Urbanization reshaped quantity, structure, and functions of cultivated land (CUL), while transforming demand and efficiency of construction land (COL). These changes drive both cultivated land utilization transition (CULT) and construction land utilization transition (COLT). The study innovatively develops the explicit-implicit interactive transition measurement and zoning research framework of CUL and COL. The CUL's implicit morphology specifically focuses on agricultural production function, while COL's is conceptualized as a complex integrating spatial agglomeration, intensive construction, and economic concentration. The study integrates carbon storage for CUL functionality and carbon emission intensity for COL intensity, achieving a comprehensive evaluation system. This county-level study targets Shandong section of the Yellow River Basin—a key CUL protection and high-quality development zone—addressing strategic priorities through finer-scale analysis. It investigates explicit-implicit interactive transition characteristics of CULT and COLT from 2000 to 2020 and innovatively implements interactive transition zoning. Results showed faster CUL loss in Jinan's urban core and northeastern Yellow River Delta, with more pronounced COL expansion in central and northeastern compared to western regions. CUL functionality rose significantly during 2015–2020, and COL intensity improved markedly during 2010–2015. The explicit-implicit interactive transition trended toward optimization for CULT, while COLT attained both transitional and optimized states. Strong CUL-COL explicit transition correlations occurred in southwestern plains. CUL functionality and COL intensity showed moderate coupling coordination. Based on these findings, interactive transition zoning informed regulatory strategies, supporting food security and land resource optimization.
Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This paper presents a deep reinforcement learning (RL) framework for optimizing land-use allocation in the Lake Malawi Basin to maximize total ecosystem service value (ESV). Drawing on the benefit transfer methodology of Costanza et al., we assign biome-specific ESV coefficients -- locally anchored to a Malawi wetland valuation -- to nine land-cover classes derived from Sentinel-2 imagery. The RL environment models a 50x50 cell grid at 500m resolution, where a Proximal Policy Optimization (PPO) agent with action masking iteratively transfers land-use pixels between modifiable classes. The reward function combines per-cell ecological value with spatial coherence objectives: contiguity bonuses for ecologically connected land-use patches (forest, cropland, built area etc.) and buffer zone penalties for high-impact development adjacent to water bodies. We evaluate the framework across three scenarios: (i) pure ESV maximization, (ii) ESV with spatial reward shaping, and (iii) a regenerative agriculture policy scenario. Results demonstrate that the agent effectively learns to increase total ESV; that spatial reward shaping successfully steers allocations toward ecologically sound patterns, including homogeneous land-use clustering and slight forest consolidation near water bodies; and that the framework responds meaningfully to policy parameter changes, establishing its utility as a scenario-analysis tool for environmental planning.
The Human Development Index (HDI) introduced by United Nations Development Programme (UNDP) offers a unique quantitative measure that encompasses advancements in three fundamental aspects of human development: health, education, and living standards. However, focusing on only three dimensions when evaluating human development performance of countries is not adequate in today’s digital world. This study proposes a data envelopment analysis (DEA)-based composite index to provide an innovation-integrated human development performance assessment tool for countries. The novel two-stage common-weight DEA-based approach proposed in here is applied in a case study examining the performance assessment of European Union (EU) countries. The first stage of the developed methodology consists of solving the novel commonweight DEA-based approach with HDI indicators as the outputs and the Gini coefficient as the input. At the second stage, innovation-based indicators from World Bank database are used to evaluate innovation efficiency of EU countries. The composite index that yields the complete ranking of EU countries in terms of innovation-integrated human development performance is computed as the product of the efficiency scores resulting from these two stages. The rankings produced by the proposed approach are compared with the HDI rankings as well as the results obtained from various common-weight DEA-based models.
