Moving Science Towards Operational Sustainability

The Use of Geospatial Decision Support Systems

Bibliographic Data

ID21648282
AuthorsFabio Terribile (0000-0003-3672-2294, University of Naples Federico II, corresponding author), Angelo Basile (0000-0002-6238-0278)
Year2025
Volume36
Issue5
Pages1401-1404
Publication date2025-03-01
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.5447
OpenAlexW4406294296
LanguageEN
References cited16

The demands on our landscapes increasingly conflict with each other (e.g., the transition to sustainable agriculture versus the expansion of urban areas). We must address increasing land degradation problems (e.g., erosion, loss of soil fertility and biodiversity, floods, pollution) and the imperative to move toward land use sustainability. Making decisions to meet these diverse requirements and solve problems is often highly complex and challenging. Similar issues are evident in the implementation of multiscale land policies at global (e.g., SDGs), European (e.g., CAP), national (e.g., climate change adaptation plans in EU Member States), regional (e.g., implementation of the EU Nitrates Directive), and local (e.g., urban planning) levels. There is a need to bridge the knowledge gap between decision-makers, who require operational support to implement policies and actions toward land use sustainability, and the research community. The development of Decision Support Systems (DSS), particularly geoSpatial Decision Support Systems (S-DSS) including Digital Twin-based tools, offers a promising avenue to address these complex challenges. Over the past decade, advancements in S-DSS were driven by progress in land management sciences, databases, modelling, datacube technologies, high-performance computing (HPC), Earth Observation (EO), artificial intelligence (AI), WebGIS facilities, and Geospatial Cyberinfrastructure. Together, these advancements have significantly enhanced the connection between land resource science and practical, operational land management. In this scenario, the current LDD special issue collects research papers on advanced approaches and methodologies in land-based Spatial Decision Support Systems (S-DSS), aiming to address whether S-DSS can effectively handle the complexity of the challenges mentioned above and facilitate the transition toward sustainable land and soil use. The focus is to cover the following items: (i) the diversity of approaches, both from a methodological and end-user perspective, using multidisciplinary and multifunctional strategies in view of the development of Decision Support Systems, (ii) the implementation of S-DSS to promote sustainable land uses in various sectors such as agriculture, forestry, urban planning, land revitalization, climate change, and environmental and human health. This special issue aims to test the feasibility of S-DSS in facilitating a scientific paradigm shift in working with the physical landscape by overcoming the current fragmentation of the many separate applied research approaches toward the common objective of sustainable land planning and management. More specifically, S-DSS promise to integrate geospatial knowledge that helps bridge the gap between scientists working on landscape research and end-users. This special issue, with a specific focus on sustainable land management, aligns well with the core focus of Land Degradation and Development. It aims to advance the field by exploring scientific domains and developing operational, scientifically sound tools to empower “management, planning and policy-making relating to the promotion of ecological sustainability and the of counteraction land degradation.” Geospatial Decision Support Systems (S-DSS) are decision support systems that incorporate geospatial information, making them particularly valuable for addressing land-based issues such as land planning and management. Their applications span various sectors, including agriculture, forestry, environmental protection, and urban planning. These S-DSS systems have a history marked by both successes and failures (e.g., Geertman and Stillwell 2009). To analyze the development of these S-DSS systems across different scientific domains from the 1990s onward, we have employed a citation-mapping analysis following the methods by Trujillo and Long (2018). Figure 1 shows that most of the advancements have taken place in the last decade, and it is evident—though expected—that there are very diverse, unconnected clusters. Besides urban transport and waste management, there are clusters for “Land Use Policies & Ecosystem Services” and “Rural Development.” These last two themes are particularly relevant to this special issue. A deeper insight into the use of S-DSS systems within the “soil science” domain is shown in Figure 2. It can be observed that the majority of developments in this area have occurred in the last decade. Notably, there are four distinct clusters—land use policy, soil sealing, modelling, and agriculture—that again do not interact with each other. These clusters appear to have evolved independently, each driven by different objectives. The new generation of S-DSS makes it possible to link these clusters, on the basis that the solutions to be applied to the sustainable management of territories must not be mono-disciplinary but rather have to be trans-disciplinary and must cover multiscale and multistakeholder needs. This Special Issue assembles 15 papers that cover a broad spectrum of topics, from weed control to climate change, all analyzed through the perspective of developing S-DSSs. Approximately, 60% of the papers refer to actual S-DSS applications, while the other half