Environmental Planning Research Articles

Path Planning Based on Artificial Potential Field with an Enhanced Virtual Hill Algorithm

The artificial potential field algorithm has been widely applied to mobile robots and robotic arms due to its advantage of enabling simple and efficient path planning in unknown environments. However, solving the local minimum problem is an essential task and is still being studied. Among current methods, the technique using the virtual hill concept is reliable and suitable for real-time path planning because it does not create a new local minimum and provides lower complexity. However, in the previous study, the shape of the obstacles was not considered in determining the robot’s direction at the moment it is trapped in a local minimum. For this reason, longer or blocked paths are sometimes selected. In this study, we propose an enhanced virtual hill algorithm to reduce errors in selecting the driving direction and improve the efficiency of robot movement. In the local minimum area, a dead-end algorithm is also proposed that allows the robot to return without entering deeply when it encounters a dead end.

Efficient multi-robot path planning in real environments: a centralized coordination system

Efficient multi-robot path planning in real environments: a centralized coordination system

Policy lessons from green gdp convergence over five decades: Enhancing sustainability and economic outcomes

This study analyzes the convergence of Green GDP among 160 countries from 1970 to 2019, emphasizing the pivotal role of environmental policies in shaping sustainable economic outcomes. By comparing traditional and Green GDP (includes environmental degradation), this paper identifies distinct economic clusters or “convergence clubs” and reveals how policy-driven changes influence these classifications. The findings highlight the significant impact of environmental policies on economic convergence and propose applicative policy recommendations to foster sustainable growth, making this study essential for policymakers engaged in economic and environmental planning. This study demonstrates the long-term convergence of the selected countries' economic growth, influenced by their disparate commitments to sustainable practices and regulatory frameworks that govern environmental protection. Thus, regardless of the variations across countries and their environmental policies, diverse economic strategies tend to produce similar outcomes in the long term.

An improve crested porcupine algorithm for UAV delivery path planning in challenging environments

With the rapid advancement of drone technology and the growing applications in the field of drone engineering, the demand for precise and efficient path planning in complex and dynamic environments has become increasingly important. Traditional algorithms struggle with complex terrain, obstacles, and weather changes, often falling into local optima. This study introduces an Improved Crown Porcupine Optimizer (ICPO) for drone path planning, which enables drones to better avoid obstacles, optimize flight paths, and reduce energy consumption. Inspired by porcupines' defense mechanisms, a visuo-auditory synergy perspective is adopted, improving early convergence by balancing visual and auditory defenses. The study also employs a good point set population initialization strategy to enhance diversity and eliminates the traditional population reduction mechanism. To avoid local optima in later stages, a novel periodic retreat strategy inspired by porcupines' precise defenses is introduced for better position updates. Analysis on the IEEE CEC2022 test set shows that ICPO almost reaches the optimal value, demonstrating robustness and stability. In complex mountainous terrain, ICPO achieved optimal values of 778.1775 and 954.0118; in urban terrain, 366.2789 and 910.1682 and ranked first among the compared algorithms, proving its effectiveness and reliability in drone delivery path planning. Looking ahead, the ICPO will provide greater efficiency and safety for drone path planning in navigating complex environments.

The psychological distance effect in impact between online review-based tourism destination image and recommendation intention: a data mining approach

ABSTRACT A total of 8,725 reviews of three East Asian travel cities were collected from TripAdvisor, and, after extracting and quantifying the words corresponding to the tourism destination image (TDI), the causal relationship with the recommendation intention (RI) was verified. An integrated data analysis on the data from the three cities revealed that all images except cleanliness among TDI had a significant influence on RI. The Seoul review data analysis revealed the environment, culture/history, and travel plan factors at the low-level influenced RI, while the Seoul Palace review data analysis revealed that society, culture/history, transportation, and travel plan factors at the low-level influenced RI.

Water Environmental Risks Encountered during Urbanization in Valley Areas and the Potential Mitigation Effects of Utilizing Reclaimed Water

