Big Data Analytics, Spatial Optimization for Land Use Planning
A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Planning and Landscape Architecture".
Deadline for manuscript submissions: closed (2 June 2023) | Viewed by 14075
Special Issue Editors
Interests: GIS science; spatial optimization; spatial big data analytics; spatially integrated social science
Interests: spatial and temporal simulation and optimization of land use
Special Issue Information
Dear Colleagues,
Land use planning is a process of resource allocation, by which different land uses or activities are allocated to specific units of land area, usually within a city or a region. Spatial optimization, a powerful spatial analysis technique that can be used to identify optimal solution(s) and generate a large number of alternatives, is able to support the land use planning process effectively. There have been many successful relevant studies focusing on developing spatial optimization models to support the land use planning practices, which have promoted the advancement of the field in recent decades. Meanwhile, emerging big datasets have also started to play a more and more important role in land use management and planning. The big data revolution is significantly changing the way of how land use planning could be conducted and how spatial optimization techniques could be utilized.
In order to capture the latest advancement and encourage more efforts in this field of the integration of big data and spatial optimization for better supporting the practices of land use planning, this Special Issue with Land aims to develop a viable research agenda in this area of research.
We are seeking original unpublished papers on the following topics including, but not limited to:
- Big data acquisition and analytics techniques for spatial optimization and land use planning;
- Quantitative modelling of objectives and constraints with the support of big data analytics for land use planning;
- Design of novel optimization algorithms for effective and efficient spatial optimization in supporting land use planning;
- Spatio-temporal optimization for land use planning;
- Integration of high-performance computing, cloud computing, GPU-based parallel computing in spatial optimization and land use planning;
- Land use planning (decision making) support system.
Prof. Dr. Kai Cao
Dr. Wenting Zhang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- spatial optimization
- big data analytics
- land use planning
- spatio-temporal optimization
- land use planning support