2019年太原市建成区面积增长了249.73km2,扩大了2.7倍,且建成区增长的面积主要集中在太原市的东南部。②2002-2012年和2017-2019年进入加速型扩张模式,扩张的速度快;1992-2019年太原市重心偏移距离为5676.42m,平均偏移速度为202.73m/a,重心位置总体向东南方偏移。③太原城市扩张的驱动力主要是受经济发展因素、人口因素、交通因素和政策规划因素的影响。本文为太原城市规划和空间结构调整提供理论依据和数据支撑。 相似文献
9.
哈尔滨城市扩展特征及驱动力分析 总被引：1，自引：0，他引：1
利用两种夜间灯光数据作为数据源，通过提取哈尔滨市1992年、1997年、2002年、2007年、2012年和2017年6个年份的建成区范围，计算扩展速度、圆度、紧凑度和分形维数等指标，并对城市扩展的驱动力进行分析。结果显示：1992—2017年，哈尔滨市建成区形态特征变化较大，紧凑度减小。城市扩展的驱动力主要来自经济发展、人口增长和政策规划等方面。 相似文献
10.
基于CLUE-S模型的南京市土地利用变化模拟 总被引：3，自引：0，他引：3
本文以南京市为研究区,以南京市1986年的土地利用现状图为基础,分析研究区概况并根据数据的可获取性,选取13类土地利用变化驱动因素,利用逻辑斯蒂回归分析求解土地利用变化驱动因素作用系数矩阵。在此基础上运行CLUE-S模型,对南京市1996年的土地利用空间格局进行模拟。将模拟结果与南京市1996年土地利用现状图与进行对比,结果较为理想,模拟正确率达88.57%,KAPPA指数0.86。这说明CLUE-S模型具有成功模拟区域土地利用时空动态变化的能力,对土地利用预测、规划具有重要的指导作用。 相似文献
11.
Capturing the heterogeneity of urban growth in South Korea using a latent class regression model 
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下载免费PDF全文 This study aims to analyze the spatial patterns of urban growth in South Korea between 2000 and 2010. Fourteen suspected causative independent variables were selected and latent class regression (LCR) was used to analyze the relationship between dependent (urban growth) and independent (causative) variables. The goodness‐of‐fit was assessed by comparison to logistic regression (LR) analysis. The LR analysis produced consistent coefficients for each independent variable across the study area. In contrast, an LCR analysis, with a three‐class assumption, resulted in a different magnitude and directional effects of the coefficients for each class. The LCR analysis enabled the identification of both spatially homogeneous and heterogeneous areas. In addition, the LCR analysis performed better than the LR analysis with a lower Akaike information criterion and Bayesian information criterion value, and a higher receiver operating characteristic value. We conclude that LCR analysis should be used to establish causative “driving” factors for efficient urban growth planning and urban spatial policy. 相似文献
12.
城区边界和城区面积是城镇化的重要表征和扩展分析的基础。然而城区边界存在概念和提取标准不统一、精度较低、可比性较差等问题。为此,提出了基于高分辨率影像和地理信息资料辅助的城区半自动化提取方法,充分利用高分辨率影像上的城市景观特征、先验地理信息知识和一系列标准规则,以得到精度高、一致性强的数据。以中国337个地级以上城市为研究区,采用该方法得到了2000年、2005年、2010年、2016年4期城区边界成果,并开展了城区时空扩展及用地效率等相关分析。结果表明:①16年间城区扩展迅速,城区主要集中分布在东部和中部,东西部地区差异大;②城市用地效率与城镇化发展水平显著相关,城区扩展以外延型为主;③大多城市城区扩展超前于人口增长,少量城市城区扩展滞后于人口增长;④城区扩展以占用耕地为主。 相似文献
13.
以深圳海岸带为研究区,基于1996、2005、2011年遥感影像得到研究区土地利用历史数据,选取自然、社会统计数据作为驱动因素,利用CLUE-S模型分别从不同时间尺度和空间尺度对研究区2005、2011年的土地利用分布予以模拟,并对模拟结果分别从类别和景观水平予以精度评价。从类别水平角度,选择ROC曲线对各地类的Logistic回归拟合精度进行评价;从景观水平角度,选取Kappa指数对模拟效果予以评估,以验证所选驱动因子的合理性。结果表明:在研究区范围内,CLUE-S模型的类别精度随着空间分辨率的改变而有所差异,100 m分辨率为本研究模拟的最佳尺度,各地类的ROC值均高于0.7;随着模拟时间的缩短模拟精度有所增加;东海岸由于受到人类影响较小,模拟效果整体相对较好。总体而言,CLUE-S模型适用于研究区土地利用模拟,所选驱动力因子能够对研究区土地利用变化予以较好的解释。 相似文献
14.
