Advancements in Geospatial Planning and Assessment of Green Infrastructure in Cities of the Future

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 28093

Special Issue Editors


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Guest Editor
Swiss Federal Institute of Aquatic Science & Technology (Eawag), 8600 Dübendorf, Switzerland
Interests: water-sensitive urban design (WSUD); future cities planning; integrated modelling; planning support systems; geographic information systems (GIS)
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Guest Editor
Environmental Social Sciences, Eawag, Switzerland
Interests: spatial multicriteria decision analysis; geographic information systems (GIS); stakeholder engagement; integrated urban drainage modelling; planning support systems; water sensitive urban design (WSUD)

Special Issue Information

Dear Colleagues,

Green infrastructure for sustainable urban water management has experienced significant scientific and practical advancements in recent decades. These systems commonly encompass nature-based solutions (NBS), referred to elsewhere as water-sensitive urban design (WSUD), low-impact development (LIDs), sponge city systems and sustainable urban drainage systems (SUDs).

Likewise, geo-spatial analysis has become commonplace in scientific and applied research in sustainable city planning. There has been an observed increase in the use of geospatial techniques and analyses in the urban water scholarship, particularly in the field of green infrastructure. This Special Issue aims to explore new insights into the application of such approaches to green infrastructure and is framed around three core themes:

  • ‘Best planning practices’ of green infrastructure, from technological and policy perspectives in a rapidly urbanizing world;
  • Opportunities for spatial green infrastructure tools and techniques in developed and developing contexts; and
  • Improving operation, monitoring and maintenance of existing green infrastructure in cities.

We encourage a diversity of new and existing methodologies, integrated approaches to green infrastructure planning and are curious to see how emerging topics such as digitalisation, machine learning and broader multidisciplinary approaches can contribute to improving green infrastructure in cities of the future.

Dr. Peter M. Bach
Dr. Martijn Kuller
Guest Editors

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Keywords

  • best planning practices
  • GIS-based planning
  • urban water management
  • asset planning and management
  • stakeholder engagement
  • digitalisation

Published Papers (7 papers)

