Geographic Information Systems and Cartography for a Sustainable World

Abstract

This article summarizes the scope and content of the Special Issue (SI) entitled “Geographic Information Systems (GISs) and Cartography for a Sustainable World” and its contribution to the global discourse regarding sustainability concerns. At the heart of the discussion in this SI lies: (i) GISs, a valuable tool and a means for modeling, designing, and analyzing (spatial) data and processes related to the pursuance of sustainability objectives at both local and global scales; and (ii) Cartography as a discipline, which through maps and visualizations can convey the present state. The latter can play a vital role in educating, empowering, and raising public awareness with regard to sustainability concerns on the one hand, and can form a basis for policy-makers, scientists, and citizens for articulating effective sustainability strategies on the other. The fulfillment of the SI goals is attained through a collection of 26 papers that delve into and attempt to visualize sustainability achievements or concerns on a variety of themes in different parts of the world. More specifically, the content of this collection of papers can be categorized into the following sustainability-related themes: Urbanization, Transportation, Carbon Emissions Management, Infrastructure, Rural Development, and Climate Change. The main conclusion is that planning and implementing sustainability policies is a challenging and multi-level task, and must be carried out within a fully dynamic decision environment. Although some progress has already been made, more intensive and collective efforts from scientists, governments, the entrepreneurial community, and citizens are needed in order for the ambitious goals of Agenda 2030 to be reached.

1. Introduction

Humanity is currently confronted with the challenge of sustainable development, i.e., meeting current societal needs without compromising the ability of future generations to meet their own. The achievement of the Sustainable Development Goals is a complex and interdisciplinary task that aims to balance economic, environmental, and societal/cultural objectives. The United Nations’ Sustainable Development Goals (SDGs), outlined in the 2030 Agenda, call for action from all the world’s states. The 17 SDGs include the following policy fields: SDG 1—No Poverty, SDG 2—Zero Hunger, SDG 3—Good Health and Well-being, SDG 4—Quality Education, SDG 5—Gender Equality, SDG 6—Clean Water and Sanitation, SDG 7—Affordable and Clean Energy, SDG 8—Decent Work and Economic Growth, SDG 9—Industry, Innovation and Infrastructure, SDG 10—Reduced Inequality, SDG 11—Sustainable Cities and Communities, SDG 12—Responsible Consumption and Production, SDG 13—Climate Action, SDG 14—Life Below Water, SDG 15—Life on Land, SDG 16—Peace and Justice Strong Institutions, and SDG 17—Partnerships to achieve the Goals. The consequences of humanity’s unsustainable development patterns are becoming evident and are therefore necessitating the fulfillment of the SDGS; consequently, the international community’s interest in achieving these goals is piquing as the deadline of 2030 draws near.

In seeking to achieve the SDGs, various kinds of datasets and relevant tools for assessing, managing, and monitoring progress are nowadays a crucial topic. Towards this end, scientists and spatial data stakeholders worldwide are currently utilizing spatial data, Geographic Information Systems (GISs), and Cartography to analyze, assess, visualize, and highlight spatial and developmental inefficiencies in order to support planning efforts and related policy pathways, aimed at achieving sustainability objectives. Geographic Information Systems (GISs) are the ultimate tools for modeling, designing, and analyzing large datasets that can demonstrate progress or barriers to sustainability achievements at scales ranging from local to global. They offer insights into complex spatial relationships and facilitate more informed policy-making. At the same time, Cartography provides an opportunity for visualization and mapping of achievements in various topics, thereby enabling the communication of sustainability progress to scientists, citizens, and the policy community. In this respect, it plays a key role in educating, empowering, and raising awareness about sustainability concerns in society as a whole.

Within such a context, this Special Issue aims to present research works on the role of Geographic Information Systems (GISs) and Cartography as key pillars in the effort of progressing towards a sustainable world.

The Special Issue (SI) collected twenty-six distinct contributions. Based on their specific focus, these papers can be classified into six topics related to sustainability, which are as follows: Rural Development, Carbon Emissions Management, Climate Change, Infrastructure, Transportation, and Urbanization. In addition to the above thematic classification, the papers address the following Sustainable Development Goals (SDGs) as outlined in the 2030 Agenda by the United Nations:

• Rural Development: SDG 1 (No Poverty), SDG 4 (Quality Education), SDG 5 (Gender Equality), SDG 7 (Affordable and Clean energy), SDG 8 (Decent Work and Economic Growth), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), and SDG 15 (Life on Land).
• Carbon Emissions Management: SDG 7 (Affordable and Clean Energy), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action).
• Addressing Climate Change Implications: SDG 13 (Climate Action).
• Infrastructure: Industry, Innovation and Infrastructure (SDG 9).
• Transportation: SDG 3 (Good Health and Well-being), SDG 9 (Industry, Innovation and Infrastructure), SDG 11 (Sustainable Cities and Communities).
• Urbanization: SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 15 (Life on Land) [1].

