首页    期刊浏览 2024年11月08日 星期五
登录注册

文章基本信息

  • 标题:GIS Technology, 3D Models and Mathematical Models as a Tool for Assessing Development Capabilities of Flood Risk Land to Make Arrangements of Municipal Planning Documents
  • 本地全文:下载
  • 作者:Anna Bazan-Krzywoszańska ; Maria Mrówczyńska ; Sławomir Tront
  • 期刊名称:Inżynieria Ekologiczna
  • 印刷版ISSN:2081-139X
  • 电子版ISSN:2392-0629
  • 出版年度:2019
  • 卷号:20
  • 期号:1
  • 页码:25-33
  • DOI:10.12911/22998993/93866
  • 出版社:Polish Society of Ecological Engineering (PTIE)
  • 摘要:With regard to municipal spatial policies, the issue of flood protection, and hence directions of development of flood-endangered land seems rather significant, given the possible social and economic consequences of mistakenly taken decision.Currently, there is no legal obligation, within the statutory activities of flood protection institutions, to implement guidance documents prior to works on the municipality development.It is determined by the local government in the planning documents, which are in accordance with the applicable regulations, acts of local law.Space management, through planning development and land use or the landscape protection, requires access to comprehensive and reliable information.GIS technology, 3D models and mathematical models using neural networks in spatial analysis and monitoring changes in space to protect flood risk land, provide the possibility to collect information that builds the base of knowledge on the area, which helps to make decisions regarding a purpose and a method of the land use.Data obtained in this way are a valuable source of knowledge on the stage of preparation of planning documents that determine the directions of municipal spatial development.Under the Act of 27 March 2003 on spatial planning and development, these documents are a municipal study of the conditions and directions of the spatial planning and a local zoning plan.
  • 关键词:municipal spatial planning ; local law ; development of flood risk areas ; sustainable development ; GIS ; 3D models ; neural networks
国家哲学社会科学文献中心版权所有