基于元胞自动机的Sleuth模型的城市转型建模

M. Chandan, H. Bharath
{"title":"基于元胞自动机的Sleuth模型的城市转型建模","authors":"M. Chandan, H. Bharath","doi":"10.1109/SSCI.2018.8628940","DOIUrl":null,"url":null,"abstract":"Changes in urban dynamics has direct linkages between human beings and its surroundings. Present decade has seen tremendous alterations in the built environment and therefore its negative effect on natural ecosystem. This paper attempts to assess land use change scenario and urban growth prediction for historical capital of central India, Bhopal. Land use analysis performed using maximum likelihood classifier revealed the immediate attention required for growing urban trends. A steep increase in urban areas of 4.90% to 8.67% was observed within a span of seven years for the present decade. In order to understand future urban growth in the city, we employed Cellular Automata based Sleuth model, by testing the datasets in a three-stage simulation procedure: test, calibration and prediction. Bhopal city is currently undergoing transformation from rural urban scenario and therefore facing growth pressure and due to various growth sectors including housing, transport and industrial sector. By urban pattern analysis indicates that unplanned urban growth. Considering business as usual scenario, input layers were carefully selected for the model by considering city development plans and delineating waterbodies etc., Output from the SLEUTH analysis suggest an alarming rate of increase in urban area of 779 km2 from the year 2017 to 2026. Results help planners and government authorities to visualize, strengthen existing policy measures to build future cities in alignment with sustainable goals and promising the community with pristine environment.","PeriodicalId":235735,"journal":{"name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modelling Urban transition using Cellular Automata based Sleuth modelling\",\"authors\":\"M. Chandan, H. Bharath\",\"doi\":\"10.1109/SSCI.2018.8628940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Changes in urban dynamics has direct linkages between human beings and its surroundings. Present decade has seen tremendous alterations in the built environment and therefore its negative effect on natural ecosystem. This paper attempts to assess land use change scenario and urban growth prediction for historical capital of central India, Bhopal. Land use analysis performed using maximum likelihood classifier revealed the immediate attention required for growing urban trends. A steep increase in urban areas of 4.90% to 8.67% was observed within a span of seven years for the present decade. In order to understand future urban growth in the city, we employed Cellular Automata based Sleuth model, by testing the datasets in a three-stage simulation procedure: test, calibration and prediction. Bhopal city is currently undergoing transformation from rural urban scenario and therefore facing growth pressure and due to various growth sectors including housing, transport and industrial sector. By urban pattern analysis indicates that unplanned urban growth. Considering business as usual scenario, input layers were carefully selected for the model by considering city development plans and delineating waterbodies etc., Output from the SLEUTH analysis suggest an alarming rate of increase in urban area of 779 km2 from the year 2017 to 2026. Results help planners and government authorities to visualize, strengthen existing policy measures to build future cities in alignment with sustainable goals and promising the community with pristine environment.\",\"PeriodicalId\":235735,\"journal\":{\"name\":\"2018 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSCI.2018.8628940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI.2018.8628940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

城市动态的变化与人类及其周围环境有着直接的联系。近十年来,建筑环境发生了巨大的变化,对自然生态系统产生了负面影响。本文试图评估印度中部历史首都博帕尔的土地利用变化情景和城市增长预测。使用最大似然分类器进行的土地利用分析显示,需要立即关注日益增长的城市趋势。在过去十年的七年间,城市面积急剧增加了4.90%至8.67%。为了了解未来城市的发展,我们采用基于元胞自动机的Sleuth模型,通过测试、校准和预测三个阶段的模拟过程对数据集进行测试。博帕尔市目前正在经历从农村到城市的转型,因此面临着增长压力,因为包括住房、交通和工业部门在内的各个增长部门。通过城市格局分析表明,城市无计划增长。考虑到一切照旧的情景,通过考虑城市发展计划和划定水体等因素,仔细选择了模型的输入层。SLEUTH分析的结果表明,从2017年到2026年,城市面积的增长速度达到了惊人的779平方公里。结果有助于规划者和政府当局可视化、加强现有政策措施,以建设符合可持续发展目标的未来城市,并为社区提供原始环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling Urban transition using Cellular Automata based Sleuth modelling
Changes in urban dynamics has direct linkages between human beings and its surroundings. Present decade has seen tremendous alterations in the built environment and therefore its negative effect on natural ecosystem. This paper attempts to assess land use change scenario and urban growth prediction for historical capital of central India, Bhopal. Land use analysis performed using maximum likelihood classifier revealed the immediate attention required for growing urban trends. A steep increase in urban areas of 4.90% to 8.67% was observed within a span of seven years for the present decade. In order to understand future urban growth in the city, we employed Cellular Automata based Sleuth model, by testing the datasets in a three-stage simulation procedure: test, calibration and prediction. Bhopal city is currently undergoing transformation from rural urban scenario and therefore facing growth pressure and due to various growth sectors including housing, transport and industrial sector. By urban pattern analysis indicates that unplanned urban growth. Considering business as usual scenario, input layers were carefully selected for the model by considering city development plans and delineating waterbodies etc., Output from the SLEUTH analysis suggest an alarming rate of increase in urban area of 779 km2 from the year 2017 to 2026. Results help planners and government authorities to visualize, strengthen existing policy measures to build future cities in alignment with sustainable goals and promising the community with pristine environment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信