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Ecosystemic Services and Landscape Perspectives on Sustainable Urban Forest Planning

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 1283

Special Issue Editors


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Guest Editor
Department of Botany, Ecology and Plant Physiology, Universidad de Córdoba, 14071 Córdoba, Spain
Interests: sustainability; urbanism; biodiversity conservation; urban forest; ecosystemic services

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Guest Editor
Department of Botany, Ecology and Plant Physiology, Universidad de Córdoba, 14071 Córdoba, Spain
Interests: key sustainability; allergenicity; pollen; ecosystemic services; urban health

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Guest Editor
Department of Economic Analysis and Political Economy, Universidad de Sevilla, 41004 Sevilla, Spain
Interests: environmental economics; sustainability; energetic policy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ensuring that human communities, and particularly cities, live sustainably is a global goal, being part of the sustainable development goals (SDGs). It brings together other objectives such as health and well-being, climate action, and the reduction of inequalities, among others, evidencing the relevance of working for the better development of cities. To achieve this sustainable development of cities, valuing and promoting urban trees and their ecosystem services (ESs) is essential. In this sense, it is essential to improve the planning and management of urban trees, not only from the perspective of the landscape but from the provision of different ESs. Although work has been carried out on landscape design in cities, currently, the local management of the urban forest does not present clear and practical methods, tools, or policies that propose and encourage the integration and maximization of the ESs of urban trees as part of the variables and fundamental elements of city planning and the management of cities. In this sense, this Special Issue proposes to create an opportunity to showcase research that provides proposals for criteria, variables, tools, and methodologies applicable to local managers and those responsible for the design, planning, and management of urban trees, that allow them to consider the natural characteristics of the ES provision of urban trees in the planning of local green areas, in order to achieve sustainable cities based on the optimization of their ecosystem services from an environmental and economic viewpoint. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Definition and proposals of variables, criteria, and methods for measuring the ecosystem services of urban trees applicable by local managers.
  • Characterization and assessment of the urban landscape, and methodology for its improvement.
  • Application of technological tools (GIS, software, artificial intelligence, and others) for the evaluation and management of the landscape and the ESs of urban trees.
  • Economic valuation methods of urban forest ESs based on specific structure and composition parameters, manageable at the local level.
  • Current status and applicability of current urban tree management policies regarding the relevance of ESs worldwide.
  • Proposals or guidelines for the development of new public policies that ensure the maximization of ecosystem services in the management of urban trees.
  • Planning strategies to integrate the design of the urban landscape with the optimization of the ESs provided by trees in cities.
  • Ecological services and landscape perspectives on sustainable urban forests.

We look forward to receiving your contributions. 

Dr. Roberto Moreno-García
Prof. Dr. Carmen Galan
Prof. Dr. José M. Cansino
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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • urban forest
  • neutral cities
  • sustainability
  • environmental services
  • urban management

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Published Papers (1 paper)

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Research

30 pages, 5634 KiB  
Article
Evaluating Ecosystem Service Trade-Offs and Recovery Dynamics in Response to Urban Expansion: Implications for Sustainable Management Strategies
by Mohammed J. Alshayeb
Sustainability 2025, 17(5), 2194; https://doi.org/10.3390/su17052194 - 3 Mar 2025
Viewed by 818
Abstract
Land use land cover (LULC) changes due to rapid urbanization pose critical challenges to sustainable development, particularly in arid and semi-arid regions like Saudi Arabia, where cities such as Abha are experiencing unprecedented expansion. Urban sprawl is accelerating environmental degradation, affecting key natural [...] Read more.
Land use land cover (LULC) changes due to rapid urbanization pose critical challenges to sustainable development, particularly in arid and semi-arid regions like Saudi Arabia, where cities such as Abha are experiencing unprecedented expansion. Urban sprawl is accelerating environmental degradation, affecting key natural resources such as vegetation, water bodies, and barren land. This study introduces an advanced machine learning (ML) and deep learning (DL)-based framework for high-accuracy LULC classification, urban sprawl quantification, and ecosystem service assessment, providing a more precise and scalable approach compared to traditional remote sensing techniques. A hybrid methodology combining ML models—Random Forest, Artificial Neural Networks, Gradient Boosting Machine, and LightGBM—with a 1D Convolutional Neural Network (CNN) was fine-tuned using grid search optimization to enhance classification accuracy. The integration of deep learning improves feature extraction and classification consistency, achieving an AUC of 0.93 for Dense Vegetation and 0.82 for Cropland, outperforming conventional classification methods. The study also applies the Markov transition model to project land cover changes, offering a probabilistic understanding of urban expansion trends and ecosystem dynamics, providing a significant improvement over static LULC assessments by quantifying transition probabilities and predicting future land cover transformations. The results reveal that urban areas in Abha expanded by 120.74 km2 between 2014 and 2023, with barren land decreasing by 557.09 km2 and cropland increasing by 205.14 km2. The peak ecosystem service value (ESV) loss was recorded at USD 125,662.7 between 2017 and 2020, but subsequent land management efforts improved ESV to USD 96,769.5 by 2023. The resilience and recovery of natural land cover types, particularly barren land (44,163 km2 recovered by 2023), indicate the potential for targeted restoration strategies. This study advances urban sustainability research by integrating state-of-the-art deep learning models with Markov-based land change predictions, enhancing the accuracy and predictive capability of LULC assessments. The findings highlight the need for proactive land management policies to mitigate the adverse effects of urban sprawl and promote sustainable ecosystem service recovery. The methodological advancements presented in this study provide a scalable and adaptable framework for future urbanization impact assessments, particularly in rapidly developing regions. Full article
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