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Research

19 pages, 10583 KiB  
Article
A Geospatial Platform for Crowdsourcing Green Space Area Management Using GIS and Deep Learning Classification
by Supattra Puttinaovarat and Paramate Horkaew
ISPRS Int. J. Geo-Inf. 2022, 11(3), 208; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi11030208 - 20 Mar 2022
Cited by 7 | Viewed by 3492
Abstract
Green space areas are one of the key factors in people’s livelihoods. Their number and size have a significant impact on both the environment and people’s quality of life, including their health. Accordingly, government agencies often rely on information relating to green space [...] Read more.
Green space areas are one of the key factors in people’s livelihoods. Their number and size have a significant impact on both the environment and people’s quality of life, including their health. Accordingly, government agencies often rely on information relating to green space areas when devising suitable plans and mandating necessary regulations. At present, obtaining information on green space areas using conventional ground surveys faces a number of limitations. This approach not only requires a lengthy period, but also tremendous human and financial resources. Given such restrictions, the status of a green space is not always up to date. Although software applications, especially those based on geographical information systems and remote sensing, have increasingly been applied to these tasks, the capability to use crowdsourcing data and produce real-time reports is lacking. This is partly because the quantity of data required has, to date, prohibited effective verification by human operators. To address this issue, this paper proposes a novel geospatial platform for green space area management by means of GIS and artificial intelligence. In the proposed system, all user-submitted data are automatically verified by deep learning classification and analyses of the greenness areas on satellite imagery. The experimental results showed that the classification and analyses can identify green space areas at accuracies of 93.50% and 97.50%, respectively. To elucidate the merits of the proposed approach, web-based application software was implemented to demonstrate multimodal data management, cleansing, and reporting. This geospatial system was thus proven to be a viable tool for assisting governmental agencies to devise appropriate plans toward sustainable development goals. Full article
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24 pages, 8414 KiB  
Article
3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
by Kaisa Jaalama, Heikki Kauhanen, Aino Keitaanniemi, Toni Rantanen, Juho-Pekka Virtanen, Arttu Julin, Matti Vaaja, Matias Ingman, Marika Ahlavuo and Hannu Hyyppä
ISPRS Int. J. Geo-Inf. 2021, 10(11), 762; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10110762 - 11 Nov 2021
Cited by 2 | Viewed by 3370
Abstract
The importance of ensuring the adequacy of urban ecosystem services and green infrastructure has been widely highlighted in multidisciplinary research. Meanwhile, the consolidation of cities has been a dominant trend in urban development and has led to the development and implementation of the [...] Read more.
The importance of ensuring the adequacy of urban ecosystem services and green infrastructure has been widely highlighted in multidisciplinary research. Meanwhile, the consolidation of cities has been a dominant trend in urban development and has led to the development and implementation of the green factor tool in cities such as Berlin, Melbourne, and Helsinki. In this study, elements of the green factor tool were monitored with laser-scanned and photogrammetrically derived point cloud datasets encompassing a yard in Espoo, Finland. The results show that with the support of 3D point clouds, it is possible to support the monitoring of the local green infrastructure, including elements of smaller size in green areas and yards. However, point clouds generated by distinct means have differing abilities in conveying information on green elements, and canopy covers, for example, might hinder these abilities. Additionally, some green factor elements are more promising for 3D measurement-based monitoring than others, such as those with clear geometrical form. The results encourage the involvement of 3D measuring technologies for monitoring local urban green infrastructure (UGI), also of small scale. Full article
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16 pages, 6733 KiB  
Article
Enhancing the Visibility of SuDS in Strategic Planning Using Preliminary Regional Opportunity Screening
by James L. Webber and Martijn Kuller
ISPRS Int. J. Geo-Inf. 2021, 10(11), 726; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10110726 - 27 Oct 2021
Cited by 6 | Viewed by 2963
Abstract
Surface water flooding poses significant threats to communities and environments. This threat has historically been managed through sewers and combined sewer overflows; however, it is now well recognised that, alone, these legacy systems are insufficient to manage the growing pressures from climate change, [...] Read more.
Surface water flooding poses significant threats to communities and environments. This threat has historically been managed through sewers and combined sewer overflows; however, it is now well recognised that, alone, these legacy systems are insufficient to manage the growing pressures from climate change, population growth and urbanisation. This realisation has led to research and practice developing a broad range of new technologies to enhance the coping capacities of existing sewer systems through capturing and attenuating or reusing surface water across catchments using sustainable drainage systems (SuDS). However, despite technical understanding, industry champions and significant best practice, SuDS remain underutilised, particularly at a synergistic catchment scale where they can be most effective. In this paper we respond to this challenge by developing preliminary screening tools to enhance the visibility of SuDS among the multidisciplinary decision-makers responsible for directing strategic surface water management. We achieve this through upscaling a regional decision support model and demonstrating implementation across a case study in South West England. We find that it is possible to use easily accessible and open-source data to provide initial indications of SuDS opportunities and that this early visibility in the decision-making process can be used to support the consideration of novel and effective surface water management strategies. Full article
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17 pages, 2346 KiB  
Article
Spatially Varying Effects of Street Greenery on Walking Time of Older Adults
by Linchuan Yang, Jixiang Liu, Yuan Liang, Yi Lu and Hongtai Yang
ISPRS Int. J. Geo-Inf. 2021, 10(9), 596; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10090596 - 10 Sep 2021
Cited by 62 | Viewed by 4198
Abstract
Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults’ walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built [...] Read more.
Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults’ walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built environment variable readily estimated by big data) on older adults’ walking behavior, they have not focused on the spatial heterogeneity in the influence. To this end, this study extracts the socioeconomic and walking behavior data from the Travel Characteristic Survey 2011 of Hong Kong and estimates street greenery (the green view index) based on Google Street View imagery. It then develops global models (linear regression and Box–Cox transformed models) and local models (geographically weighted regression models) to scrutinize the average (global) and location-specific (local) relationships, respectively, between street greenery and older adults’ walking time. Notably, green view indices in three neighborhoods with different sizes are estimated for robustness checks. The results show that (1) street greenery has consistent and significant effects on walking time; (2) the influence of street greenery varies across space—specifically, it is greater in the suburban area; and (3) the performance of different green view indices is highly consistent. Full article
