In Côte d'Ivoire, the government and its development partners have implemented a national strategy to promote agroforestry and reforestation systems as a means to combat deforestation, primarily driven by agricultural expansion, and to increase national forest cover to 20% by 2045. However, the assessment of these systems through traditional field-based methods remains labor-intensive and time-consuming, particularly for the measurement of dendrometric parameters such as tree height. This study introduces a remote sensing approach combining drone-based Airborne Laser Scanning (ALS) with ground-based measurements to enhance the efficiency and accuracy of tree height estimation in agroforestry and reforestation contexts. The methodology involved two main stages: first, the collection of floristic and dendrometric data, including tree height measured with a laser rangefinder, across eight (8) agroforestry and reforestation plots; second, the acquisition of ALS data using Mavic 3E and Matrice 300 drones equipped with LiDAR sensors to generate digital canopy models for tree height estimation and associated error analysis. Floristic analysis identified 506 individual trees belonging to 27 genera and 18 families. Tree height measurements indicated that reforestation plots hosted the tallest trees (ranging from 8 to 16 m on average), while cocoa-based agroforestry plots featured shorter trees, with average heights between 4 and 7 m. A comparative analysis between ground-based and LiDAR-derived tree heights showed a strong correlation (R2 = 0.71; r = 0.84; RMSE = 2.24 m; MAE = 1.67 m; RMSE = 2.2430 m and MAE = 1.6722 m). However, a stratified analysis revealed substantial variation in estimation accuracy, with higher performance observed in agroforestry plots (R2 = 0.82; RMSE = 2.21 m and MAE = 1.43 m). These findings underscore the potential of Airborne Laser Scanning as an effective tool for the rapid and reliable estimation of tree height in heterogeneous agroforestry and reforestation systems.

This study examines the spatial distribution of consumption competitiveness and carrying capacity across regions, exploring their interrelationship and implications for sustainable regional development. An evaluation index system is constructed for both consumption competitiveness and carrying capacity using a range of economic, social, and environmental indicators. We apply this framework to regional data in China and analyze the resultant spatial patterns. The findings reveal significant regional disparities: areas with strong consumption competitiveness are often concentrated in economically developed regions, while high carrying capacity is notable in less populated or resource-rich areas. Notably, a mismatch emerges in some regions—high consumer demand is not always supported by adequate carrying capacity, and vice versa. These disparities highlight potential sustainability challenges and opportunities. In the discussion, we address reasons behind the spatial mismatch and propose policy implications to better align consumer market growth with regional resource and environmental capacity. The paper concludes that integrating consumption-driven growth strategies with carrying capacity considerations is essential for balanced and sustainable regional development.

Land use changes have been demonstrated to exert a significant influence on urban planning and sustainable development, particularly in regions undergoing rapid urbanization. Tehran Province, as the political and economic capital of Iran, has undergone substantial growth in recent decades. The present study employs sophisticated Geographic Information System (GIS) instruments and the Google Earth Engine (GEE) platform to comprehensively track and analyze land use change over the past two decades. A comprehensive analysis of Landsat images of the Tehran metropolitan area from 2003 to 2023 has yielded significant insights into the patterns of land use change. The methodology encompasses the utilization of GIS, GEE, and TerrSet techniques for image classification, accuracy assessment, and change detection. The Kappa coefficients for the maps obtained for 2016 and 2023 were 0.82 and 0.87 for four classes: built-up, vegetation cover, barren land, and water bodies. The findings suggest that, over the past two decades, Tehran Province has undergone a substantial decline in ecological and vegetative areas, amounting to 2.4% (458.3 km2). Concurrently, the urban area and the barren lands have expanded by 287.5 and 125.5 km2, respectively. The increase in water bodies during this period is likely attributable to the reduction of vegetation cover and dam construction in the region. The present study demonstrates that remote sensing and GIS are excellent tools for monitoring environmental and sustainable urban development in areas experiencing rapid urbanization and land use changes.

Cobalt-based sulfides have emerged as promising candidates for next-generation high-performance anode materials for lithium-ion batteries (LIBs) due to their high theoretical specific capacity and reversible conversion reaction mechanisms. However, their practical application is hindered by volume expansion effects and relatively low rate performance. Guided by theoretical principles, this study synthesizes nanoscale Bi/CoS-C and Bi/Co4S3-C (denoted as Bi/CS-C) composite materials using Co and Bi2S3 as precursors via a solid-state ball milling method. The electrochemical properties of these materials were systematically investigated. When employed as anodes for LIBs, Bi/CoS-C and Bi/CS-C exhibit excellent rate capabilities. At current densities of 0.1, 0.5, 1, 4, and 10 A/g, the reversible capacities of Bi/CoS-C were 939.2, 730.7, 655.6, 508.1, and 319 mAh/g, respectively. In contrast, Bi/CS-C exhibited reversible capacities of 760.4, 637.6, 591.9, 484.3, and 295.4 mAh/g, respectively. Moreover, Co4S3, as an active component, enables superior long-cycle performance compared to CoS. After 300 cycles at 0.2 A/g, the Bi/CoS-C and Bi/CS-C electrodes retained capacities of 193.1 and 788.8 mAh/g, respectively. This study demonstrates that nanostructure design and carbon-based composite materials can effectively mitigate the volume expansion issue of cobalt-based sulfides, thereby enhancing their rate performance and cycling stability. This strategy provides new insights for the development of high-performance anode materials for lithium-ion batteries and is expected to accelerate their practical application in next-generation energy storage devices.

The pressing need to redefine the tourism industry's relationship with nature and local communities has never been more critical. Ecotourism, as a paradigm of sustainable travel, holds transformative potential—not only for preserving our planet's fragile ecosystems but also for fostering local cultural and economic development. In this context, the integration of circular economy principles offers innovative pathways to enhance sustainability across the tourism sector. The application of circular economy frameworks in tourism not only reduces environmental impact but also enhances economic viability by creating closed-loop systems. My interest in this topic stems from a personal conviction: Tourism should leave a positive mark, one that enriches rather than diminishes the destinations we visit. This study delves into how the hotel industry can align itself with ecotourism principles by embracing innovative, sustainable practices that minimize environmental impact while delivering authentic, high-quality experiences for travelers. Through the lens of green energy, resource optimization, and cultural integration, the research demonstrates that sustainability is both an ethical responsibility and a pathway to long-term competitiveness in tourism. By supporting local economies and protecting natural heritage, the industry can shift from being a passive observer of environmental degradation to a proactive steward of change. This work serves as a call to action for stakeholders: Our choices today will define the landscapes and cultural legacies available to future generations.

Lighting conditions in learning spaces can affect students’ emotions and influence their performance. This research seeks to verify the influence of classroom lighting on students’ academic performance under different conditions and measurement forms. The research method is based on the systematic review of research articles establishing case analyses characterizing lighting intensity and color temperature to determine ranges favorable to a higher level of attention and long-term memory. Also, this study shows relevant aspects of the cases representative of a sustainable solution and proposes a research model. The study found light intensity values between 350 and 1000 lux and color temperatures between 4000 and 5250 Kelvin that favor attention. Long-term memory reached the highest levels of measurement by analyzing different parameters sensitive to lighting conditions and questionnaires. In conclusion, it was demonstrated that an adequate light intensity and color temperature based on the greatest possible amount of natural light complemented with Light Emitting Diode (LED) light generates optimal lighting for the classroom, achieving energy efficiency in a sustainable solution and promoting student well-being and performance.