Smart Land Use Planning: Hotspots and Prospects

1. Introduction

Land use planning is a crucial tool for achieving the optimal allocation of land resources. However, traditional land use planning exhibits inadequacies in adaptability when confronting increasingly complex and diverse land use issues, such as resilient cities development [1], Urban Digital Twins (UDTs) [2], and smart city initiatives [3]. Therefore, it is imperative to transform land use planning from a traditional experience-based paradigm to a data-driven one and address current land use issues through Smart Land Use Planning. Smart land use planning is a diversified integrated intelligent system that is network-based, with software platforms as the core, data as the key element, and security as the fundamental guarantee. It integrates technologies including Geographic Information System (GIS), Internet of Things (IoT), and Artificial Intelligence (AI) [4]. It can provide core technical support for the sustainable utilization of land resources and the achievement of regional development goals.

2. Technology Hotspots: Core Links of Digital Empowerment

The key feature of smart land use planning lies in the integrated application of multi-source big data and diverse tools [4]. It emphasizes the integration of intelligent perception technology, intelligent decision-making technology, and intelligent operation technology throughout the entire life cycle of land use planning, forming a data-driven planning and management process. Ultimately, this enhances the rationality of land resource allocation in terms of spatial layout, functional configuration, and utilization efficiency, thereby facilitating the efficient allocation of land resources.

2.1. Intelligent Perception

Spatio-temporal data elements are essential components of smart land use planning, and accurate temporal information and geographical locations constitute the basic premise for sound land use planning. The process of integrating such multi-source heterogeneous data in real-time through multiple technologies is defined as intelligent perception. From the perspective of smart land use planning, intelligent perception technology encompasses two aspects: dynamic perception and systematic cognition. Specifically, it acquires fine-classification information of Land Use and Land Cover (LULC) via hyperspectral remote sensing satellites [5] and deploys Internet of Things (IoT) technology to monitor the dynamic changes in land use, thereby realizing the real-time collection, transmission, storage, and processing of multi-source data. Based on the acquired dynamic land use data, technologies such as big data and simulation can be employed for efficient data cleaning, summarizing the laws governing land use changes, establishing a systematic land use framework, and predicting future spatial patterns of land use to guide land use planning.

The process of intelligent perception technology significantly improves the efficiency and quantity of data acquisition for smart land use planning, thereby providing data support and a model foundation for subsequent smart land use decision-making and operations. The massive volume of accurate data obtained through intelligent perception technology can maximally support the application of land use planning in various scenarios. Ranging from smaller-scale village planning and urban planning to regional and even national-level planning, data matching the required resolution and coverage can be obtained, forming a complete technical chain. Thus, intelligent perception technology serves as the foundation of smart land use planning.

2.2. Intelligent Decision-Making

In the past, the decision-making subjects of land use planning were typically governments, public organizations, or individuals. However, smart land use planning breaks the limitations of a single and relatively isolated subject in the traditional planning process. Specifically, through intelligent decision-making technology, it innovates decision-making tools and platforms to achieve human–computer interaction and collaborative governance. Against the backdrop of intelligent decision-making, based on the results of data perception, smart land use planning introduces decision-making tools such as Artificial Intelligence (AI) [6] and Geographic Information System (GIS) as auxiliary technologies. These tools intelligently identify numerous land elements and conduct spatial correlation analysis, providing decision-makers with corresponding adjustment schemes for land use planning. Additionally, digital platform technology enables the integration of various departments into the public space of the network, realizing resource sharing and inter-departmental collaboration. This maximizes the compatibility between various types of land use planning and their “red lines,” avoiding conflicts between different plans.

The systematic application of this series of intelligent decision-making technologies not only rapidly generates scientific decision-making and planning schemes for decision-makers to choose from but also allows for flexible adjustments based on practical needs. Furthermore, digital platforms can engage more stakeholders in the land use planning process and expand their participation channels. Therefore, intelligent decision-making technology constitutes the core part of smart land use planning. It is pivotal to the full and effective utilization of planning data elements and provides directions and goals for the smooth implementation of subsequent land use planning.

2.3. Intelligent Operation

After making sound decisions, smart land use planning enters the practical operation phase. The key to this phase is to ensure the effective implementation of decision content, which requires the support of intelligent operation technology. Specifically, through technologies such as Digital Twins (DT) [7], Information and Communications Technology (ICT) [8], and City Information Modeling (CIM) [9], physical entities of land use that incorporate factors like population, environment, and economy are constructed. This enables bidirectional interaction between the ecological, economic, and social goals of planning and digital models, forming a closed feedback loop: the decision schemes and intervention strategies formulated by smart land use planning through systematic analysis can be implemented in the physical operation of land use scenarios. The relevant implementation results can then be dynamically monitored by means of technologies such as DT, ICT, and CIM, thereby supporting the closure of the loop. This continuous cycle enables iterative improvement and refinement, provides land governance strategies, and allows intelligent operation technology to quickly adapt to changing conditions.

