Topic Editors
Spatial Decision Support Systems for Urban Sustainability
Topic Information
Dear Colleagues,
Spatial Decision Support Systems (SDSSs) are designed around geospatial data, models, and analytical tools that collectively support human planning and decision-making procedures in multiple application areas. These areas are constantly evolving to better address existing real-world challenges and find innovative ways forward such as in enabling and facilitating urban sustainability.
In this Topic Issue, we focus on the theory and methods of SDSSs and their implementation in the context of urban sustainability. We are interpreting sustainability broadly to mean the understanding and improvement of inputs and processes that optimize the distribution of output patterns. We welcome contributions from research directions that focus on data-oriented approaches (e.g., spatial multicriteria methods and remote sensing), intelligence-based approaches (e.g., machine learning and artificial intelligence methods), model-based approaches (e.g., analytics and simulation methods), and participatory approaches (e.g., citizen science and volunteer GIS methods). In addition, the interoperability between the data, systems, and people can yield innovative contributions. We anticipate these ideas will be developed around the pressing urban sustainability challenges that deal with land use and land cover change, climate change adaptation, and population growth, among others.
The topic "Spatial Decision Support Systems for Urban Sustainability” provides an outlet to publish original research and application papers. Join us as we re-examine existing pathways and explore new ground in the science and applications of SDSSs. We look forward to your contributions.
Dr. Shivanand Balram
Dr. Raja Sengupta
Dr. Jorge Rocha
Topic Editors
Keywords
- Spatial Decision Support Systems (SDSS)
- climate change adaptation
- Geographic Information Systems (GIS)
- land use planning
- remote sensing
- urban informatics
- urban sustainability
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
|---|---|---|---|---|---|---|
Geographies
|
- | 1.7 | 2021 | 23.5 Days | CHF 1000 | Submit |
Geomatics
|
- | - | 2021 | 21.8 Days | CHF 1000 | Submit |
ISPRS International Journal of Geo-Information
|
2.8 | 6.9 | 2012 | 36.2 Days | CHF 1700 | Submit |
Land
|
3.2 | 4.9 | 2012 | 17.8 Days | CHF 2600 | Submit |
Urban Science
|
2.1 | 4.3 | 2017 | 24.7 Days | CHF 1600 | Submit |
Sustainability
|
3.3 | 6.8 | 2009 | 20 Days | CHF 2400 | Submit |
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Published Papers (1 paper)
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Spatial nonlinear effects of street vitality constrained by construction intensity and functional diversity—A case study from the streets of Shenzhen
Authors: Conceptualization, J.L. and S.L.; Methodology, J.L. and S.L.; Software, J.L.; Validation, J.L. and S.L.; Formal analysis, J.L.; Investigation, J.L., N.K., Y.K., J.Z. and J.C.; Resources, J.L. and S.L.; Data curation, J.L. and S.L.; Writing—original draft, J.L.; Writing—review and editing, J.L. and S.L.; Project administration, S.L.; Funding acquisition, S.L. and J.L. All authors have read and agreed to the published version of the manuscript.
Affiliation: Jilong Li1, Shi** Lin1, *, Niuniu Kong1, Yilin Ke1, Jie Zeng1 and Jiacheng Chen1 1 Hainan University, College of Tropical Agriculture and Forestry, Hainan570208, China;
Abstract: Street vitality, as an essential component of urban vitality, is a comprehensive description of activities and processes within the street, influenced by various factors of the street's built environment and the vitality of surrounding streets. Consequently, the spatial effects of street vitality can be understood within the constraints of the built environment. However, existing assessment methods struggle to effectively explain the spatial correlations between street vitalities. This study uses 5290 street segments in Shenzhen, utilizing multi-source geospatial big data to evaluate street vitality, construction intensity, and functional diversity. Based on varying living circle ranges, spatial weight matrices at different distances were created. Using a spatial autoregressive threshold model, thresholds for construction intensity and functional diversity on streets were estimated, and the spatial non-linear effects of urban vitality based on various spatial weight matrices were analyzed. The results indicate: (1) There is a significant spatial spillover effect of street vitality; (2) The spatial spillover effect of street vitality weakens as the living circle expands (Moran's I under 500m, 1000m, and 1500m spatial weight matrices are 0.178***, 0.160***, and 0.145*** respectively); (3) There is a threshold for construction intensity at 0.1466 across different spatial matrices, and two thresholds for functional diversity at 0.6832 and 1.2681 for the 500m spatial weight matrix, and dual thresholds of 0.6832 and 1.4325 for 1000m and 1500m spatial weight matrices. This conclusion provides stakeholders with spatial patterns that affect street vitality, offering a theoretical basis for further breaking down the barriers to street vitality.
