Ecological Environmental Assessment Research Articles

Changes of the ecological environment status in villages under the background of traditional village preservation: a case study in Enshi Tujia and Miao Autonomous Prefecture

The preservation of Chinese traditional villages plays a crucial role in promoting the sustainable development of rural natural, cultural, and ecological environments. It is also a key strategy for achieving rural revitalization. Current research on traditional villages predominantly focuses on the realm of cultural landscapes, with an emphasis on preserving the cultural ecological value of these communities. In comparison, discussions on the quality of the ecological environment of villages from the perspectives of natural environment, economic environment, and the social organizational environment within regional development are relatively scarce. Our study employed GIS and RS technology and refers to the Technical Criterion for Ecosystem Status Evaluation. Several sub-indices of the ecological environment status, including the biological richness index, vegetation coverage index, water network density index, and land stress index, were selected to construct an ecological environment assessment model. This model was used to analyze the spatial–temporal changes in the ecological environment status of each county, county-level city, and traditional village within the jurisdiction of Enshi Tujia and Miao Autonomous Prefecture and its surrounding areas from 2010 to 2020. The study quantitatively evaluated the ecological environment status of each county, county-level city, and village in Enshi before and after the implementation of traditional village preservation policies. Through comparative analysis, the study revealed the impact of these policies on the natural ecological environment of the study area. The results indicated the following: (1) From 2010 to 2020, the ecological index (EI) values in the villages of Enshi Prefecture exhibited a similar trend to the EI values in the respective counties and county-level cities they are located in, although significant differences in magnitude of change were observed. (2) The EI values in the counties, county-level cities, and villages demonstrated greater variation in the latter five years of the decade (2015–2020) compared to the previous five years (2010–2015). (3) In 2020, the EI value of the villages experienced more significant changes compared to 2010, whereas the overall EI value of the counties and county-level cities showed less pronounced changes. The findings of this study suggest that the traditional village preservation policies implemented in Enshi Prefecture have both positive and negative impacts on the ecological environment of the surrounding areas of protected villages, and these impacts become increasingly evident over time. By comparing and analyzing the ecological changes in the surrounding areas of traditional villages in Enshi Prefecture with the overall ecological changes in the respective counties and county-level cities, our study employs quantitative analytical methods to delve into the impact of traditional village conservation policies on the natural ecological environment. It assesses the effects of policy implementation on the natural ecological environment of traditional villages, analyzing both the positive and negative impacts brought about by the execution of these policies, with the aim of effectively guiding the natural ecological conditions of traditional villages towards a more healthy trajectory of development.

Monitoring and Analysis of the Driving Forces Behind Ecological and Environmental Quality at the County Scale Based on Remote Sensing Data

Chaohu Lake, as an important freshwater lake in China, mainly relies on surface runoff for water replenishment, and the environmental quality of the surrounding towns directly impacts the environment of Chaohu Lake. Given the characteristics of rich water resources and extensive river networks in the lake area, this paper utilizes the GEE platform and selects Landsat data from 1992 to 2022, taking Feidong County, one of the lake’s inlets, as the study area. We used the water benefit-based ecological index (WBEI) to monitor and evaluate the ecological quality of the study area and employ the Sen+MK trend analysis method to analyze the spatial-temporal characteristics of ecological quality changes. To explore the driving forces behind the spatial-temporal changes in the WBEI, this study selects land use type, elevation, slope, aspect, potential evapotranspiration, annual average precipitation, annual average temperature, and five characteristic factors used in the construction of the WBEI as influencing factors. Using the geo-detector method, the study analyzes the driving forces behind the spatial-temporal changes in the WBEI in the study area. Results show that the WBEI, considering water efficiency, integrates waterbody information into regional environmental quality assessments, comprehensively reflecting the ecological environment of lakeside cities. From 1992 to 2022, the WBEI of the study region shows an increasing trend, with an improved area accounting for 1110.42 km2, or 51.21% of the total area. Among these, the significantly improved area covers 372.9789 km2 or 17.2% of the total area, while the slightly improved area covers 737.4411 km2, corresponding to 34.01% of the total area. Interaction types of influencing factors include bivariate enhancement and nonlinear enhancement, with the primary interactive factors affecting the ecological environment quality change in Feidong County being CLCD∩RVI; changes in land use and vegetation cover are the main driving forces behind the changes in ecological and environmental quality in Feidong County. From 1992 to 2022, the main land type transformations in the study area were from arable land to other land types, with a significant conversion of arable land to construction land, which is the main reason for the degradation of local ecological and environmental quality. The results of this study can provide practical references and theoretical support for ecological environment assessment, governance, and improvement in areas with abundant water resources.

