Search Results (1,088)

Forest frequentation is associated with benefits for human health, warranting the importance of forest-based health practices. These practices can be classified into four categories: connection with nature (e.g., Shinrin-Yoku, yoga, and meditation); sports, outdoor, and adventure activities; Indigenous health practices on the land; and professional consultations in a natural environment. The aim of this research was to better understand the social representations of the forest supporting these practices and the environmental characteristics that are favorable to them, as well as to examine the effects of these practices on the forests. We interviewed 28 forest-based health practitioners in Quebec and conducted four participant observation activities. Data analysis led us to five forest representations: an entity in its own self, an unfamiliar area, a place of attachment, a land at the heart of Indigenous cultures, and a tool to improve health. The results showed that favorable environmental characteristics varied according to the type of health practice. The presence of water (e.g., drinking water, lakes, and rivers) is favorable to all forest-based health practices and access to nature seems to be an issue for many practitioners. We also found that forest-based health practices were leaving traces in the forest and attempting to redefine the place of humans in nature. Full article

An innovative way to combat water scarcity brought on by population increase and climate change is rainwater harvesting (RWH), particularly in arid and semiarid areas. Currently, Pakistan is facing major water issues due to underprivileged water resource management, climate change, land use changes, and the sustainability of local water resources. This research aims to find out the suitable sites and options for RWH structures in the Quetta district of Pakistan by integrating the depression depth technique, Boolean analysis, and weighted linear combination (WLC) with hydrological modeling (HM), multicriteria analysis (MCA), a geographic information system (GIS), and remote sensing (RS). To find suitable sites for RWH, a collection of twelve (12) thematic layers were used, including the slope (SL), land use land cover (LULC), subarea (SA), runoff depth (RD), drainage density (DD), lineament density (LD), infiltration number (IFN), distance from built-up area (DB), distance from roads (DR), distance from lakes (DL), maximum flow distance (MFD), and topographic wetness index (TWI). The Boolean analysis and WLC approach were integrated in the GIS environment. The consistency ratio (CR) was calculated to make sure the assigned weights to thematic layers were consistent. Overall, results show that 6.36% (167.418 km²), 14.34% (377.284 km²), 16.36% (430.444 km²), 18.92% (497.663 km²), and 18.64% (490.224 km²) of the area are in the categories of very high, high, moderate, low, and very low suitability, respectively, for RWH. RWH potential is restricted to 25.35% (666.86 km²) of the area. This research also identifies the five (5) best locations for checking dams and the ten (10) best locations for percolation tanks on the streams. The conducted suitability analysis will assist stakeholders in selecting the optimal locations for RWH structures, facilitating the storage of water, and addressing the severe water scarcity prevalent in the area. This study proposes a novel approach to handle the problems of water shortage in conjunction with environmental and socioeconomic pressures in order to achieve the sustainable development goals (SDGs). Full article

This study integrates various remote sensing datasets to analyze environmental changes and their impacts on ecosystems across Pakhtunkhwa Province in Pakistan. Precipitation data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) dataset, along with vegetation health assessments using Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) data from the Landsat dataset, were used to comprehensively analyze the impact of vegetation dynamics on environmental footprints (i.e., temperature, precipitation, and LST). Land use maps, generated through supervised classification of Landsat images from 1985 to 2023, highlight significant changes in different land use classes, including vegetation and forest cover. Bayesian Network Modelling (BNM) and Dummy Variable Regression (DVR) methods were employed to assess the impact of vegetation (using NDVI time series) on environmental footprint and forest cover in particular. The results suggest that the NDVI generally increase the cooling effect across most of the study area, indicating that higher vegetation density is linked to a decrease in temperatures. This inverse relationship is also apparent in the connection between the NDVI and the LST, depicting a negative trend in surface temperature over most of the pixels/districts. The regression coefficients for the NDVI and the LST vary across different pixels, ranging from −5.3839 °C to 5.2697 °C, with standard deviations from 2.057 °C to 5.138 °C, reflecting a variability in the strength of this cooling effect. Similarly, for the relationship between the NDVI and the LST, coefficients range from −7.1513 °C to 6.6322 °C, with standard deviations between 1.612 °C and 4.155 °C. In contrast, NDVI and precipitation show a positive relationship, with regression coefficients ranging from 4.1686 °C to 44.3932 °C and standard deviations between 2.242 °C and 8.224 °C, suggesting greater variability in precipitation corresponding to vegetation dynamics. Additionally, forest cover generally correlates positively with precipitation in most pixels, but the variability across pixels emphasizes the complex nature of these relationships. The study identified substantial fluctuations in land use categories over the decades, indicating environmental shifts driven by both natural and human factors. BNM demonstrated a positive impact of vegetation dynamics on precipitation and a negative impact on both temperature and LST. On the other hand, the increase in forest cover, particularly due to the Billion Tree Tsunami Project, has a significant impact on the environmental footprint identified through DVR. By combining high-resolution datasets with advanced statistical techniques, this study offers key insights into the dynamic interactions between land cover, vegetation, and climate in the study region, providing valuable information for sustainable environmental management. Full article