By establishing an intelligent adaptive planning and operation system, intelligent operation technology effectively drives the full-process optimization of land use planning from implementation to dynamic monitoring. It not only ensures the efficiency of planning implementation but also achieves full coverage of the monitoring link and the sustainable development of the entire process. This multi-faceted capability connects elements such as land, economy, and ecology with strategic planning, creating an integrated framework. It enhances the adaptability and dynamic capabilities of the land use planning system, ensuring that planning plays a guiding role throughout the entire land use process and preventing the “absence” of planning.

In summary, in the context of smart land use planning, intelligent perception, intelligent decision-making, and intelligent operation constitute three core links. These three links fully cover the entire life cycle of smart land use planning. By embedding technical elements into the entire process of planning, approval, implementation, monitoring, and evaluation, they realize intelligent, efficient, and scientific development. This effectively overcomes the limitations of traditional land use planning in aspects such as data acquisition efficiency, decision-making scientificity, and implementation accuracy. More importantly, through the in-depth integration of digital technology and planning business, they significantly improve the efficiency of land resource allocation, ultimately providing technical support for smart land use planning to realize the digital empowerment process of “data-driven—scientific decision-making—efficient operation.”

3. Practical Challenges: Bottlenecks in Technology Implementation

Despite the increasing advancement of technical tools, the full-scale implementation of smart land use planning in the field of land use planning, which is characterized by strong policy relevance and complex interest relationships, still faces numerous challenges. Currently, the most prominent difficulties in smart land use planning stem from three aspects: institutional environment, human resource environment, and technological environment. These three factors collectively determine the level of intelligence and effectiveness of land use planning.

3.1. Challenges from the Institutional Environment

The government is regarded as a key player in smart cities. Similarly, the stability and continuity of the institutional environment, including the government and policies, also determine the degree of realization of Smart Land Use Planning. In practice, the implementation of smart land use planning requires a relatively long-term process. The application of technology, coordination of interests, and adjustment of goals also demand that policies remain relatively stable over a certain period to ensure that the planning path aligns with the needs of social development. However, due to differences in conditions and diverse goals across countries or regions, coupled with the rapid development of the social economy and science and technology, the weight of concepts such as ecological protection, human settlement optimization, and social equity continues to rise. This leads to timely adjustments in specific national development planning requirements, which in turn affect the application level and effectiveness of smart land use planning. For example, India’s smart city development relies on the top-down management model of the Special Purpose Vehicle (SPV) Model [10], which tends to lead to fragmented management in smart city development due to decentralized governance; the Chinese government implements the “integration of multiple plans,” and the integration of multiple planning systems such as Land Use Planning and urban-rural planning may lead to difficulties in historical data compatibility, affecting the role of technical coordination; Iran adopts exogenous Land Use Planning (LUP) [11], which emphasizes external perspectives and tends to be disconnected from the country’s actual conditions, weakening the feasibility of technology application. While these policies align with national development needs, they also alter the application scope and value orientation of land use planning itself. This directly affects the goal-setting and scope of application of smart land use planning, thereby requiring it to possess greater resilience and adaptability.

3.2. Challenges from the Human Resource Environment

The relationship between land and people is an eternal topic in geography and many other disciplines. From the perspective of smart land use planning, challenges related to human resources also constitute an important issue that must be addressed, mainly reflected in two dimensions: the shortage of interdisciplinary talents for smart land use planning and the difficulty in coordinating multiple stakeholders. On the talent supply side, smart land use planning imposes interdisciplinary application requirements on practitioners’ knowledge structures. Practitioners must absorb and draw on knowledge from disciplines such as landscape ecology, economics, and management in terms of concepts, master various digital technology planning tools in terms of skills, and achieve refinement in intelligent perception, precision in intelligent decision-making, and accurate calculation in intelligent operation in terms of goals. These requirements for interdisciplinary talents impose significant pressure on practitioners. Practitioners must invest more time and effort to master these technologies, which directly prolongs the process of practical implementation of advanced planning technologies and affects the intelligent transformation of land use planning. Meanwhile, the development of smart land use planning involves various stakeholders, such as governments, investors, and citizens. These stakeholders have distinct and strong interest demands, and their understanding of planning goals often varies, which easily leads to conflicts of interest demands. Current smart land use planning lacks efficient coordination mechanisms. Although smart planning technologies can provide data support for conflict resolution and expand channels for public participation in governance, they are unable to directly balance the demands of all parties. This goal of considering multiple demands in the process of technology application also poses challenges to smart land use planning.

