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The effects of factor generalization scales on the reproduction of dynamic urban growth

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Geo-Spatial Information Science 2022年第3期25卷 457-475页

作者： Yongjiu Feng Peiqi Wu Xiaohua Tong Pengshuo Li Rong Wang Yilun Zhou Jiafeng Wang Jinyu Zhao College of Surveying&Geo-Informatics Tongji UniversityShanghaiChina The Shanghai Key Laboratory of Space Mapping and Remote Sensing for Planetary Exploration Tongji UniversityShanghaiChina

The production and selection of driving factors are essential to building a strong Cellular Automata(CA)model of dynamic urban growth simulation.A critical issue that should be addressed is how the spatial representation and the generalization scale of driving factors affect the CA modeling and the simulation *** is challenging to evaluate the effectiveness of the selected driving factors because they have no true *** explore the impacts of the generalization scales,we produced nine sets of driving factors at nine scales to calibrate the CA models based on the Particle Swarm Optimization(CAPSO)and applied them to simulate urban growth of Suzhou during *** results show that the driving factors at a smaller scale have much better performance in explaining urban growth simulations as inferred by the Explained Residual Deviance(ERD)of the Generalized Additive Models(GAMs).Specifically,the ERD declined from 51.9%to 45.9%as the factor scale became larger during 2000-2020,but there was a peak value(52.2%)at *** all simulations during 2000-2020,the CAPSO models with larger-scale factors have slightly lower overall accuracy and Figure-of-Merit(FOM),which respectively decreased by 3.1%and 4.4%as compared to the CA models with scale-free *** concluded that the driving factors at a smaller scale(200~400 m for point-like facilities and 7~14 m for line-like facilities)can build more accurate CA models to simulate urban growth patterns,and the optimal scale for factors can be identified using the *** study contributes to the methods of evaluating the effectiveness of driving factor production and reveals the impacts of spatial representation of factors on the CA modeling and simulation considering the factor generalization scales.

关键词： Cellular automata urban growth driving factors scale effects generalized additive model

To move or stay?A cellular automata model to predict urban growth in coastal regions amidst rising sea levels

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International Journal of Digital Earth 2021年第9期14卷 1213-1235页

作者： Siqin Wang Yan Liu Yongjiu Feng Zhenkun Lei School of Earth and Environmental Sciences The University of QueenslandSt LuciaAustralia Spatio-Temporal Analytics Research Laboratory(STAR Lab) The University of QueenslandSt LuciaAustralia College of Surveying and Geo-Informatics Tongji UniversityShanghaiPeople’s Republic of China College of Marine Sciences Shanghai Ocean UniversityShanghaiPeople’s Republic of China

Low-lying coastal cities are widely acknowledged as the most densely populated places of urban settlement;they are also more vulnerable to risks resulting from intensive land use and land cover change,human activities,global climate change,and the rising sea *** study aims to predict how urban growth is affected by sea level rise(SLR)in the Australian *** develop an urban cellular automata model incorporating urban planning policies as potential drivers or constraints of urban growth under different SLR scenarios and adaption *** on data capturing the socioeconomic and environmental factors in South East Queensland,Australia,our model is positioned to address one core research question:how does SLR affect future urban growth and human resettlement?Results show that urban growth in coastal regions varies depending on the extent to which the sea level rises and is affected by a combination of factors relating to urban planning and human adaptation *** study demonstrates the complexity of urban growth in coastal regions and the nuanced outcomes under different adaptation strategies in the context of rising sea levels.

关键词： Climate change Cellular automata Sea level rise urban growth Human settlement

Satellite remote sensing for urban growth assessment in Shaoxing City, Zhejiang Province

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Journal of Zhejiang University Science 2004年第9期5卷 1095-1101页

作者： RAMADANElnazir 冯学智程征 GIS＆RSLaboratory DepartmentofUrbanandResourcesSciencesNanjingUniversityNanjing210093China

urban growth represents specific response to economic, demographic and environmental conditions. Rapid urbanization and industrializations have resulted in sharp land cover changes. The present investigation was carried out from Shaoxing City to quantify satellite-derived estimates of urban growth using a three-epoch time series Landsat TM data for the years 1984, 1997 and ETM 2000. The methodology used was based on post classification comparison. The use of GIS allowed spatial analysis of the data derived from remotely sensed images. Results showed that the built-up area surrounding Shaoxing City has expanded at an annual average of 7 km2. Analysis of the classified map showed that the physical growth of urban area is upsetting the other land cover classes such as farming, water resources, etc. The study conclusion mainly emphasized the need for sustainable urban capacity.