Since urbanization poses risks to regional environments, assessing and mitigating these risks is a challenge inherent to the urbanization process. The present study employs an adapted methodology based on the water environmental capacity (WEC) to assess the risks associated with the water environment in an urbanizing area located in a valley of the Chongqing municipality in Southwestern China, with a particular emphasis on its representative regional river. By utilizing hydrological data and planned parameters specific to this region, this study estimates the spatial and temporal distribution of the WEC and pollution loads in the river under various urbanization scenarios. It also explores the potential of the utilization of reclaimed water to mitigate these water environmental risks. The results indicate that the extent of urbanization exerts significant influences on the water environment and, therefore, requires meticulous planning. Areas experiencing higher levels of urbanization in the middle reaches of the river are associated with greater environmental risks compared to those observed in the lower reaches, while minimal risk is observed in the headwater. Due to the pollution loads brought about by precipitation, there is a higher level of environmental risk during the wet season (May–October) compared to the dry season. Utilizing reclaimed water can effectively reduce the pollution loads discharged into the river and is the most efficient means of mitigating environmental risks. To effectively manage environmental risks during urbanization in this valley area, further studies should prioritize examining the correlation between the scale of urban expansion and the river’s environmental carrying capacity. Additionally, it is imperative to establish realistic targets for the river water’s quality and discharge standards for the effluent from wastewater treatment plants. Furthermore, it is crucial to determine an appropriate level of utilization of reclaimed water and delve into the mechanisms behind the method used to assess the water environmental capacity. Despite these challenges, analyzing the spatial and temporal distribution of risk during urbanization and evaluating the mitigative effect of utilizing reclaimed water based on adapted assessments of the water environmental capacity hold reference value for the formulation of environmental management strategies and environmental planning. There is significant potential for this approach to have various applications.

Implementation of environmental management plans in the transport sector development projects: A case study of two mega projects in Bangladesh

This study assesses the Environmental Management Plans (EMPs) of two major urban transport megaprojects in Bangladesh, MRT Line-6 and BRT Line-3, implemented in Dhaka City to alleviate traffic congestion. The EMPs were evaluated using content analysis, SWOT analysis, and key informant interviews with environmental impact assessment experts. This research identifies the challenges and strengths of these projects, including occupational health and safety management, compensation measures for resettlement, handling cash grievances, emergency response plans, and organized environmental maintenance. The EMPs demonstrate efforts to compensate for greenspace loss by creating new ground coverage along the routes and planting trees and shrubs beneath elevated tracks. Notable weaknesses were observed, including a lack of integration between project proponents and regulatory authorities, absence of monitoring and reporting of impacts, health hazards caused by dust and emissions from equipment and project activities, insufficient traffic management plans, and inadequate health and safety measures for pedestrians during the construction phase. Several measures have been proposed for monitoring the operational phases by designated authorities, such as an environmental treatment plan for wastewater, solid waste management, water supply and sanitation, noise pollution control, and other emission control measures. Unfortunately, the study revealed that the restoration of blue spaces, such as water bodies and wetlands, affected by the megaprojects, was not adequately planned. This study further suggests that transparency and public participation should be ensured during preparation and implementation of EMPs of megaprojects. It also emphasizes the need for an adequate workforce and resources in the Department of Environment (DoE) to monitor EMP implementation effectively.

Direct and indirect effects of urbanization on vegetation: A survey of Yunnan central urban Economic Circle, China

Urbanization affects vegetation distribution by changing land cover. However, it also significantly changes urban water and heat conditions, affecting vegetation growth and development. Vegetation coverage is an effective indicator of vegetation growth. This study analyzed trends in vegetation coverage over the past 35 years, taking the Yunnan Central Urban Economic Circle as the study area. The study was based on applying the pixel dichotomy model and correlation statistical analysis on joint Landsat 5, 7, and 8 long- term remote sensing data, meteorological, and land use data. The direct and indirect effects of urbanization on vegetation coverage were also further explored by constructing an urbanization impact framework. The results revealed that: (1) The urban area during urbanization from 1986 to 2021 increased by 720.29 km2. There was a continuous decline in vegetation cover in and around urban areas, which intensified with accelerating urbanization, with the effect being more pronounced in suburban areas. (2) There were consistent increasing trends in urbanization’s direct and indirect effects on vegetation over the last 35 years, with average negative and positive effects of − 0.41 and 1.59, respectively. (3) Direct effects could mainly be attributed to the expansion of impervious surfaces, whereas the main indirect effect during the late urbanization period (2011–2020) was increasing average temperature. The average temperature showed a correlation coefficient with urbanization of 0.7767, and this relationship showed seasonal heterogeneity due to the significant growth of urban vegetation in summer and winter. (4) Cities that developed faster showed better environmental planning and construction. The direct and indirect effects of urbanization on vegetation during the early and middle stages were higher in cities developing at slow and moderate rates, with this trend reversing only in the later stages of urbanization. The results of this study can increase understanding of the effect of urbanization on vegetation coverage in the Yunnan Central Urban Economic Circle. They can assist in improving urban green spaces and urban ecological resilience.