Several case studies are presented in the SI articles, covering an area that spans all continents except North America and Oceania. Specifically, 13 case studies (50%) are dealing with topics situated in Asia, 9 in Europe (38%), 1 in South America (4%), and 1 in Africa (4%), while 1 article (4%) does not have a particular case study reference. This diversity and global coverage highlights the efforts of the international scientific community to achieve the SDGs, through gaining insight and developing tools that can tackle the global challenges and overcome obstacles to SDGs, as an important facet of their research. Regarding the nationalities of the first authors, 14 (54%) are from Asia, 10 (38%) are from Europe, and 2 (8%) are from Africa.

The research articles integrate several software and tools for data acquisition, processing, (spatial) analysis, statistical analysis, visualization, and web dissemination. These include the following:

• Open-source and commercial GIS software, such as QGIS and plugins, ArcMap and toolboxes, as well as Supermap (e.g., [2,3,4,5,6,7,8,9,10,11,12,13,14]);
• Statistical software, such as SAS, SPSS, and R (e.g., [13,15,16]);
• Remote sensing software, e.g., ERDAS Imagine, platforms such as Google Earth Engine (GEE), and toolboxes such as Guidos Toolbox (e.g., [6,17,18])
• Web mapping technologies such as Open Layers, Leaflet, and Geoserver (e.g., [8,10,12,16]);
• Python scripting (e.g., [3,5,7,10,12]);
• Spatial database management, e.g., Postgres (e.g., [8]);
• Other specialized spatial data analysis tools, libraries, and custom tools (e.g., [5,7,8,10,11,13,16]).

AI and machine learning techniques are rarely employed across the case studies of the research. One study uses Support Vector Machine (SVM), a machine learning technique, for land use classification from satellite imagery [19]. Furthermore, in one study, cellular automata–artificial neural networks (CA-ANN) are utilized to monitor LULC changes over three decades (1990–2020) [11]. However, several papers suggest the future integration of advanced machine learning algorithms to improve research efforts [5,12,17,18,20].

The studies include a rich variety of data, such as the following:

• Satellite data (e.g., Sentinel-2, Landsat) (e.g., [5,13,19,20,21]).
• Volunteered Geographic Information (e.g., OSM) (e.g., [9,10,11,16]).
• Social and economic data (e.g., [9,11,14,17,18,19,21,22,23,24,25,26]).
• Climate and meteorological data (e.g., [5,7,11,17,20]).
• Land use–land cover (e.g., [2,5,10,11,14,17,23]).
• Topographic data such as road networks, hydrological networks, etc., (e.g., [2,3,4,6,8,9,11,18,19,25]) and Digital Elevation Models (e.g., [3,6,7,10,23]).
• Environmental data (e.g., [5,14,22,24,26]).
• Geotechnical and seismic data (e.g., [13]).
• Soil data (e.g., [4,13]).
• Protected Natural Areas and Biodiversity data (e.g., [2]).
• Cultural heritage data (e.g., [4,26]).
• Tourism data (e.g., [26]).
• Data collected especially for the case study, e.g., GNSS measurements, LIDAR (e.g., [8,27]).
• Expert and citizen survey data (e.g., [3]).

Cartography and geovisualization play an important role in supporting the analysis and presenting the results of the case studies. Most papers use traditional 2D paper maps and some use 3D maps [7,8,10], while web maps are also utilized [10,12,15,16].

In Section 2, the published papers are briefly presented according to their classification into the sustainability topics. As the major points and outcomes of each contribution are highlighted and discussed, a general discussion for each sustainability topic is formed. Finally, in Section 3, future research directions in sustainability assessments and visualization are drawn.

2. An Overview of the Published Papers

In this section, the main findings of each research article of the SI are summarized. Articles are grouped by class based on the main topic they address.