关键词： Change detection Post classification urban growth Shaoxing

Remote Sensing Data and SLEUTH urban growth Model:As Decision Support Tools for urban Planning

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Chinese Geographical Science 2018年第2期28卷 274-286页

作者： SERASINGHE PATHIRANAGE Inoka Sandamali Lakshmi N.KANTAKUMAR SUNDARAMOORTHY Sivanantharajah Mahaweli Authority of Sri Lanka Colombo 10Sri Lanka Institute of Human Resource Advancement University of ColomboColombo 7Sri Lanka Institute of Environment Education and Research Bharati Vidyapeeth Deemed UniversityPune 411043India District Survey Office The Sri Lanka Survey DepartmentJaffna 40000Sri Lanka

Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions(GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the urban Development Authority(UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.

关键词： urban growth urban planning land use land cover SLEUTH model Cellular Automata (CA) remote sensing Sri Lanka

Ecosystem service of green infrastructure for adaptation to urban growth:function and configuration

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Ecosystem Health and Sustainability 2018年第5期4卷 20-31页

作者： Yun-Cai Wang Jia-Ke Shen Wei-Ning Xiang Department of Landscape Architecture Center for Ecophronetic Practice ResearchCollege of Architecture and Urban PlanningTongji UniversityShanghaiChina Department of Geography and Earth Sciences the University of North Carolina at CharlotteCharlotteNCUSA

Objectives:(1)to explore what kind of green infrastructure(GI)meets the demand for urban ecological security of rapid urbanization areas;(2)to figure out how to determine the specific function and configuration of GI from ecosystem service requirements of urban ecological ***:(1)Through the literature review,this article summarizes the function and structure evolution of GI in order to adapt to urban growth.(2)Standing on the imperfect ecological functions and unreasonable spatial configurations,this article builds up a conceptual model for the optimization of green infrastructure ecosystem services to meet the demand for the green infrastructure pattern needed by urban ***:The optimization framework consists of four central function modules and its regulating and controlling mechanisms,incuding:(1)Balancing supply and demand of GI's ecosystem service;(2)Measuring and evaluating GI's ecosystem services;(3)Elevating and optimizing GI's ecosystem service;(4)Building urban ecological security patterm with high efficiency of GI's ecosystem ***,this framework provides guidance for the planning and design of GI and the urban ecological security pattern building in rapid urbanization areas based on ba lancing supply and demand of GI's ecosystem ***:The conceptual model of Gl's ecosystem service optimization based on balan-cing supply and demand shows a new path to meet the needs of urban growth and build a city's ecological security pattern through upgrading and optimizing GI.

关键词： Green infrastructure ecosystem service urban growth balancing supply and demand optimization framework

urban growth, TRANSPORTATION SYSTEM AND COMMERCIALNETWORK OF BEIJING

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Journal of Geographical Sciences 1995年第3期5卷 15-31页

作者： Yang Wuyang(Department of Geography, Peking University, Beijing 100871)People’s Republic of China

In this afticle, three uopt problems on the developlnent and plabong of Beijing metropolis are expounded (1) Having analyzed the process of urbanlzation dunng 45 years, the autihor divides it into three Stages :city expansion, qrban sprawl and fonmation of centnpotal urban nngr. Then a rank-number-size law is pLif fotward to predict the development and allocation of satellite towns (2) Having looked back on the change of urban transpoftation nforork, the atlthor points out its merits and *** to the increases of traffic flow, improving measures for the urban road systems are demonstrated. (3) Having reviewed the llistory of commercial distnbution and referred to previous lnodels, the author roprds the spatial structure of business as a combined network from central place and idealized stnucture of lnetropolitan area. The trade and service orgaluzation in n1ain urban area and peripheral zone can be planned with defferent ways. The atlthor predicts a rational network of commerce and service of Beijing with a strong BCD Which is accepted by some trade authorities

关键词： urban growth central place theory transportation system,commercial network

urban growth Modeling Using Neural Network Simulation: A Case Study of Dongguan City, China