3.3. Challenges from the Technological Environment

The most significant challenges faced by smart land use planning have always centered on the application of technology. To a certain extent, the intelligentization process is a process of technology application. Therefore, the feasibility of technology must be a key consideration. This feasibility not only encompasses the connotation of technology application but also requires that technology conforms to social value concepts, both of which constitute major technological environment constraints for smart land use planning. On one hand, the regional environments covered by land use planning exhibit significant heterogeneity. Land use planning technologies must be able to accurately adapt to the complex and diverse environments of different regions. For example, cloudy climates in basin areas affect remote sensing monitoring, which tends to reduce the accuracy of remote sensing images. This requires the exploration of more media for monitoring planning targets in terms of technology, but this will significantly increase the cost of applying land use planning technologies. On the other hand, intelligent technologies may trigger social concerns. For instance, the development of smart cities requires tracking vehicle information [12], and such data tracking may give rise to issues related to data privacy and security. The protection of privacy will restrict the application scope and scenarios of intelligent planning technologies. Alleviating the contradiction between data security and planning accuracy requires smart land use planning to explore diverse technical paths that balance security and practicality and meet the dual needs of technology application and social values.

In summary, the bottlenecks in the implementation of smart land use planning technologies are not caused by a single factor but result from the interweaving and mutual constraints of the three environments: institutional, human resource, and technological. Furthermore, these three aspects do not exist in isolation. Policy adjustments at the institutional level may exacerbate the difficulties in updating interdisciplinary talents, while issues such as privacy concerns at the technological level also require institutional guarantees and public collaboration for resolution. This implies that future research and practice must be based on the interconnections among these three environments and construct integrated solutions to effectively overcome the current predicament of technology implementation.

4. Future Prospects: Outlook on Smart Governance

To realize its core value and large-scale application, effective smart land use planning must systematically address the aforementioned institutional, human resource, and technological issues. The resolution of these issues requires relying on the collaborative response of the three rather than isolated policies. This will promote the normalization of smart land use planning, making it a core force supporting the coordinated development of urban and rural areas, efficient resource utilization, and the achievement of mutually beneficial outcomes in ecological protection.

To address the pain point of enhancing the resilient governance capacity of smart land use planning amid challenges from the institutional environment, a conceptual shift is necessary to avoid overemphasizing physical and technical aspects [13]. Policy changes stem from the dynamic allocation of resources, and the resilient governance of planning requires embedding value concepts such as social sustainability and social justice into the entire technical process, enabling smart land use planning to obtain reliable long-term guiding capabilities. For example, guided by the goal of sustainable development, Shenzhen, China integrates smart city development technologies [14] into urban planning; through the combination of technology and green development goals, the planning becomes more adaptable when facing ecological pressures; the African Great Green Wall (GGW) Initiative, as a form of land use planning [15], emphasizes the combination of long-term security and stability of Land tenure security with social sustainability, significantly enhancing the resilience of planning in response to dynamic changes in power. This approach of binding land resource utilization with multiple goals can maximize the balance of allocation requirements for different resources. In the future development of smart land use planning, emphasis should continue to be placed on resource allocation issues, with priority given to their implementation. This will enhance the ability of planning to address complex issues and provide rigid support for the sustainable use of resources and social justice.

Focusing on the issues of talent scarcity and meeting the needs of stakeholders amid challenges from the human resource environment, future smart land use planning must prioritize the cultivation of personnel skills and engage more interdisciplinary talents in the land use planning process. This is not only an effective way to leverage public wisdom to solve problems and make up for the shortcomings of existing methods but also enables timely responses to citizens’ demands, emphasizing public participation and social inclusion. The form of Participatory Budgeting [16] can promote the integration of social capital, social inclusion, and mainstream pluralism in the decision-making process into the content of land use planning. These characteristics are conducive to the development of a democratic and diversified spatial pattern of land use planning, thereby facilitating the formulation of more inclusive and high-satisfaction land use planning schemes.

To address the current challenges faced by smart land use planning at the technological level, such as insufficient diversification and weak scenario adaptability, future efforts need to promote the diversified expansion of the technology system. Meanwhile, the iteration of land use planning tools has progressively accelerated [17], requiring continuous dynamic optimization in practical applications to adapt to the core scenarios of land use planning. In this process, the effective implementation of technology is only a basic requirement; the more core aspect lies in that technology application must carry social value orientations. This requires the construction of social participation mechanisms in the technical framework, integrating public demands into the technology embedding link throughout the entire planning process, and maximizing the engagement of multiple stakeholders in the formulation of land use planning schemes. Ultimately, technology will break through the attribute of single tool integration and become a core link connecting multiple values.

In the face of the three core challenges, namely institutional, human resource, and technological, future smart land use planning needs to construct systematic solutions through the aforementioned measures and promote the collaborative governance of the three. This in-depth coupling of “institution—human resource—technology” can not only effectively resolve the current pain points and difficulties in planning practice but also promote smart land use planning to form an integrated system with resilience, inclusiveness, and sustainability. Ultimately, it will provide planning guarantees for countries or regions to utilize land resources in a rational and efficient manner, achieving goals such as coordinating economic development and land resource allocation, and ensuring the sustainable use of land. Furthermore, the advancement of smart land use planning from theory to practice represents an inevitable trend in the integration of empirical scientific concepts of land resource management with advanced technologies. The human-land relationship follows complex laws; future smart land use planning must adopt more advanced technologies and concepts, coordinate the demands of different stakeholders in a more equitable manner, and plan the future of land resources in a more sustainable way.