focus on preliminary steps, such as analyzing environmental and land features relevant for developing DSS or S-DSS. Below, we provide detailed insight into these contributions. Approximately 45% of the submitted papers are related to the EU Horizon 2020 project named LANDSUPPORT (www.landsupport.eu), funded by the European Commission (Call RUR-03-2017), and its connected final international conference. The LANDSUPPORT project aims to develop a web-based, free, open-access GeoSpatial Decision Support System (S-DSS) to support sustainable agriculture and forestry, evaluate land-use trade-offs, and contribute to land-use policy development and implementation in Europe. The project developed a comprehensive set of operational, transdisciplinary S-DSS tools based on a smart Geospatial CyberInfrastructure (GCI) across different geographical and governance scales, ensuring substantial transferability across diverse physical, socio-economic, and cultural settings. The papers describe the scientific approaches and results in developing these operational tools. Terribile et al. (2024) detail the central concept and results of developing a multiscale, multistakeholder, and transdisciplinary S-DSS, demonstrating that reconciling agriculture and the environment is feasible with appropriate DSS tools. Manna et al. (2024) showcase an S-DSS tool used to quantify land degradation across the EU, fulfilling SDG 15.3 requirements. Baumann et al. (2024) address the critical issue of database architecture (datacube technology) necessary for implementing high-performance S-DSS systems. Bonfante et al. (2024) present an operational S-DSS tool developed to estimate the impact of climate change at various NUTS levels (e.g., municipalities to countries) across the EU, with additional focus on crop adaptability in Italy. Mileti et al. (2024) produce a biodiversity tool implementing the EU Habitat Directive at the regional level (Campania region in Italy) while Bancheri et al. (2024) demonstrate a tool based on process-based (crop growth) modelling implemented in an S-DSS, evaluating agricultural best practices in real-time based on site-specific pedoclimatic information. Finally, Stankovics et al. (2024) highlight the critical importance of stakeholder engagement in developing successful S-DSS systems. Two papers focus on DSS applied to multi-criteria decision support systems in aquaculture (Dharani Shrree et al. 2024) and on the prediction of Festuca ovina for the restoration of degraded lands (Saffariha et al. 2023). The remaining 40% of contributions cover preliminary research relevant to S-DSS development, including Spatiotemporal evolution and driving mechanisms of slope cultivated land (Yu, Li et al. 2024), Land pressure evaluation through the lens of the production-living-ecology framework (Yu, Chen et al. 2024), A framework for quantifying and integrating green development of cultivated land in China, using an Adaptability-Vitality-Resistance (AVR) perspective (Niu et al. 2024), Spatial variability of soil organic carbon in China's terrestrial ecosystems (Li et al. 2024), Optimization strategies for ecological security patterns (Wei et al. 2024), Risk assessment in a contaminated area (Mondaca et al. 2024). This special issue of Land Degradation & Development reveals a dynamic and evolving landscape of research in the field of Spatial Decision Support Systems (S-DSS). It offers a compelling overview of the latest advancements in methodologies, showcasing the development of sophisticated tools designed to address complex land management challenges. A key theme emerging from the collected papers is the necessity of transdisciplinary collaboration. The development of effective S-DSS requires integrating expertise from various scientific domains, including soil science, environmental science, computer science, and social science. This collaborative approach ensures that S-DSS tools are not only scientifically sound but also address the practical needs of stakeholders and policymakers. Furthermore, the special issue emphasizes the importance of making these tools accessible to a wider audience. Several papers present freely available, web-based S-DSS tools, demonstrating a commitment to open access and knowledge sharing. This approach facilitates broader adoption of S-DSS by land managers, researchers, and policymakers, ultimately promoting more sustainable land use practices. Looking ahead, the insights presented in this special issue on advanced approaches and methodologies in land-based Spatial Decision Support Systems (S-DSS) underscore the potential of S-DSS to revolutionize land management practices. By fostering collaboration between scientists and end-users, S-DSS can empower informed decision-making, bridge the gap between research and application, and promote a more sustainable future for our lands. The development and widespread adoption of S-DSS are crucial steps toward addressing the complex environmental challenges facing our world today. We wish to thanks Dr. M. H. Sellami for providing the co-citation mapping (Figures 1 and 2). Data are available upon request to authors. Data S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article

Business · Data mining · Decision support system · Environmental planning · Environmental resource management · Geography · Geospatial analysis · Process management · Remote sensing · Sustainability · Sustainability organizations · Sustainability science · 3D Modeling in Geospatial Applications · Computer Science · Environmental Science · Geographic Information Systems Studies · Land Use and Ecosystem Services

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