Intercropping is widely utilised in agricultural production to enhance land use efficiency because of its benefits, such as heightened crop productivity and optimised resource utilisation. We investigated the effects of Pinto peanut/sisal (HST), Stylo/sisal (strT) and Grona styracifolia/sisal (JqT) intercropping systems on soil bacterial communities compared with sisal continuous cropping (CK) by using Illumina MiSeq high-throughput sequencing technology. The intercropping system significantly increased the total nitrogen (TN), soil pH and soil moisture levels and decreased the levels of available phosphorus (AP) and available potassium (AK). Minimal variations were observed in Shannon’s and Simpson’s diversity indices between the monoculture and intercropping systems as well as among different intercropping systems. The most abundant phyla observed within the four groups were Proteobacteria, Acidobacteria, Cyanobacteria and Bacteroidetes. At the phylum level, the relative abundances of Proteobacteria, Acidobacteria, Cyanobacteria and Bacteroidetes were 37.37–54.35%, 10.54–21.21%, 3.46–20.43% and 2.15–5.67%, respectively. Compared with ZCK, StrT, JqT and HST treatments led to higher abundance of Cyanobacteria (from 3.46% to 20.43%, 11.37% and 16.58%, respectively) and Bacteroidetes (from 2.15% to 5.67%, 5.21% and 5.10%, respectively). The results of the linear discriminant analysis of effect sizes demonstrated notable variations in the relative abundance of bacterial taxa among various intercropping systems. The dominant categories of the genus in strT and JqT groups were Blastocatellia and Blastocatellaceae-Subgroup4, while Firmicutes was the dominant category of the genus in the HST group. The structure of bacterial communities did not vary between intercropping and monoculture systems. The findings indicated that the impact of the intercropping system on the bacterial community structure was not contingent on the specific intercropping patterns employed. Full article

The China–Pakistan Economic Corridor (CPEC), as an important part of the Belt and Road Initiative, is of great significance for the promotion of sustainable development in the region through the study of land use change and the simulation of future multi-scenarios. Based on the multi-period land use data of the CPEC, this study firstly analyzed the spatial and temporal land use changes in the CPEC from 2000 to 2020 by using GIS technology, and, secondly, simulated the land use patterns of the CPEC under four scenarios, namely, natural development, investment priority, ecological protection, and harmonious development, in 2040 by using the Markov-FLUS model with comprehensive consideration of natural, socio-economic, and other driving factors. The results show the following: (1) The urban land, forest land, and grassland in the CPEC from 2000 to 2020 show an increasing trend, while the farmland, unutilized land, and water area categories show a decreasing trend. In terms of land use transfer changes, the most frequently transferred out is the conversion of unutilized land to grassland. (2) The FLUS model has high accuracy in simulating the land use pattern of the CPEC, and its applicability in the CPEC area is strong and can be used to simulate the future land use pattern of the CPEC. (3) Among the four different land use scenarios, the harmonious development scenario strikes a better balance between infrastructure construction, economic development, and ecological protection, and can provide a scientific basis for future land management in the CPEC, in order to highlight the importance of promoting economic growth and ecological protection and ultimately realize sustainable development. Full article