2.1. Rural Development

Hrustek et al. [15] analyze the transparency of government tenders for leasing state-owned agricultural land in Croatia. To improve transparency, the authors propose a national digital tendering platform and repository, hybrid public bid openings, randomized expert selection for commissions, full public disclosure of all bids, and an evaluation of the results to ensure the responsible and transparent management of agricultural land leases. Ge et al. [23] analyze the coordinated development of rural industry and employment (RIE) in Chongqing, China, from 2013 to 2023. This is achieved by examining the spatiotemporal evolution and driving mechanisms of the coordinated development of RIE. The study suggests employment-centered strategies to address industrial lag and spatial imbalances, providing insights for rural revitalization policies in developing regions. Cao et al. [19] evaluate the new quality productivity of agriculture and rural areas across 31 provinces in mainland China from 2010 to 2022 by examining spatial changes and evolutionary trends. The study emphasizes the importance of regional coordination, technological innovation, infrastructure investment, and ecological protection to promote balanced rural revitalization and quality productivity growth. Angelelli et al. [2] present a replicable methodology for assessing land suitability for agrivoltaic (agriPV) projects, focusing on the province of Viterbo, Italy. The case study reveals significant spatial variability in suitability and sensitivity within the province and emphasizes the need for nuanced, flexible approaches to planning agriPV installations that ensure the minimization of conflicts and enhance sustainability and public acceptance.

In summarizing key issues raised in the rural development context, all papers highlight the importance of spatially-aware, integrated, and multi-dimensional approaches to rural and agricultural development, highlighting regional disparities, the critical role of infrastructure and investment, the environmental and social sustainability, and transparency in governance. These insights collectively inform strategies for balanced rural revitalization and sustainable land use.

2.2. Carbon Emissions Management

Xie et al. [14] focus on the geographical pattern, evolution model, and driving mechanisms of carbon emission density from urban industrial land in the Yangtze River Economic Belt (YREB) of China. The research aims to provide key information and a basis for incorporating carbon emission density indicators into urban and territorial planning to achieve “carbon peaking and carbon neutrality” goals. Chen et al. [5] explore the factors influencing vegetation carbon sequestration across different regions of Beijing. They investigate the spatial and temporal variations in Annual Gross Primary Productivity (AGPP) in Beijing from 2000 to 2020, focusing on the impacts of urbanization and environmental factors. The study also discusses future urbanization and environmental management policies with the intention of promoting the carbon peak and the carbon neutrality process of ecological space management. Zhao et al. [22] analyze CO₂ emissions across different sectors (total, power, industry, transport) in 31 major Chinese cities from 2019 to 2022. Towards this end, they use a city-scale CO₂ emission correlation model and social network analysis. The study emphasizes the need for collaborative governance, targeted sector-specific policies, and technological innovation to achieve emission reduction and sustainable development goals. In the Cartography context, Touya et al. [12] elaborate on energy consumption related to the transfer of map tiles for web mapping. The article suggests focusing on the most frequent zoom levels and applying generalization to create lighter tiles, as well as promoting eco-friendly browsing behaviors to reduce energy use.

To summarize this section, all the papers conclude that spatial heterogeneity, multifactor influences, and dynamic interactions are key features of urban environmental phenomena, such as carbon emissions.

2.3. Handling Climate Change

Kotovs et al. [16] draw attention to beekeeping as a means for raising the productivity and profitability of agricultural crops and agricultural systems. In this respect, they present an experimental prototype that can be replicated at a universal scale; additionally, they demonstrate the feasibility of using crowdsourced spatial data in combination with web and GIS technologies to conduct a pre-exploration of proper and environmentally-responsible placement areas for apiaries, supporting the flourishing of precise beekeeping. Gaspari et al. [8] deal with glacier melting, which is deeply connected to mountainous local communities. The authors elaborate on web-based geospatial solutions that integrate qualitative and quantitative aspects of the transformation of the natural environment into a multi-level digital geospatial framework to enable the realization of the long-term changes of the Belvedere Glacier in the Italian Alps. The scope of the study is to provide an interactive visualization tool for displaying glacier retreat processes overtime, raising awareness of the tangible impacts of global warming. Gaia et al. [7] focus on the visualization of climate change (CC) impacts in Switzerland through an interactive digital map as part of the national Atlas of Switzerland (AoS). In this work, they elaborate on three specific types of CC impacts, namely the rise of the zero degree line, the evolution of glacial lakes, and the change in the flowering dates of plants. The ultimate goal of this effort is to use simple, clear-cut, and visual communication means—maps—in order to raise the awareness of laypeople to the implications of CC on the planet’s stability in a comprehensible, visible, and easy to grasp manner. Jiang et al. [20] elaborate on an emerging threat to regional water quality safety caused by high concentrations of chlorophyll-a (Chl-a) as a result of hydrological extremes in Jiujiang City, Jiangxi Province, China. A quantitative inversion model for estimating Chl-a concentration is developed for assessing water quality in various inland water types for each quarter from 2020 to 2022. The results demonstrate seasonal changes in Chl-a concentrations in inland waters due to extreme hydrological events, a result that is valuable for the sustainable management of water quality for the population.

