【作者】 李杰；

【导师】 闫庆武； 李桂娥；

【作者基本信息】 中国矿业大学 ， 地图制图学与地理信息工程， 2024， 硕士

【摘要】 随着全球城市化进程持续深化,城市建成区的快速扩张引发了一系列问题。对城市建成区的时空演化分析及驱动力研究,不仅能在纵向揭示不同地区的经济政治中心在发展过程中结构的变化特征,而且能从横向上对比不同发展水平城市的建成区的差异,有利于为城市空间的优化发展提供帮助。运用地理信息与遥感相关理论知识构建城市建成区研究的理论与模型,有助于深化城市化过程与机理研究、完善城市空间结构演变研究的分析框架。选取具有典型性和代表性的31个省会城市作为研究区,引入面积阈值对传统的城市聚类算法(CCA,City Clustering Algorithm)进行了改进,并将其与多源数据融合指数法进行组合构成新的研究框架,进行了2013-2022年省会城市建成区的提取,并进行了提取结果的精度评定。采用二维自组织映射神经网络(Self-Organizing Map,SOM)和时空地理加权回归(Geographically and Temporally Weighted Regression,GTWR)等多个空间分析手段从多个维度对提取的省会城市建成区进行了时空演变及驱动机制的综合研究,并对不同城市的健康及可持续发展提出了针对性建议。本文得出以下主要结论:(1)基于改进的CCA算法提取的不同城市的建成区整体精度均良好,可扩展至不同类型城市建成区的提取。本文提取的建成区面积与实际建成区面积对比,结果的整体相对误差较小。以2018年数据为例,经与30m空间分辨率的中科院土地利用数据对比,得到Kappa系数、OA和F1 Score均值分别为0.648、0.907和0.681。与现有研究相比,在某些城市的建成区提取精度有所提升,说明引入面积阈值的CCA算法能够更好地识别不同类型城市的建成区,能够为城市规划和空间分析提供可靠的数据支撑。(2)东部、东北、中部和西部省会城市建成区发展具有显著差异。东部省会城市的城市化水平高,发展迅速,建成区扩张趋向高效、集约,形态复杂度高;中部省会城市在中部崛起战略下,新一线城市发展良好,建成区扩张速度加快,形态复杂度高;东北省会城市建成区扩张速度下降,形态发生变化;西部省会城市发展不均衡,部分城市扩张较快,形态相对简单。多数城市建成区重心迁移路径具有方向性,可能与功能优化、经济结构及发展战略相关。一些城市以单一方位扩张,另一些则以多方位扩张,因此,在规划和发展中需要综合考虑不同扩张模式的利弊,制定相应的策略。(3)不同因素对建成区扩张的影响存在时间和地域差异,并随时间波动变化。随着时间的推进,常住人口、固定资产投资总额、道路长度对建成区面积的增长主要起促进作用,GDP增长率、人均道路面积对建成区面积的增长主要起抑制作用。人口密度、人均GDP、第三产业占GDP比重、科学技术支出在不同地区对建成区的扩张有不同的影响机制。在城市规划中,应根据不同地区的特性制定相应的发展战略和政策导向。更多还原

【Abstract】 As global urbanization intensifies,the rapid expansion of urban built-up areas presents a host of challenges.Analyzing the spatial and temporal evolution of these areas and studying their driving forces can illuminate the economic and political center structures during development and facilitate horizontal comparisons among cities of varying developmental stages.This approach aids in optimizing urban spatial development.Leveraging theoretical knowledge in geographic information and remote sensing,constructing models to study urban built-up areas deepens our understanding of urbanization processes and mechanisms while enhancing analytical frameworks for evaluating urban spatial structure evolution.In this study,thirty-one provincial capital cities,chosen for their representativeness,serve as the study area.We enhance the traditional City Clustering Algorithm(CCA)by introducing an area threshold and integrate it with a multi-source data fusion index method to establish a novel research framework.We extract built-up areas of provincial capitals from 2013 to 2022 and evaluate the accuracy of our extraction results using rigorous assessment techniques.Furthermore,we comprehensively examine the spatial and temporal evolution and driving mechanisms of these built-up areas through a variety of spatial analytical tools such as two-dimensional Self-Organizing Map(SOM)and Geographically and Temporally Weighted Regression(GTWR).We rigorously evaluate the accuracy of our findings.This thesis provides a thorough investigation into the spatial and temporal evolution of provincial capital cities’ built-up areas,along with their driving mechanisms,from multiple dimensions.It offers targeted recommendations for promoting the health and sustainable development of diverse cities.The main conclusions drawn from this study include:(1)The overall accuracy of the built-up areas extracted using the enhanced CCA algorithm demonstrates good performance,suggesting its applicability across various city types.When comparing the extracted built-up areas with actual data,the relative error is minimal.For instance,utilizing 2018 data,the mean values of the Kappa coefficient,Overall Accuracy,and F1 Score are 0.648,0.907,and 0.681,respectively,when compared to the 30 m spatial resolution land use data from the Chinese Academy of Sciences.Notably,in comparison with previous studies,the accuracy of built-up area extraction in certain cities has improved,indicating the efficacy of the CCA algorithm with the introduction of an area threshold in distinguishing built-up areas across diverse urban landscapes.This underscores the algorithm’s potential to offer robust data support for urban planning and spatial analysis.(2)There exist notable disparities in the evolution of built-up areas among the capital cities spanning eastern,northeastern,central,and western provinces.Eastern provincial capitals exhibit a high level of urbanization characterized by rapid and efficient expansion of built-up areas,marked by their intensive development and intricate morphological complexity.In contrast,central provincial capitals,buoyed by the Central China Development Strategy,demonstrate robust development trends,particularly in the emergence of new first-tier cities,leading to accelerated expansion of built-up areas and heightened morphological complexity.Conversely,northeastern provincial capitals experience a slowdown in the pace of built-up area expansion alongside morphological shifts.In the western provinces,the development landscape is marked by imbalances,where certain capitals undergo rapid expansion characterized by relatively simplistic morphologies.Notably,the migration trajectory of the built-up area centers in most cities displays a directional pattern,potentially linked to functional optimization,economic structural adjustments,and development strategies.While some cities expand predominantly in a single direction,others exhibit expansion in multiple directions.Consequently,strategic planning and development initiatives must holistically consider the merits and demerits of various expansion modes to formulate tailored strategies.(3)The impact of various factors on the expansion of built-up areas exhibits temporal and geographic variability,subject to fluctuation over time.Over the course of advancement,factors such as resident population,total investment in fixed assets,and road infrastructure length emerge as primary drivers promoting built-up area growth.Conversely,the GDP growth rate and per capita road area assume significant roles in constraining such expansion.Furthermore,population density,per capita GDP,the tertiary industry’s share of GDP,and expenditure on science and technology exhibit distinct mechanisms of influence on built-up area expansion across different regions.In urban planning endeavors,it is imperative to formulate development strategies and policies tailored to the unique characteristics of each region.更多还原