With economic development and coal resource exploitation, the area of mined-out zones is expanding continuously. The traditional waste disposal methods no longer meet the current demands, making it urgent to evaluate and reuse the surface stability of these mined-out zones. Surface residual deformation is a process where voids and fissures within the mined-out zones are gradually filled and compacted, affecting the overlying rock structure. Additionally, groundwater significantly impacts the strength of the overlying rock, leading to increased subsidence. Therefore, predicting surface residual deformation while considering the effects of groundwater is crucial for forecasting surface deformation and assessing stability in mined-out zones. This study, taking into account the characteristics of subsidence zones and the impact of groundwater on the compaction of fractured rock masses, uses equivalent mining height and probability integral methods to develop a predictive model for surface residual deformation incorporating groundwater effects. Predictions for the study area show that groundwater exacerbates surface residual deformation, with various deformation values ranging from 33.8% to 51.9%. The surface stability categories are divided into stable and essentially stable regions based on the residual deformation’s impact on the working face. This model fully considers the influence of groundwater on residual deformation in mined-out zones, refining existing mining subsidence theories, addressing deformation issues caused by adverse groundwater factors, and providing a theoretical basis for predicting residual deformation and evaluating stability in mined-out zones, promoting the sustainable development of land and environmental resources in mining areas. Full article

Wildfires pose a growing threat to Mediterranean ecosystems. This study employs advanced classification techniques for shrub fractional cover mapping from satellite imagery in a fire-prone landscape in Quinta da França (QF), Portugal. The study area is characterized by fine-grained heterogeneous land cover and a Mediterranean climate. In this type of landscape, shrub encroachment after land abandonment and wildfires constitutes a threat to ecosystem resilience—in particular, by increasing the susceptibility to more frequent and large fires. High-resolution mapping of shrub cover is, therefore, an important contribution to landscape management for fire prevention. Here, a 20 cm resolution land cover map was used to label 10 m Sentinel-2 pixels according to their shrub cover percentage (three categories: 0%, >0%–50%, and >50%) for training and testing. Three distinct algorithms, namely Support Vector Machine (SVM), Artificial Neural Networks (ANNs), and Random Forest (RF), were tested for this purpose. RF excelled, achieving the highest precision (82%–88%), recall (77%–92%), and F1 score (83%–88%) across all categories (test and validation sets) compared to SVM and ANN, demonstrating its superior ability to accurately predict shrub fractional cover. Analysis of confusion matrices revealed RF’s superior ability to accurately predict shrub fractional cover (higher true positives) with fewer misclassifications (lower false positives and false negatives). McNemar’s test indicated statistically significant differences (p value < 0.05) between all models, consolidating RF’s dominance. The development of shrub fractional cover maps and derived map products is anticipated to leverage key information to support landscape management, such as for the assessment of fire hazard and the more effective planning of preventive actions. Full article

To curb the impacts arising from the agricultural sector, the actions undertaken by policymakers, and ultimately by the farmers, are of paramount importance. However, finding the best strategy to reduce impacts, and especially assessing the effects of the interactions and mutual influence among farmers, is very difficult. To this aim, this paper shows an application of an agent-based model (ABM) coupled with life cycle assessment (LCA), which also includes multi-objective optimization of farming activities (including both crop cultivation and livestock breeding) from an economic and environmental perspective. The environmental impacts are assessed using the impact assessment scores calculated with the Environmental Footprint 3.0 life cycle impact assessment method and the study is conducted “from cradle to farm gate”. The model is applied to all the farms in Luxembourg, whose network is built utilizing neighborhood interactions, through which a parameter known as farmer’s green consciousness is updated at each time step. The optimization module is instantiated at the end of each time step, and decision variables (the number of livestock units and land allocation) are assigned based on profitability and specified environmental impact categories. If only profit optimization is considered (i.e., when farmers’ green consciousness is de-activated), the results show a 9% reduction in the aggregated environmental impacts (obtained as the Environmental Footprint single score) and a 5.5% increase in overall profitability. At the farm level, simulations display a clear trade-off between environmental sustainability and financial stability, with a 25% reduction in overall emissions possible if farming activities are carried out using the single score impact in the objective function, though this results in an 8% reduction in profitability over 10 years. Full article