Abstract Landsat Thematic Mapper (TM) data have been used to monitor land cover types and to estimate biophysical parameters. However, studies examining the spatial relationships between land cover change and biophysical parameters are generally lacking. With the integration of remote sensing and Geographic Information Systems (GIS), these relationships can be better explored. The research reported in this paper applies this integrated approach for detecting urban growth and assessing its impact on vegetative greenness in the Zhujiang Delta, China. Multi‐temporal Landsat TM data were utilized to map urban growth and to extract and identify changes in vegetative greenness. GIS analyses were conducted to examine the changing spatial patterns of urban growth and greenness change. Statistical analyses were then used to examine the impact of urban growth on vegetative greenness. The results revealed that there was a notably uneven urban growth pattern in the delta, and urban development had reduced the scaled Normalized Difference Vegetation Index (NDVI) value by 30% in the urbanized area. 相似文献
15.
Mohamed Al-shalabi Biswajeet Pradhan Lawal Billa Shattri Mansor Omar F. Althuwaynee 《Journal of the Indian Society of Remote Sensing》2013,41(2):405-416
Sana’a the metropolitan capital of Yemen, has experienced rapid spatial growth and uncontrolled development for decades. In the absence of a means to forecast and predict urban growth trends, planning and urban policy decisions have been found wanting. In this study the SLEUTH (Slope, landuse, exclusion, urban extent, transportation and hillshade) model which has been widely and successfully applied in developed countries, has been applied to predict the spatial urban sprawl pattern from 2004–2020 in Sana’a. This was to provide the necessary forecast for better planning and decision making. The model performed well as per the calibration coefficient values. The results showed that there will a 29 % increase in spatial urban sprawl growth during the modeling period. Growth of the sprawl will be mainly at the edges of the urban boundary, there will also be a wide area of scattered urban clusters. Factors that will have major influence on spatial expansion of the city will be diffusion, natural and internal growth, slope (that will hinder spread) and transportation (along which most of the urban sprawl will occur). The study also provides an insight into how the SLEUTH model performs in a poorly planned urban environment as compared to the planned and controlled environment where it has been applied. 相似文献
16.
Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules 总被引：2，自引：0，他引：2
The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions. 相似文献
17.
Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey 总被引：3，自引：0，他引：3
Olena Dubovyk Richard SliuzasJohannes Flacke 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(2):235-246
In less developed countries, the recent high rates of urban expansion are often associated with the emergence of informal settlements that may exaggerate social and environmental problems and impede sustainable development. An enhanced understanding of informal development may, therefore, be a key for future success in its effective management. This paper explores the possibilities offered by progress in Geo-Information Science and spatial modelling to improve understanding of informal settlement development through comprehensive spatio-temporal analyses. First, it investigates spatial and temporal patterns of the growth of the informal settlements in Sancaktepe district of Istanbul between 1990 and 2005. Second, using a logistic regression model, an analysis of the driving forces of informal development and prediction of probable locations of new informal settlements are performed. A list of spatial factors that are correlated to informal development is compiled and used to build six logistic regression models for different time steps between 1990 and 2005. Population density, slope, and proportion of informal settlements in the neighbourhood were found to be the main predictors influencing the spatial development of informal settlements during the study period. The performance of the models is evaluated and validated to identify those which best explain the informal development in the study area. As a result, three models built for 1990-1995 and 1995-2000 were selected to generate probability maps of informal settlement development, showing the likelihood for each location to be informally developed in the future. These results can be used as a basis for the evaluation of the process of informal development in other parts of Istanbul, as well as in other cities and countries. At the same time, the technique may serve as a decision-making tool for urban planners and policy makers. 相似文献
18.
以河南省为研究区,利用2000—2018年夜间灯光数据、NDVI数据和VANUI数据提取城市建成区.在建成区面积和灯光强度两个方面的变化进行论述,利用景观指数对河南省城市景观进行定量分析,采用主成分分析法对河南省建成区扩张驱动力进行分析.结果表明,河南省建成区面积从1937 km2增加到5155 km2;灯光强度从75... 相似文献
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城市空间结构及其扩展的模拟是城市科学管理与规划的重要前提,本文基于极限学习机提出了顾及不同非城市用地转化为城市用地差异与强度的城市扩展元胞自动机模型（ELM-CA）。模型验证表明：①ELM-CA模型的模拟精度达到70.30%,相比于逻辑回归和神经网络分别提高了2.21%和1.54%,FoM系数分别提高了0.025 9和0.017 9,Kappa系数分别提高了0.024 7和0.016 9,且Moran I指数接近于实际值,说明极限学习机模型较逻辑回归和神经网络能更有效模拟城市扩展的空间形态及其变化;②ELM模型的训练时间仅为神经网络的1/3左右,体现了ELM学习速度的优势;③在小样本情况下,逻辑回归和神经网络都受到明显的影响,而极限学习机还能保持良好的性能,这个特点使其在样本难以获取的情况下具有明显的优势。两个时相的城市扩展模拟与真实数据的比较表明：基于极限学习机的城市扩展元胞自动机模型（ELM-CA）,简化了CA模型的复杂度,并在小样本情况下能有效提高模拟精度,适合于复杂土地利用条件下城市扩展模拟与预测。 相似文献