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28 pages, 11422 KiB  
Article
Whose Urban Green? Mapping and Classifying Public and Private Green Spaces in Padua for Spatial Planning Policies
by Guglielmo Pristeri, Francesca Peroni, Salvatore Eugenio Pappalardo, Daniele Codato, Antonio Masi and Massimo De Marchi
ISPRS Int. J. Geo-Inf. 2021, 10(8), 538; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10080538 - 10 Aug 2021
Cited by 22 | Viewed by 7291
Abstract
The rising environmental issues on contemporary cities urgently calls for sustainable planning policies. Implementation of nature-based solutions, ecosystem services, and green infrastructures associated to green spaces management is at present of paramount importance. In contrast to policies mainly focused on public greenery, the [...] Read more.
The rising environmental issues on contemporary cities urgently calls for sustainable planning policies. Implementation of nature-based solutions, ecosystem services, and green infrastructures associated to green spaces management is at present of paramount importance. In contrast to policies mainly focused on public greenery, the inclusion of private green in planning strategies might be a promising pathway. The general aim is mapping and classifying urban green spaces in Padua, a city of 93.3 km2 (Northeast Italy). Specific aims are (i) testing an NDVI-derived extraction from very high-resolution orthophotos; (ii) classifying property status; (iii) highlighting multilevel relationships and strategies for urban green spaces implementation and management; (iv) assessing greenery in relation to per capita population. By performing remote sensing and GIS analyses, a first detailed global map of urban green spaces in Padua was created; then, binary classification and thematic maps for rural/non-rural, public/private, municipal/non-municipal greenery were produced for all urban units. Results show that, among total green spaces (52.23 km2), more than half are rural. Moreover, private green spaces represent 80%, while within public areas (20%) less than 10% are municipal (5 km2). We therefore highlight scenarios for planning policies in Padua by providing tools to policymakers for an integrated management of green spaces, where private greenery might also contribute to ecosystem services implementation for common urban well-being. Full article
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16 pages, 7789 KiB  
Article
Hydrological Modeling of Green Infrastructure to Quantify Its Effect on Flood Mitigation and Water Availability in the High School Watershed in Tucson, AZ
by Yoganand Korgaonkar, David Phillip Guertin, Thomas Meixner and David C Goodrich
ISPRS Int. J. Geo-Inf. 2021, 10(7), 443; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070443 - 29 Jun 2021
Cited by 4 | Viewed by 2948
Abstract
Green Infrastructure (GI) practices are being implemented in numerous cities to tackle stormwater management issues and achieve co-benefits such as mitigating heat island effects and air pollution, as well as water augmentation, health, and economic benefits. Tucson, Arizona is a fast-growing city in [...] Read more.
Green Infrastructure (GI) practices are being implemented in numerous cities to tackle stormwater management issues and achieve co-benefits such as mitigating heat island effects and air pollution, as well as water augmentation, health, and economic benefits. Tucson, Arizona is a fast-growing city in the semiarid region of the southwest United States and provides a unique landscape in terms of urban hydrology and stormwater management, where stormwater is routed along the streets to the nearest ephemeral washes. Local organizations have implemented various GI practices, such as curb cuts, traffic chicanes, roof runoff harvesting, and retention basins, to capture the excess runoff and utilize it on-site. This study models the 3.31 km2 High School watershed in central Tucson using the Automated Geospatial Watershed Assessment (AGWA) tool and the Kinematic Runoff and Erosion (KINEROS2) model. Each parcel in the watershed was individually represented using the KINEROS2 Urban element to simulate small-scale flow-on/flow-off processes. Seven different configurations of GI implementation were simulated using design storms, and we stochastically generated 20 years of precipitation data to understand the effects of GI implementation on flood mitigation and long-term water availability, respectively. The design storm analysis indicates that the configuration designed to mimic the current level of GI implementation, which includes 175 on-street basins and 37 roof runoff harvesting cisterns, has minimum (<2%) influence on runoff volume. Furthermore, the analysis showed that the current level of GI implementation caused an increase (<1%) in peak flows at the watershed outlet but predicted reduced on-street accumulated volumes (>25%) and increased water availability via GI capture and infiltration. When the GI implementation was increased by a factor of two and five, a larger reduction of peak flow (<8% and <22%, respectively) and volume (<3% and <8%, respectively) was simulated at the watershed outlet. The 20-year analysis showed that parcels with roof runoff harvesting cisterns were able to meet their landscape irrigation demands throughout the year, except for the dry months of May and June. Additionally, stormwater captured and infiltrated by the on-street basins could support xeric vegetation for most of the year, except June, where the water demand exceeded volume of water infiltrated in the basins. The current level of GI implementation in the High School watershed may not have significant large-scale impacts, but it provides numerous benefits at the parcel, street, and small neighborhood scales. Full article
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13 pages, 2230 KiB  
Article
Spatial Orientation Skill Performance with a Workshop Based on Green Infrastructure in Cities
by Carlos Carbonell-Carrera, Jose Luis Saorin, Dámari Melián-Díaz and Stephany Hess-Medler
ISPRS Int. J. Geo-Inf. 2020, 9(4), 216; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040216 - 03 Apr 2020
Cited by 2 | Viewed by 2652
Abstract
Better training of spatial skills of green infrastructure managers will contribute to better planning practices in this field. The professionals using geo-spatial technologies in sustainable city planning require, in their curriculum, specific training focused towards the acquisition of spatial skills. Using maps and [...] Read more.
Better training of spatial skills of green infrastructure managers will contribute to better planning practices in this field. The professionals using geo-spatial technologies in sustainable city planning require, in their curriculum, specific training focused towards the acquisition of spatial skills. Using maps and geo-spatial technologies, spatial orientation skill is needed. In this research, a workshop based on a green infrastructure has been carried out. A specific teaching strategy for the improvement of spatial orientation skill has been performed. In the workshop, 3D technologies of graphic representation of an urban environment were used such as Cad Mapper, Sketch Up Make 2017 and Google Street View. Thirty-two students (22 treatment group, 10 control group) of agronomic engineering participated. The impact on spatial orientation skill was measured with the Perspective Taking-Spatial Orientation test, through pre- and post-tests. No gender differences were found. The Treatment Group obtained a significant increase of 19.27% in their spatial orientation skill. Participants of the Control group did not significantly increase their spatial orientation skill (3.21%). Specific teaching strategies such as those performed in this research can be effective for the training and development of spatial orientation skill, needed for geospatial planning in the field of Green Infrastructures. Full article
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