摘要
分析长时序城市扩张动态变化,研究城市扩张与社会经济发展协调程度的有效评价,对于推进粤港澳区域经济社会文化发展,保护耕地资源和生态环境具有十分重要的意义。基于多源遥感数据,采用支持向量机自动分类方法,提取了1979~2017年间广州市近40年的城市建设用地信息,探究城市扩张进程,并结合地理国情普查成果资料,实现城市扩张与社会经济发展协调程度的分析评价。结果表明:①1979~2017年间,广州市建设用地面积整体处于快速增长状态,其主要占用的土地利用类型是耕地、园地、林地和水域;②新增建设用地多以功能单一的开发区、工业园区和住宅区为主,并与人口密度、人口城市化率保持协调的增长趋势。③地理国情普查成果的分类体系更精细、分类结果更准确,需要对其进行常态化监测。
It is of great significance to analyze the dynamic changes of long-term urban expansion and discuss the evaluation of the coordination degree between urban expansion and socio-economic development for promoting economic,social and cultural development in Guangdong-Hong Kong-Macao Greater Bay Area and protecting cultivated land resource and ecological environment.In this paper,based on multi-source remote sensing data,Support Vector Machine classification is used to extract the urban construction land information of Guangzhou in the past 40 years from 1979 to 2017 in order to investigate the process of urban expansion.Then,combined with the results of national geographic conditions monitoring,the analysis and evaluation of the degree of coordination have been conducted.The results indicate that:① from 1979 to 2017,the area of construction land in Guangzhou is in a rapid growth state,and the main types of land use are cultivated land,garden land,woodland and water area;② the newly added construction land mainly consists of single-function development zones,industrial parks and residential areas,and is related to population density and population.The urbanization rate keeps a coordinated growth trend.③ the classification system of national geographic conditions monitoring is more precise and the classification results are more accurate,and it needs to be monitored regularly.
作者
金兵兵
王梓璇
刘洋
孟媛
吴子为
JIN Bingbing;WANG Zixuan;LIU Yang;MENG Yuan;WU Ziwei(Guangzhou Urban Planning&Design Survey Research Iinstitute,Guangzhou 510000,China;College of Geography and Environment,Shandong Normal University,Jinan 250358,China)
出处
《地理信息世界》
2019年第6期123-128,共6页
Geomatics World
关键词
多源数据
城市扩张
动态监测
评价分析
multi-source data
urban expansion
dynamic monitoring
evaluation and analysis