In order to address severe siltation and enhance urban green spaces in Xianyang Lake, the research offers a sustainable solution by proposing an innovative integration of ecological dredging and landscape transformation. The key findings are as follows: Firstly, an ecological dredging mechanism was established by directly transporting sediment from Xianyang Lake to its central greenbelt, reducing dredging costs and environmental impact while creating a sustainable funding cycle through revenue from eco-tourism activities. Secondly, the landscape artistic conception of the central greenbelt was significantly improved by leveraging the natural distance between the lakeshore and the greenbelt, offering diverse viewing experiences and enhancing the cognitive abilities and urban life satisfaction of tourists. Thirdly, the project demonstrated substantial economic and social benefits, including revenue generation from paid activities like boat tours, increased public awareness of biodiversity through ecological education, and improved community well-being. The central greenbelt also enhanced the urban environment by improving air quality, mitigating the “heat island effect,” and providing habitats for wildlife. This integrated approach serves as a model for sustainable urban development, offering valuable insights for cities facing similar ecological challenges. Future research should focus on long-term monitoring to further evaluate the ecological and socio-economic impacts of such projects.

Mangrove forests are vital to coastal protection, biodiversity support, and climate regulation. In the Niger Delta, these ecosystems are increasingly threatened by oil spill incidents linked to intensive petroleum activities. This study investigates the extent of mangrove degradation between 1986 and 2022 in the lower Niger Delta, specifically the region between the San Bartolomeo and Imo Rivers, using remote sensing and machine learning. Landsat 5 TM (1986) and Landsat 8 OLI (2022) imagery were classified using the Support Vector Machine (SVM) algorithm. Classification accuracy was high, with overall accuracies of 98% (1986) and 99% (2022) and Kappa coefficients of 0.97 and 0.98. Healthy mangrove cover declined from 2804.37 km² (58%) to 2509.18 km² (52%), while degraded mangroves increased from 72.03 km² (1%) to 327.35 km² (7%), reflecting a 354.46% rise. Water bodies expanded by 101.17 km² (5.61%), potentially due to dredging, erosion, and sea-level rise. Built-up areas declined from 131.85 km² to 61.14 km², possibly reflecting socio-environmental displacement. Statistical analyses, including Chi-square (χ² = 1091.33, p < 0.001) and Kendall’s Tau (τ = 1, p < 0.001), showed strong correlations between oil spills and mangrove degradation. From 2012 to 2022, over 21,914 barrels of oil were spilled, with only 38% recovered. Although paired t-tests and ANOVA results indicated no statistically significant changes at broad scales, localized ecological shifts remain severe. These findings highlight the urgent need for integrated environmental policies and restoration efforts to mitigate mangrove loss and enhance sustainability in the Niger Delta.

Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area’s most susceptible to erosion. The outcome of the study reveals that 3371.23 km², which constitutes 91% of the district’s total area, is identified as having mild soil erosion; in contrast, 154 km², or 4%, is classified as moderate soil erosion, while 92 km², representing 2.5%, falls under the high soil erosion category. Ad

Fintech as a three-dimensional phenomenon reflects the rapidly changing technological, financial and business environment. The bibliometric analysis of scientific articles allowed us to identify the main themes and create a map of the field of fintech influences. Systematization of scientific articles revealed the influence of economic development and socio-demographic inequality on fintech development. Government regulatory policies can accelerate the digitisation of financial services and financial inclusion and help the fintech sector face geopolitical challenges. Fintech’s impact was divided into three areas: financial stability and sustainable development, the business ecosystem and human behaviour. The research we summarised allowed us to identify the mechanisms through which fintech influences various fields. A complex approach to the influence of fintech enables us to understand the phenomenon and make better decisions.

Payment for forest ecosystem services (PFES) policy is a prevalent strategy designed to establish a marketplace where users compensate providers for forest ecosystem services. This research endeavours to scrutinise the impact of PFES on households’ perceptions of forest values and their behaviour towards forest conservation, in conjunction with their socio-economic circumstances and their communal involvement in forest management. By incorporating the social-ecological system framework and the theory of human behaviours in environmental conservation, this study employs a structural equations model to analyse the factors influencing individuals’ perceptions and behaviours towards forest conservation. The findings indicate that the payment of PFES significantly increases forest protection behaviour at the household level and has achieved partial success in activating community mechanisms to guide human behaviour towards forest conservation. Furthermore, it has effectively leveraged the role of state-led social organisations to alter local individuals’ perceptions and behaviours towards forest protection.