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Journal of Geographic Information System 2016年第3期8卷 317-328页

作者： Xinmin Zhang Graduate School of Life and Environmental Sciences University of Tsukuba Tsukuba Japan

Dongguan is an important industrial city, located in the Pearl River Delta, South China. Recently, Dongguan city experienced a rapid urban growth with the locational advantage by transforming from traditional agricultural region to modern manufacturing metropolis. The urban transformation became the usual change in China under the background of urbanization which belongs to one trend of globalization in the 21st century. This paper tries to analyze urban growth simulation based on remotely sensed data of previous years and the related physical and socio-economic factors and predict future urban growth in 2024. The study examined and compared the land use/cover (LUC) changes over time based on produced maps of 2004, 2009, and 2014. The results showed that water and forest area decreased since the past years. In contrast, the urban land increased from 2004 to 2014, and this increasing trend will continue to the future years through the urbanization process. Having understood the spatiotemporal trends of urban growth, the study simulated the urban growth of Dongguan city for 2024 using neural network simulation technique. Further, the figure of merit (FoM) of simulated map of 2014 map was 8.86%, which can be accepted in the simulation and used in the prediction process. Based on the consideration of water body and forest, the newly growth area is located in the west, northeast, and southeast regions of Dongguan city. The finding can help us to understand which areas are going to be considered in the future urban planning and policy by the local government.

关键词： urban growth Neural Network Simulation Dongguan City

Implications of urban growth on Domestic Water Consumption： A Case Study of Jorhat Town, India

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Journal of Earth Science and Engineering 2014年第12期4卷 736-748页

作者： Mayurakshi Bhuyan Baruah Research Scholar Department of Geography North-Eastern Hill University Shillong 793022 Meghalaya India

This paper tries to embraces the urban growth in Jorhat town and its implications on water consumption at household＇s level. urban growth is measured through the increase in the number of population and the aerial extent. It is a pathetic situation for Jorhat residents in case of domestic water consumption that due to rapid increase of population in the town, the existing water supply systems cannot cope with the current demand. So, the people of the town always struggle to collect water from other sources such as River Bhogdoi, ponds, dug well, water vendor etc., moreover, try to satisfy the limited daily household needs. The methodology adopted in this paper is involved on both primary and secondary data. The primary data has been collected through household survey pertains to 600 households from each of 19 municipal wards in Jorhat town in both pre and post monsoon seasons. To highlight the growth of population and population projection, the compound rate of growth method has been used and it is tried to link with the future water demand in Jorhat town,

关键词： urban growth Domestic Water Consumption Jorhat Town.

Simulation of urban expansion using geographical similarity transition rules and neighbourhood sizes

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Journal of Geographical Sciences 2024年第7期34卷 1394-1414页

作者： LI Yinqi AN Yue ZHOU Zhou REN Hui TAN Xuelan College of Resources Hunan Agricultural UniversityChangsha410128China College of Geographical Sciences Hunan Normal UniversityChangsha410081China

Most existing cellular automata(CA)models impose strict requirements on the number and spatial distribution of *** makes it a challenge to capture spatial heterogeneity in urban dynamics and meet the modeling needs of large and complex geographic *** paper presents a CA model based on geographically optimal similarity(GOS)transition rules and similarly sized neighborhoods(SSN).By comparing the similarity in geographical configuration between samples and predicted points,the model enables a comprehensive characterization of the driving mechanism behind urban expansion and its self-organizing *** helps to mitigate the impact of sample selection and assumptions about spatial stationarity on simulation *** performance of GOS-SSN-CA simulation was tested by taking the urban expansion in the Changsha-Zhuzhou-Xiangtan urban agglomeration in China as an *** results show that GOS can derive more accurate and reliable urban transition rules with fewer samples,thereby significantly reducing spatial prediction errors compared with logistic ***,SSN selects different neighborhood sizes to represent the difference between the local self-organizing range and surrounding cells,thus further improving the simulation accuracy and restricting urban expansion ***,GOS-SSN-CA effectively characterizes the geographical similarity of urban expansion,improves simulation accuracy while constraining the urban expansion form,and enhances the practical application value of CA.

关键词： urban growth cellular automata geographic similarity model optimization spatial nonstationarity