A Design of Three-Dimensional Spatial Path Planning Algorithm Based on Vector Field Histogram.

In this paper, we present a novel three-dimensional spatial path planning algorithm based on the Vector Field Histogram* (VFH*) approach, specifically tailored for underwater robotics applications. Our method leverages the strengths of VFH* in obstacle avoidance while enhancing its capability to handle complex three-dimensional environments. Through extensive simulations, we demonstrate the superior performance of our algorithm compared to traditional methods, such as RS-RRT algorithm. Our results show significant improvements in terms of computational efficiency and path optimality, making it a viable solution for real-time path planning in dynamic underwater environments.

Potential use of Environmental Management Plan for the Sustainability of Coastal Area and Resources

The potential use of Environmental Management Plans (EMPs) for the sustainability of coastal areas has demonstrated significant benefits in enhancing environmental protection, regulatory compliance, and stakeholder engagement. However, challenges such as data collection, monitoring, and the effectiveness of mitigation measures must be addressed to fully realize the potential of EMPs. By investing in baseline data, implementing robust monitoring and adaptive management practices, enhancing stakeholder engagement, integrating EMPs with broader management frameworks, and allocating adequate resources, the effectiveness and sustainability of EMPs can be significantly improved.

Investigating the environmental capacity of soil heavy metals and its determinants in agro-pastoral regions of the qinghai-tibetan plateau.

Environmental capacity (EC) serves as the basis for environmental planning and management, as a key indicator for assessing environmental risk and quality, and as a foundation for achieving sustainable development. Studies on EC typically address agricultural or urban rather than pastoral areas, with few examining agro-pastoral areas. The EC of the Tibetan Plateau is particularly important, considering its importance as an agricultural area and ecological reserve. To address this gap, the Qingshizui area in Menyuan County, a typical agro-pastoral area on the Tibetan Plateau, was selected to quantify soil EC and its spatial distribution. In terms of the dynamic and static annual soil EC for this region, the heavy metals were ranked as follows, in ascending order: Cd, Hg, Co, As, Sb, Ni, Cu, Pb, Cr, and Zn. Most of the areas with high residual EC were in the west. For the 10 heavy metals, residual EC was significantly affected by geological background. For all the heavy metals except Zn and Hg, residual EC was significantly affected by soil type. The heavy metal elements in the agro-pastoral area's soil are mildly enriched, suggesting minimal human impact. The composite EC index of this soil is 0.98, indicating an intermediate EC and low health risk. This study underscores that integrating agriculture and pastoralism can optimize land use and mitigate ecological pressures associated with these practices when done separately. Our research provides valuable insights for resource optimization, environmental conservation, and enhancing the welfare of farmers and herders in the Qinghai-Tibet region.

New perspective on the recent challenges of regional environmental management plans under the background of deep-sea mining: from Northwest Pacific to global

New perspective on the recent challenges of regional environmental management plans under the background of deep-sea mining: from Northwest Pacific to global

Research, Analysis, and Improvement of Unmanned Aerial Vehicle Path Planning Algorithms in Urban Ultra-Low Altitude Airspace

Urban ultra-low altitude airspace (ULAA) presents unique challenges for unmanned aerial vehicle (UAV) path planning due to high building density and regulatory constraints. This study analyzes and improves classical path planning algorithms for UAVs in ULAA. Experiments were conducted using A*, RRT, RRT*, and artificial potential field (APF) methods in a simulated environment based on building data from Chengdu City, China. Results show that traditional algorithms struggle in dense obstacle environments, particularly APF due to local minima issues. Enhancements were proposed: a density-aware heuristic for A*, random perturbation for APF, and a hybrid optimization strategy for RRT*. These modifications improved computation time, path length, and obstacle avoidance. The study provides insights into the limitations of classical algorithms and suggests enhancements for more effective UAV path planning in urban environments.

Chemical exposure from the Hebei spirit oil spill accident and its long-term effects on mental health