First published online 27 November 2025
Viacheslav Davydenko, Anna Kavunska, Viacheslav Barba
The study focuses on the conceptual, theoretical, empirical and methodological foundations of a legal and economic nature, concerning the legal support for the activities of operational units of the National Police in preventing cybercrime, in the context of economic globalisation and existential challenges. Methodology. The present study employed both general and special methods of cognition. Utilising the dialectical method, the author evaluated the essence of countering cybercrime by operational police units in terms of its prevention and prevention of these offences in the legal and economic planes, according to a diverse range of parameters. The analysis established the foundations for a multidimensional study of all the characteristic features of cybercrime prevention in the context of economic integration, in terms of economic and legal etymology. The synthesis established the conditions necessary for the generalisation of the distinctive features of the activities of police operational units. The formal legal method enabled the correct interpretation of the content of legal acts defining the general and special legal regimes of preventive activities of operational police units within the context of economic globalisation and existential challenges. The purpose of the article is to provide a comprehensive analysis of the potential areas for improvement in the activities of the operational units of the National Police in order to prevent cybercrime in the context of economic globalisation and existential challenges. The results of the study demonstrated that the role of the operational units of the National Police in preventing cybercrime in the context of economic globalisation and existential challenges encompasses a range of complex measures in various areas of activity of the relevant police unit, primarily in ensuring cybersecurity. It has been determined that there are specific areas in which the operational units of the National Police can enhance their efforts to combat cybercrime. These areas have been identified in the context of economic globalisation and existential challenges. Conclusion. The advent of cybercrime can be attributed to the prevailing technological transformations in the economy, particularly with regard to the dissemination of information as the primary resource and catalyst for societal advancement. The author's position is that the implementation of economic policies aimed at curbing cybercrime should encompass the following measures: the establishment of a fair and balanced tax system, the formulation of a strategic economic development policy, the promotion of production-oriented initiatives, and the allocation of resources towards the enhancement of public services. From the standpoint of a company's economic security, measures to prevent cybercrime are crucial, due to both local and global economic factors. The analysis of cybercrime legislation enabled the identification of measures of general and special competence taken by the operational units of the National Police. Concurrently, within the legislative framework on national security, which encompasses cybersecurity, the National Police is delineated as a subject of counteraction to such crime, signifying a specialised competence. Concomitantly, the general competence in combating and preventing cybercrime is reflected in the primary function of the National Police, namely to ensure public safety and order, protect human rights and freedoms, the interests of society and the state, and combat crime, including in cyberspace. The primary focus of the implementation of the special competence of operational police units is the Cyber Police Department, which is an integral component of the National Police. The Cyber Police Department is responsible for conducting comprehensive operational and investigative activities as a component of the broader strategy to prevent cybercrime. The authors support the view that the following measures, carried out by operational police units, stand out as effective means of countering cybercrime under conditions of existential challenges associated with armed aggression. These measures include counterintelligence, operational and investigative work, and procedural work to counter relevant information threats; the introduction of incentive measures aimed at creating their own information product; the development of their own information and telecommunications infrastructure; and the establishment of communication between civil society and law enforcement agencies in this area.
Debvrat Varshney, Vibhas Vats, Bhartendu Pandey
et al.
Land cover, both present and future, has a significant effect on several important Earth system processes. For example, impervious surfaces heat up and speed up surface water runoff and reduce groundwater infiltration, with concomitant effects on regional hydrology and flood risk. While regional Earth System models have increasing skill at forecasting hydrologic and atmospheric processes at high resolution in future climate scenarios, our ability to forecast land-use and land-cover change (LULC), a critical input to risk and consequences assessment for these scenarios, has lagged behind. In this paper, we propose a new paradigm exploiting Generative AI (GenAI) for land cover change forecasting by framing LULC forecasting as a data synthesis problem conditioned on historical and auxiliary data-sources. We discuss desirable properties of generative models that fundament our research premise, and demonstrate the feasibility of our methodology through experiments on imperviousness forecasting using historical data covering the entire conterminous United States. Specifically, we train a diffusion model for decadal forecasting of imperviousness and compare its performance to a baseline that assumes no change at all. Evaluation across 12 metropolitan areas for a year held-out during training indicate that for average resolutions $\geq 0.7\times0.7km^2$ our model yields MAE lower than such a baseline. This finding corroborates that such a generative model can capture spatiotemporal patterns from historical data that are significant for projecting future change. Finally, we discuss future research to incorporate auxiliary information on physical properties about the Earth, as well as supporting simulation of different scenarios by means of driver variables.