In summary, these papers use contemporary means for handling and visualizing geospatial data in order to identify the distinct implications of climate change and use them for both raising public awareness and making more informed policy decisions.

2.4. Infrastructure

Yang et al. [17] attempt to assess the impact of Coal Mining Intensity (CMI) on Ecosystem Service Value (ESV). This is carried out by obtaining deep insight into ecosystem services and studying their interaction with coal resource development, using the Yellow River Basin as a case study area. The results demonstrate that the overlap between the coal mining area and basin has expanded, resulting in an increasing negative impact on the ESV. These results highlight the need to address the adverse effects of resource extraction on ecosystem services and the risk of ESV loss, demonstrating the value of spatial overlapping analysis in identifying ‘hotspots’ and the articulation of relevant policies for the protection of ecologically fragile basins. Wahba et al. [13] elaborate on a currently critical issue, caused by land scarcity: the optimization of site selection for serving urban, industrial, and tourist development objectives. In seeking to fulfill this goal, Kharga Oasis, Egypt, is used as a case study; and a GIS and a multicriteria decision-making approach are combined with multiple datasets, integrating in situ and laboratory-based data. As a result, a detailed site suitability map is created, using the analytic hierarchy process to develop a weighted GIS model that accounts for numerous elements and ultimately influences civil project design and construction. Wei et al. [18] explore the spatial pattern of basic educational services in the Yellow River Basin of China. Basic educational services are perceived as a crucial component of public services, as well as a means for safeguarding individuals’ fundamental rights to survival and development and facilitating comprehensive human development. The study is based on a big data analysis model for sketching the layout of basic public educational facilities. The results display certain disparities, mostly influenced by the permanent population and the large proportion of tertiary industry.

Outcomes of this part stress the use of a variety of means and geospatial data for informing decisions as to infrastructure development in a sustainable, socially-fair, and resource-respectful way.

2.5. Transportation

Astrat & Cho [27] explore recent advancements in the generation and updating methods and techniques of high-definition (HD) maps within the rapidly growing field of autonomous driving. In addition, they discuss the existing challenges and future prospects of the technologies associated with autonomous vehicles and driving systems. Bi et al. [24] examine the decoupling state of traffic carbon emissions in Guangdong Province from 1999 to 2019, utilizing the Tapio decoupling index model. Their results indicate that traffic carbon emissions increased within the study area during the examined period. The study shows that the decoupling effect of traffic carbon emissions is mainly “weakly decoupled”, while the overall decoupling effect is not significant in the study area. The study also reveals that the production value of traffic and turnover volume are the most significant factors contributing to traffic carbon emissions. Miao et al. [25] describe the development of a comprehensive connectivity index system towards evaluating the inter-country connectivity of Latin America. The system is based on sea, road, air, and railroad transport modes, and uses actual trade volume as a comparison. They analyze the spatial pattern of connectivity in the study area by combining network analysis and visualization techniques. The results indicate the main cross-border transport types and the existing patterns of overall connectivity, as well as the roles of different countries in regional connectivity. Aprigliano et al. [3] present a method which combines a multicriteria GIS-based analysis with an experimental study in the municipality of Valparaíso (Chile) for the evaluation of potential routes and the possibility of increasing the power limitations for non-motorized mobility. Their results suggest that the variables of slope, traffic accidents, intersections, and street directionality impact the viability and safety of E-bike users. The study emphasizes the necessity of adapting urban mobility policies to each city’s topographical characteristics. Li et al. [9] examine the characteristics of the bus network in Beijing during the period 2006–2014 by combining multi-source spatiotemporal data. Their results show that the bus network has extended from the central urban areas to peripheral regions within the study area. The study indicates that administrative boundaries and the layouts of ring roads greatly affect bus network characteristics. Additionally, the study demonstrates that bus stops are characterized by high levels of clustering and irregular development patterns. Misthos & Krassanakis [10] present an integrated method and a geoprocessing tool in Python for highway route characterization, based on landscape composition and visual significance. In particular, this method leads to the characterization of segments of highway routes according to the dominant element of the visible landscape by employing spatial aggregation approaches. The introduced method is applied in a peri-urban area in the Attica region (Greece), while the produced results are visualized through an interactive web map, which serves as an exploratory tool for summarizing the landscape character of the selected highway.