While evidence indicates that exposure to oil spill incidents can affect mental health, it is unclear whether the mental health effects result from the incident itself or from exposure to associated chemicals. Oil contains chemicals that can impact mental health and these chemicals may have long-term effects due to their persistence in the environment. To address the gap in current knowledge, we conducted cross-sectional and prospective analyses of data from adults who participated in the Health Effects of the Hebei Spirit Oil Spill study. To assess chemical exposure from oil spills, we used indirect exposure indicators such as distance from the contaminated oil band to residences and duration of clean-up work, along with direct exposure indicators such as urine metabolite concentrations of volatile organic compounds and polycyclic aromatic hydrocarbons. Mental health assessments covered posttraumatic stress disorder (PTSD), depression, state anxiety, and trait anxiety. In the cross-sectional analyses, all four mental health issues were found to be associated with proximity to the oil band (p-value<0.05) and showed a positive association with clean-up work duration (p-value<0.05). Cox regression analysis revealed that higher urinary t, t-muconic acid levels were associated with an increased risk of depression (Hazard Ratio [HR] = 1.55, 95 % Confidence Interval [CI] = 1.05–2.28), and elevated 1-hydroxypyrene levels increased the risk of PTSD (HR = 1.60, 95 % CI = 1.03–2.48). Additionally, higher urinary 2-naphthol levels were associated with increased state anxiety (HR = 1.39, 95 % CI = 1.00–1.93) and trait anxiety (HR = 1.64, 95 % CI = 1.15–2.32). These associations persisted even after controlling for distance and duration variables related to psychosocial exposure. Our findings suggest that environmental disaster response plans should prioritize minimizing chemical exposure while also considering the duration and nature of the mental health impacts.

Evolutionary computation for unmanned aerial vehicle path planning: a survey

Unmanned aerial vehicle (UAV) path planning aims to find the optimal flight path from the start point to the destination point for each aerial vehicle. With the rapid development of UAV technology, UAVs are required to tackle missions in increasingly complex environments. Consequently, UAV path planning encounters more challenges, causing traditional deterministic algorithms to struggle to find the optimal path within a certain time. Evolutionary computation (EC) is a series of nature-inspired methodologies and algorithms, which have shown effectiveness and efficiency in solving many complex optimization problems in real-world applications. Recently, EC algorithms have been effectively applied in UAV path planning and have shown encouraging performance in obtaining high-quality solutions. Therefore, it is crucial to review the related research experience and literature in the field of using EC for UAV path planning. This paper presents a comprehensive survey to showcase the existing studies on EC in UAV path planning, especially in complex environments. The paper first proposes a novel taxonomy to categorize the relevant studies into three different categories according to the complex environmental properties of the application scenarios. These environmental properties include complex search space, complex time control, and complex optimization objectives. Then, the EC algorithms for UAV path planning in these complex environments are further systematically surveyed as constrained search space and large-scale search space in complex search space, dynamic UAV path planning and multi-UAV concurrent path planning in complex time control, and expensive objective and multiple objectives in complex optimization objectives. Finally, some potential future research directions for applying EC algorithms to UAV path planning are presented and discussed.

UTILIZING GOOGLE EARTH FOR ENVIRONMENTAL PLANNING: EXTRACTION OF POINT SOURCE LOCATIONS AT THE UPSTREAM OF SUNGAI SKUDAI CATCHMENT, JOHOR MALAYSIA

This study explores the application of geospatial technologies, specifically focusing on Google Earth (GE), to extract and mapping point source pollution in the upstream of Sungai Skudai Catchment (SRC). A thorough analysis of the locations of restaurants, launderettes, car washes, and workshops was made practical by the combination of Geographic Information Systems (GIS) tools with satellite images, which offers important data for environmental planning and water quality management. The research area, located in Johor, Malaysia, offers an example of the difficulties driven by rapid urban growth. This study provides comprehensive directions for extracting point sources, with a focus on verifying data via field surveys and Google searches. The upstream region was found to have 373 restaurants, 62 launderettes, 73 car washes, and 80 workshops. The dataset was further improved by the validation process, which determined any inconsistencies and added additional data. This study highlights the importance of field verification for improving point source pollution data accuracy. It also provides a base for comprehensive strategies for pollution management, land-use planning, and preservation efforts in rapidly changing environments, such as the Sungai Skudai Catchment.

An active SLAM with multi-sensor fusion for snake robots based on deep reinforcement learning

Snake-like robots can imitate the movement patterns of animals in nature and enter the space that traditional robots cannot enter, which adapt to environments that humans cannot reach, and expand the field of human exploration. However, it is often challenging to realize autonomous navigation and simultaneously avoid obstacles under an unknown environment, that is, active SLAM (Simultaneous Localization and Mapping). This paper proposes an autonomous obstacle avoidance method combined with SLAM based on deep reinforcement learning for a wheeled snake robot by using a multi-sensor. Firstly, we design a modular wheeled snake robot structure with lightweight materials based on orthogonal joints and build a three-dimensional model of a snake robot in Gazebo. Secondly, the SLAM based on two-dimensional LiDAR and IMU is used to realize autonomous navigation under an unknown environment and detect obstacles. At the same time, a Deep Q-Learning-based path planning method of the snake robot is proposed to realize obstacles avoidance during navigation. Finally, simulation studies and experiments show that the designed snake-like robot can realize effective path planning and environmental mapping in environments with obstacles. The proposed active SLAM algorithm improves the success rate of snake-like robot path planning, has better obstacle avoidance ability for obstacles, and reduces the number of collisions compared with the traditional A* and the sampling-based RRT* algorithms.