The prevention of ecological risks is a critical determinant influencing sustainable development. Driven by rapid socio-economic development, the ecosystems of mountainous cities within agro-pastoral transition zones are increasingly vulnerable to complex disturbances, constituting a significant threat to sustainable development and human well-being. To help achieve sustainable development, it is essential to conduct research on addressing and mitigating ecological risks from the perspective of collaborative management networks in mountainous cities. Taking Zhangjiakou as the study area, this paper employed the land use transfer matrix and standard deviation ellipse methods to analyze the dynamic land use changes. Additionally, using Fragstats 4,2 to calculate the landscape indices with land use data, this paper evaluated the landscape ecological risk (LER) from 2000 to 2020. Furthermore, the social network analysis (SNA) method was utilized to explore the spatial correlation characteristics of the LER. The findings indicate that: (1) Cultivated land and grassland were the predominant land use types in Zhangjiakou. During 2000–2020, Zhangjiakou experienced significant changes in land use, dominated by the transfer among cultivated land, forestland, and grassland. It indicated that the issue of unstable ecological land use continued to exist. Affected by human activities, construction land showed a consistent upward trend, primarily concentrated in the urban built-up areas and areas along the Jing-Zhang Railway. (2) The LER of Zhangjiakou was predominantly characterized by low risk, medium risk, and high risk levels. In the transitional areas and foothills, the LER was relatively higher. During 2000–2020, Zhangjiakou showed a declining trend of LER. This suggested that the ecological protection policies in Zhangjiakou were effective, leading to an improvement in the local ecological environment. (3) The LER in Zhangjiakou demonstrated a spatial clustering pattern that exhibited an upward trend, which was supported by both spatial autocorrelation and the SNA analysis. In the LER collaborative management network, Xuanhua, Qiaodong, Qiaoxi, Wanquan and Zhangbei consistently upheld pivotal roles. Based on the number of inward and outward connections, 16 counties in Zhangjiakou were classified into four categories and three zones accompanied by corresponding recommendations. The findings of this study can serve as a valuable reference for subsequent landscape pattern optimization and ecological restoration in Zhangjiakou. Full article

The adoption of innovations in rice cultivation is presumed to operate in a rational manner, wherein new technologies or practices that successfully increase productivity or resource efficiency are adopted by target farmers based on cost-benefit calculations. In contrast, this paper examines a case of a public initiative to promote the system of rice intensification (SRI), wherein farmers widely disadopted the technique despite reporting increasing yields and reduced water consumption. To explain this paradox, we use the concept of the socio-ecological niche to examine a range of social and institutional factors that shape farmers’ decision-making. These included (1) access to land and labour; (2) water management capacity; (3) the quality of networks for knowledge sharing. The research suggests that small variations in these categories among otherwise similar smallholder households can markedly shape farmers’ risk perceptions and tangible outcomes with SRI. The implication is that agricultural innovations should be judged within their wider social context rather than on narrow evaluations of agronomic efficiency. Importantly, this must involve greater feedback mechanisms from smallholders with a variety of socio-economic profiles to help shape the character of agricultural innovations and extension strategies. Full article

Land use and land cover changes significantly affect the function and value of ecosystem services (ES). Exploring the spatial correspondence between changes in land cover and ES is conducive to optimizing the land use structure and increasing regional coordinated development. Thus, this study aimed to examine changes in land use and land cover (30 × 30 m) in Laos between 2000 and 2020 and their effects on ecosystem services value (ESV) using the Global Surface Cover Database land use data for 2000 to 2020, ArcGIS technology, and the table of Costanza’s value coefficients. The study results indicated that forest (79.5%), cultivated land (10.6%), and grassland (8.3%) were the dominant land use types in Laos over the past two decades. The forest area decreased significantly, while there were increases in other land types, and the forest was transformed into cultivated land and grassland. ES in Laos was valued at about USD 140–150 billion, with forest contributing the most, followed by cultivated land and grassland. ESV over the last two decades in Laos has increased by USD 3.94 million. Large values were assigned to regulating services (40%) and supporting services (14%). The ESV of food production, soil formation, and water supply increased, and the ESV of climate regulation, genetic resources, and erosion control decreased. In addition, the elasticity value of artificial surfaces was more prominent, with a more evident impact on ESV. For future development, Laos should rationally plan land resources, develop sustainable industries, maintain the dynamic balance of second-category ESV, and achieve sustainable economic and ecological development. This study provides a scientific basis for revealing changes in ESV in Laos over the past two decades, maintaining the stability and sustainable development of the environment in Laos, and realizing the sustainable use and efficient management of the local environmental resources. Full article