Christopher Ummerle, Antonio Giganti, Sara Mandelli
et al.
Remote sensing plays a crucial role in monitoring Earth's ecosystems, yet satellite-derived data often suffer from limited spatial resolution, restricting their applicability in atmospheric modeling and climate research. In this work, we propose a deep learning-based Super-Resolution (SR) framework that leverages land cover information to enhance the spatial accuracy of Biogenic Volatile Organic Compounds (BVOCs) emissions, with a particular focus on isoprene. Our approach integrates land cover priors as emission drivers, capturing spatial patterns more effectively than traditional methods. We evaluate the model's performance across various climate conditions and analyze statistical correlations between isoprene emissions and key environmental information such as cropland and tree cover data. Additionally, we assess the generalization capabilities of our SR model by applying it to unseen climate zones and geographical regions. Experimental results demonstrate that incorporating land cover data significantly improves emission SR accuracy, particularly in heterogeneous landscapes. This study contributes to atmospheric chemistry and climate modeling by providing a cost-effective, data-driven approach to refining BVOC emission maps. The proposed method enhances the usability of satellite-based emissions data, supporting applications in air quality forecasting, climate impact assessments, and environmental studies.
Grik Tadevosyan, Maksim Osipenko, Demetros Aschu
et al.
This paper introduces a safe swarm of drones capable of performing landings in crowded environments robustly by relying on Reinforcement Learning techniques combined with Safe Learning. The developed system allows us to teach the swarm of drones with different dynamics to land on moving landing pads in an environment while avoiding collisions with obstacles and between agents. The safe barrier net algorithm was developed and evaluated using a swarm of Crazyflie 2.1 micro quadrotors, which were tested indoors with the Vicon motion capture system to ensure precise localization and control. Experimental results show that our system achieves landing accuracy of 2.25 cm with a mean time of 17 s and collision-free landings, underscoring its effectiveness and robustness in real-world scenarios. This work offers a promising foundation for applications in environments where safety and precision are paramount.
The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysis, web analytics and technology partnerships for success in the digital marketplace. It also examines modern organisational strategies to help IT companies effectively implement marketing initiatives and adapt quickly to changing business landscapes. Methodology. This article is based on a theoretical and methodological review of the existing scientific literature on digital technologies, the marketing of digital products and services, and an overview of current technological and organisational solutions in the digital field. In addition, it includes a survey of marketing managers from renowned IT companies with the aim of delineating the typology of organisational structures within marketing departments. Results. Information delivery, data analytics, monitoring tools and web analytics are critical to digital marketing in IT organisations, facilitating the collection and analysis of data from multiple sources such as websites, social media and CRM systems. By leveraging big data and machine learning algorithms, it is possible to identify complex dependencies and predict consumer behaviour. Technological partnerships and collaborations with startups are becoming increasingly important for IT companies' marketing efforts, providing access to fresh ideas, technologies and a competitive edge. Organisational structures in the marketing departments of IT companies emphasise agility and cross-functional teamwork, often using agile methodologies. This promotes adaptability to market changes. Marketing structures typically include inbound approaches, flexible growth-oriented setups, and streamlined hierarchies. Practical implications. These marketing tools and organisational methods are recommended for implementation in the marketing departments of IT companies. The correlation between informational and organisational capabilities contributes to the achievement of marketing goals and the competitive advantage of IT companies in the marketplace. Scrum and Kanban, widely used agile frameworks, are not limited to technology companies but are also common in financial services and retail. Value / Оriginality. In the context of the ongoing military conflict, successful operation of Ukrainian IT companies in the modern world requires not only technological superiority, but also effective marketing and a well-organised internal structure. To accelerate the recovery of the Ukrainian IT sector and improve existing practices, the following recommendations have been made.