Generating high-resolution land use and land cover maps for the greater Mariño watershed in 2019 with machine learning

Land Use and Land Cover (LULC) maps are important tools for environmental planning and social-ecological modeling, as they provide critical information for evaluating risks, managing natural resources, and facilitating effective decision-making. This study aimed to generate a very high spatial resolution (0.5 m) and detailed (21 classes) LULC map for the greater Mariño watershed (Peru) in 2019, using the MORINGA processing chain. This new method for LULC mapping consisted in a supervised object-based LULC classification, using the random forest algorithm along with multi-sensor satellite imagery from which spectral and textural predictors were derived (a very high spatial resolution Pléiades image and a time serie of high spatial resolution Sentinel-2 images). The random forest classifier showed a very good performance and the LULC map was further improved through additional post-treatment steps that included cross-checking with external GIS data sources and manual correction using photointerpretation, resulting in a more accurate and reliable map. The final LULC provides new information for environmental management and monitoring in the greater Mariño watershed. With this study we contribute to the efforts to develop standardized and replicable methodologies for high-resolution and high-accuracy LULC mapping, which is crucial for informed decision-making and conservation strategies.

Refining Environmental Sustainability Governance Reports through Fuzzy Systems Evaluation and Scoring

Environmental, Social, and Governance (ESG) reports have become essential tools for enterprises to showcase their commitment to sustainable development and social responsibility. However, discrepancies persist regarding the criteria, assessments, and ratings disclosed in these reports. Moreover, there is a need for more objective methods to determine the weight distribution of indicator items. This study introduces a novel approach utilizing semantic variables in fuzzy theory and a multiple logic fuzzy inference system to develop an ESG environmental management performance assessment model. Therefore, this paper aims to develop a novel approach utilizing semantic variables and a multiple logic fuzzy inference system to quantitatively evaluate the sustainable performance of an environmental management plan. This research also aims to ensure fair and objective assessment outcomes, providing valuable guidance for enterprises in implementing performance management strategies. Key aspects investigated include the impact of membership functions, the extended utilization of semantic variables and logical rules, a comparative analysis of traditional weight assessments, and the limitations of applying fuzzy theory. Through comprehensive discussions and calculations, it is evident that fuzzy theory offers considerable flexibility in application. By tailoring fuzzy rules and selecting appropriate membership functions, diverse application scenarios can be accommodated. The Fuzzy systems evaluation and scoring EMP model generates EMP evaluation scores ranging from 1.76 to 8.29 for Gaussian membership, 1.80 to 8.19 for Triangular membership-A, 1.92 to 8.00 for Triangular membership-B, and 1.81 to 8.19 for Quadrilateral trapezoidal membership, based on simulated rating scenarios using the semantic variables of completeness and feasibility. This approach successfully incorporates distribution logic from subjective membership degrees to evaluate EMP scores. The findings demonstrate that fuzzy theory enables the consideration of multiple factors and facilitates the provision of objective-level membership, underscoring its potential in addressing complex evaluation challenges. This study illuminates the versatility of the fuzzy system theory, with its applications poised to extend across various domains.

How Can Ecological Product Value Realization Sustainably Enhance the Well-Being of Farmers? A Case Study of Xingyuan Village in China

Although recent years have witnessed a considerable increase in studies on the economic value of ecological products, the extant literature has overlooked the multidimensional enhancement of ecological product value from the perspective of farmers’ well-being. This research aims to examine how the Realization of Ecological Product Value (EPVR) serves as a crucial pathway to promoting the overall well-being of farmers in developing countries. Through a case study of a village in southeastern China, this research reveals that EPVR can enhance farmers’ well-being via various mechanisms as follows: (1) Economic solution to enrich farmers’ livelihood diversity, achieved by leveraging rural resource endowments and comparative advantages; (2) Fair social protection program enabling farmers to enjoy ecological benefits and further achieving urban-rural integration; (3) Environmental protection plan that balances production, living, and ecology; and (4) Grassroots governance tool promoting the governance ability to form collaborative governance model in a community of shared interests. This study offers theoretical support for enhancing human well-being through the realization of ecological product value in rural areas.