The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing the delays and capacity of airports. This framework encompasses a diverse array of authentic features pertaining to a civil airport for a mixture of both landing and departing flights. Being a decision support for the management of international airports, all sizes and weight categories of aircraft are considered permissible, each with their own unique service time and speed requirements in accordance with the global aviation regulations. The proposed discrete event simulation digital twin provides a real-time demonstration of the system performance with the possibility of predicting the future outcomes of managerial decisions. Additionally, this twin is equipped with an advanced and realistic 3D visualization that facilitates a more comprehensive understanding of the ongoing operations. To assess its efficiency in practice, the framework was implemented at an international airport. The statistical tests revealed the superior similarity between the proposed twin and the real system. Using this twin, we further optimized the studied system by analyzing its projected future performance under a set of scenarios. This resulted in a nearly 30% upgrade in the capacity of this airport while decreasing the expected delays by over 18% annually. Full article

Many cities are looking to adopt nature-based solutions (NBS) in greenspace to manage urban flooding and provide diverse co-benefits. Yet little research exists to inform the planning and design of park NBS. This study investigated NBS adoption in 58 public parks across major U.S. cities, using a 2022 survey by the Trust for Public Lands and other secondary datasets. We developed a typology to conceptualize a wide range of park NBS into five high-level categories by size/capacity, location of the gray–green spectrum, and design objectives. We then employed this typology to explore how a park’s adopted NBS types may relate to its landscape and sociodemographic contexts. We found that the most used type of NBS in the studied parks was ECO (a typology we defined as conserving, restoring, or creating ecosystems to mitigate flooding through ecological processes and functions), while the least used NBS type was ENG (a typology we defined as imitating natural infiltration processes but having no living elements). Further, parks that adopted ECO had significantly higher percentages of greenspace in the surrounding, as well as higher flood risks. We also found notable—though not statistically significant—evidence of potential associations between the type of NBS implementation in a park and its nearby neighborhoods’ income level, poverty, and population racial and age compositions. Moreover, our findings indicated that park visitors were more privileged compared to residents living near a park. We concluded that park contextual factors deserve more explicit consideration in the planning and design of NBS and discussed key implications of this study for practice and future research around park NBS for urban flooding. Full article

Scientific and logical classification is crucial for efficient information storage, management, and sharing. However, there are numerous existing classification systems for geographical entities, and the categories to which the same geographical entity belongs are often different in the business databases constructed according to different classification systems, which brings great obstacles to the management and sharing of geographical information. This study analyzes the complexities of multiple classifications of geographical entities and proposes a multi-classification model for geographical entities based on directed hypergraph theory. This model integrates and transforms different classification systems for the same geographical entity, creating a unified method for expressing multiple classifications. We also designed a data structure to support this unified expression. By implementing this model, the study enables the effective management of geographical entity data, facilitating improved sharing and the exchange of geographical information across different industries and applications. In practical, the multi-classification model proposed in this paper allows geographical entities from different classification systems to be stored and managed within a single geographical database. Data views are then used to provide tailored services to various industry sectors and business applications. This approach effectively reduces data duplication and enhances the efficiency of managing and sharing geographical information. Using land use classification as an example, this study constructs a unified expression of three different land use classification systems based on the multi-classification model. An experiment managing land use data for a specific city was conducted using this model in PostgreSQL. The results indicate that the proposed method not only reduces data redundancy but also improves the query efficiency by over 10% on average compared to the mainstream relational database management mode. This confirms the effectiveness and practical value of the proposed method. Full article

The examination of land-use change simulations across a range of scenarios represents a pivotal research avenue for the advancement of sustainable development analysis. Nevertheless, the extant research merely categorises all building land in a land-use classification into a single category, which is unable to provide a detailed analysis of the dynamic internal spatial form of the city. This paper analyses 17 LCZ land-use types in Guiyang City in 2013 and 2022, and reclassifies them into 7 RLCZ land-use types based on the height of urban building sites. It also proposes three possible scenarios of BAU, WLC, and SPC in 2040 and simulates their land-use changes using the PLUS model. The results demonstrate that (1) the size of low-rise buildings in Guiyang has declined significantly over the past decade; (2) built-up land within cities is significantly affected by drivers such as night-time lighting, topography, elevation, and roads; (3) the SPC scenario emphasises a development pattern of land intensification and a focus on high density in urban built space. It also protects the stability of the ecosystem. The scenario can provide informative suggestions for spatial pattern changes in rapidly developing cities such as Guiyang. Full article