2.6. Urbanization

Chen et al. [6] put forward a methodology of geospatially analyzing a multi-level and multi-objective composite ecological network, based on red space (tourism resources for slow walking), green space (public/urban green space), and blue space (water-related natural and man-made spaces). This study constructs a composite ecological network under urban–rural integration in Dali City (China). A major contribution is in proposing the “point, line, and surface” combination of the optimization scheme to coordinate ecological protection. Kang et al. [21] employed satellite-derived indexes to investigate socio-economic development and eco-environmental changes across a system of cities in the Loess Plateau, China. Geospatial methods are used to assess the relationship between urbanization and ecological factors. The results are particularly interesting and geographically diverse, as there is a very uneven development of different types of cities, with developed cities exhibiting signs of improved alignment between urbanization and ecological conditions. Mumtaz et al. [11] focus on the integrated impacts of significant land use/land cover (LULC) attributed to urbanization processes in the riverine coastal megacities of semi-arid Southern Asian regions that are particularly affected by climate change. The megacity of Karachi in Pakistan is used as a case study. LULC changes are monitored over the past three decades and simulated until 2025, with the incorporation of various sets of geospatial data, while flood inundation scenarios are also created. The study’s innovation lies in quantifying SDGs achievements and integrating LULC analysis with SDGs metrics through a quantitative methodology. Chatzi et al. [4] set out to examine spatial relations and potential conflicts, underscoring the insufficient protection of cultural heritage due to ineffective spatial planning and mass tourism development. Geospatial methods are used to quantify the impact of uncontrolled built-up area dispersion on the cultural heritage of islands, with a focus on the Southern Aegean region. The results lead to suggestions of regulating urban sprawl and tourism development, while taking into consideration the spatial impacts at various spatio-cultural levels. Leka et al. [26] introduce an innovative approach to evaluating overtourism by integrating geospatial technologies and the well-established PSR—Pressure/State/Response—model. The study applies this framework to assess overtourism impacts in insular regions, using Santorini as a case study. Geographic Information Systems (GISs), remote sensing techniques, and spatial indicators are used to map tourism pressures on several aspects of socio-spatial structure and the environment of the island. By integrating quantitative spatial data with qualitative insights, the framework offers a comprehensive tool for serving sustainable tourism planning purposes.

3. Future Research Directions

With humanity facing complex sustainability challenges, future research empowered by GIS and Cartography in the pursuit of sustainable development goals should leverage new technological capabilities, such as GeoAI, Digital Twins, and Smart Cities, while also investing in the ethical dimension of Geospatial Science. Several future research directions can be proposed:

• GeoAI and Machine Learning Monitoring: Future efforts should focus on developing more sophisticated methods for monitoring the SDGs using machine learning. The application of GeoAI in satellite image analysis significantly enhances the results [28] and improves the assessment of the SDGs’ indicators. Scientists should develop explainable AI models [29], tailored to diverse geographic and socio-economic contexts.
• Digital Twins and Smart Cities: In promoting the Sustainable Development Goals (SDGs), digital twins, i.e., dynamic, real-time 3D models of urban or environmental systems, can be highly beneficial [30]. By monitoring and predicting urban development trajectories and their associated costs, they can contribute to reducing key resource consumption, such as land, water, and energy. Smart cities offer tremendous potential for advancing the SDGs, since they provide strong and positive support for sustainable development achievements [31].
• Participatory and Ethical Cartography: Citizen Science and VGI can be utilized to enhance data collection in areas facing severe SDGs challenges, as seen in the case of Humanitarian OSM [32]. Accessible, inclusive, and effective visualizations should communicate complex sustainability issues for every part of the world within the framework of Ethical Cartography [33,34].

Future research in GIS and Cartography is expected to have a significant impact on achieving the Sustainable Development Goals (SDGs). Furthermore, since developing countries are confronted with significant obstacles in achieving the SDGs [35], their support through access to the evolving scientific knowledge and financial resources is also a critical dimension in the course of the universal effort towards the SDGs achievement.