Economics as a science, Management. Industrial management
Lu'liyatul Mutmainah, Listia Andani, Ela Susilawati
The mosque has so far been known only as a place of worship such as prayer and recitation by Muslims. History records that during the time of the Prophet, the mosque was also the center of government, economic center, education center, and others. Some mosques are also tourist areas that provide more economic value so that they can improve people's welfare. However, tourist areas often cause problems related to waste, water use, and others. Understanding of the circular economy that can provide sustainable benefits is still not widely known and implemented, including for managing mosques. This study aims to analyze and propose an optimization model for mosque-based circular economic empowerment to achieve a sustainable economy. The research uses a qualitative approach with literature studies and in-depth interviews with related parties. The results of the study show that empowering mosques based on a circular economy will not only have a positive impact on places of worship but also the economic, social, and environmental sectors. For example, managed mosque waste can provide economic value. In addition, the use of ablution water can be reused for land irrigation and fish farming. The synergy between the government, universities, communities, and the industrial world can be carried out to implement this mosque-based circular economy. The results of this study can be used as a basis for recommendations and a pilot project for implementing mosque-based circular economic empowerment.
This study aims to compare the soil quality indexing model by adding and weighting the soil under different land uses and slope positions on the southwest slope of Mount Merapi, Indonesia. Soil sampling was carried out based on a landscape analysis divided into four geomorphological units (slopes): upper, middle, lower and foot slopes. The research design was nested where the soil sample was located (surface soil 0-30 cm). Based on the research results, soil quality indices (SQI) of forest on the upper slopes is very high. SQI of dry fields on the middle, lower and foot slopes is low to medium. SQI of mixed gardens on the middle and lower slopes is low to medium. SQI of snake fruit land on the middle, lower and foot slopes is medium to high. SQI of grassland on the lower slopes is medium to high, and SQI of paddy fields on the foot slopes is medium to high. Weighted soil quality index (SQIw) has a higher correlation (R2 = 0.90) and can predict soil quality better than the adding soil quality index (SQIa) model (R2 = 0.76). Indicators that most influence soil quality are the percentage of sand, total N, C-POM, C-Min, pH, and aggregate stability, that indicators are entirely influenced by organic matter, site-specific management to maintain SQI by maintaining organic matter. The selected indicators in this study can be used to determine the SQI in similar areas.
Owing to the rapid urbanization combined with global climate change, dramatic land-use change in coastal watersheds is occurred, which, in turn, cause the evolution of landscape patterns and threaten the valuable but fragile ecosystem. The coastal zone is characterized by severe cloud cover, frequent changes in land type, and fragmented landscape, so it is challenging to carry out the accurate landscape patterns analysis. To address this problem, this study employed the Google Earth engine cloud platform, Landsat time series, and landscape metrics in the Fragstats model to develop a comprehensive framework that integrates landscape pattern metrics and spatial analysis methods, considering both type level and landscape level. The Hangzhou Bay region was selected for conducting land-use classification and landscape patterns analysis. The results indicate that, during nearly four decades, with the continuous expansion of the urban, the urbanization process has accelerated, and the construction land has expanded by 6.93 times. By analyzing the evolution of landscape patterns, Hangzhou Bay heightened landscape fragmentation and patch shapes became more irregular caused by a trend toward intensified urbanization. The Shannon's diversity index continuously increased from 1.14 to 1.51, while the contagion index consistently decreased from 59.83% to 42.21%, suggesting an increase in land-use diversity, reduced aggregation, and extension tendencies between land patches, along with a decrease in the proportion of highly connected patches within the landscape. This study is anticipated to provide robust evidence for the rational planning of future development directions and the deployment of landscape ecological spatial services.