This research examines the intricate connection between tourism and environmental destruction in 28 Asian countries, concentrating on the non-linear impacts of tourism. Moreover, this study contemplates how tourism can mitigate the effects of economic growth on environmental decline. Westerlund, Johansen-Fisher, and Pedronico-integration tests are necessary to detect the co-integration connection between the proposed factors. The research also uses the Augmented Mean Group; the dynamic system generalized method of moments, and fully changed Ordinary Least Squares (OLS). These tools help address econometric and economic problems such as co-integration, dynamism, variation, inter-sectional dependence, and endogeneity. The results demonstrate a U-shaped non-linear connection between ecological footprint and Tourism in Asian nations. Primarily, the tourism industry can initially decrease environmental damage. However, as it increases in size, it can worsen the harm. Additionally, the study suggests that tourism negatively influences how economic growth affects ecological footprint. This research contributes to the existing literature on tourism’s effects on the environment. The research suggests that tourism significantly impacts the environment; therefore, initiatives to reduce damage should be aimed at tourism.

The tourism sector is exponentially expanding across the globe. Despite different forms of tourism, community-based tourism has evolved with new dimensions of development. Assessing the sustainable development of the sector is a top priority in order to adopt the new forms. Therefore, in this study, the association between community-based tourism and its sustainable development was measured under the lens of collaborative theory and social exchange perspective. Non-probabilistic judgmental sampling techniques were applied, and 201 respondents were assessed. Data analysis was conducted using structural equation modeling (SEM). The study grounded with residents’ perspectives and attested that community-based tourism directly enhanced residents’ economic conditions with a better environment, and the relationship between residents and tourists enhanced the tourism industry’s sustainable development. Stakeholders like government and local administrations play a significant role in exploring community-based tourism. This outcome of the research will be a substantial resource for local administrations, governments, researchers, policymakers and practitioners.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

This paper discusses the concept of creating a new reality using the approaches of smart cities to develop eco-cities, in which the necessary balance between nature and progress can be maintained. The authors propose that the concept of smart cities should be used as a tool for the creation of eco-cities, and argue that the positive synergies between the two will be strongest if the smart concept acts as a tool for the creation of eco. The core elements of a smart eco-city are identified as smart sustainable use of resources, a smart sustainable healthy community, and a smart sustainable economy. The results of the article were the foundation for the development concept for Vision Bratislava 2050—the vision and strategy for the development of the capital of the Slovak Republic. The authors also discuss the challenges of transforming cities into smart eco-formats, including the need for digital resilience in the face of potential cataclysms. They suggest that this is a promising area for further research into the concept of smart eco-cities.

In the domains of geological study, natural resource exploitation, geological hazards, sustainable development, and environmental management, lithological mapping holds significant importance. Conventional approaches to lithological mapping sometimes entail considerable effort and difficulties, especially in geographically isolated or inaccessible regions. Incorporating geological surveys and satellite data is a powerful approach that can be effectively employed for lithological mapping. During this process, contemporary RS-enhancing methodologies demonstrate a remarkable proficiency in identifying complex patterns and attributes within the data, hence facilitating the classification of diverse lithological entities. The primary objective of this study is to ascertain the lithological units present in the western section of the Sohag region. This objective will be achieved by integrating Landsat ETM⁺ satellite imagery and field observations. To achieve our objectives, we employed many methodologies, including the true and false color composition (FCC&TCC), the minimal noise fraction (MNF), principal component analysis (PCA), decoration stretch (DS), and independent component analysis (ICA). Our findings from the field investigation and the data presented offer compelling evidence that the distinct lithological units can be effectively distinguished. A recently introduced geology map has been incorporated within the research area. The sequence of formations depicted in this map is as follows: Thebes, Drunka, Katkut, Abu Retag, Issawia, Armant, Qena, Abbassia, and Dandara. Implementing this integrated technique enhances our comprehension of geological units and their impacts on urban development in the area. Based on the new geologic map of the study area, geologists can improve urban development in the regions by detecting building materials “aggregates”. This underscores the significance and potential of our research in the context of urban development.