A global annual simulated VIIRS nighttime light dataset from 1992 to 2023

Nighttime light (NTL) data is recognized as a reliable proxy for measuring the scope and intensity of human activity, finding wide application in studies such as urbanization monitoring, socioeconomic estimation, and ecological environment assessment. However, the substantial discrepancies and limited temporal coverage of existing NTL datasets have constrained their potential for long-term research applications. To address this, a Nighttime Light U-Net super-resolution network is proposed for the cross-sensor calibration between the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) NTL data and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. This network is applied to generate a continuous and consistent 500-meter global annual simulated VIIRS NTL dataset (SVNL) from 1992 to 2023. Validation results indicate a high confidence in the quality of the SVNL data, demonstrating its superiority in capturing longer NTL dynamics, maintaining higher temporal consistency, and presenting greater spatial detail compared with other NTL datasets. The SVNL could be utilized for prolonged human activities monitoring, and further research on regional or global urbanization.

Inventory List of Plant Diversity in Tropical Dry Deciduous Forest of Pench Tiger Reserve, Maharashtra, India

Aim: To assess the phyto diversity of pench tiger reserve, Maharashtra, India. Place and Duration of Study: Pench Tiger Reserve (PTR), June 2022 to December 2023. Methodology: The study was carried out by laying out quadratic sample plots in the PTR given by National Forest Inventory working plan code-2014 The plot size was 0.1 ha with 31.62 m x 31.62 m quadrats. Results: The study reveals a rich biodiversity comprising 863 species across 554 genera and 117 families, along with 8 varieties and 2 sub-species. The predominant taxa are herbs, accounting for 34.06% of species, followed by trees at 23.29%, climbers at 15.17%, grasses at 13.09%, sedges at 7.3%, epiphytic herbs at 0.8%, and bamboo at 0.2%. Fabaceae emerges as the most species-rich family in comparable studies, underscoring its ecological significance. Conclusion: The study emphasizes the importance of comprehensive biodiversity inventories for understanding and conserving tropical forest ecosystems. This research provides valuable baseline data essential for future ecological studies, environmental assessments, and effective.

Ecological Environment Assessment System in River–Riparian Areas Based on a Protocol for Hydromorphological Quality Evaluation

This paper aims to propose a method for the evaluation of the hydromorphological quality of a river and its riparian areas using three essential components: morphological characterization, river connectivity, and vegetation coverage. The method has been applied to the Tordera river in Catalonia, Spain. The general goal is to establish a riparian environment assessment tool by proposing parameters for each of the three mentioned aspects. This approach relies on data collection and evaluation with a simple computational procedure for eliminating subjectivity in the weighting and classification of evaluation levels. In the proposed methodology, the weights of the indicators are determined by the Distance Correlation-Based CRITIC (D-CRITIC) method, and the results are integrated using the Coupling Coordination Degree Model (CCDM). The proposed methodology quantifies assessment parameters and analyzes the environmental problems faced by riparian zones and rivers through the parameters and the results of the CCDM and thus can be used as a basis for proposing methods to improve the ecological situation. The results can be used for the enhancement of the coordination between the development of riparian resources and the requirements of ecosystem protection and utilization, and they can be used to promote the healthy development of ecological environments and the effective use of riparian resources.

Temporal and spatial variation patterns of chlorophyll a in marine ranching under global interannual events

Marine ecosystems are facing numerous environmental challenges due to global climate change. In response to these challenges, the establishment and growth of marine ranching has emerged as a pivotal solution. Chlorophyll a concentration (Chla) is recognized as a valuable indicator for the ecological assessment of marine ranching. This study focused on the spatiotemporal distribution of Chla and its response to environmental factors according to the dataset in the marine ranching area of Haizhou Bay (Lianyungang, Jiangsu, China) from 2003 to 2022. The results showed that Chla had a significant cycle of summer > spring > autumn and was distributed evenly in the central area of the marine ranching. During interannual changes, Chla patches were centered in the central region during 2014, 2015, and 2016. The Chla patches predominantly focused on the eastern area in 2018–2019, shifting to the western area in 2020–2021. The generalized additive model (GAM) indicated that salinity, depth, temperature, biological oxygen demand (BOD5) and SiO3−–Si were the main environmental factors affecting Chla during spring, summer and autumn. However, during El Niño events, salinity, depth, temperature, BOD5 and transparency became the main environmental factors. We concluded that salinity, depth and temperature consistently played a crucial role in determining Chla under various climate conditions, and SiO3−–Si and transparency will no longer be an environmental factor limiting Chla. In addition, The effect of interannual variability on upwelling and vertical mixing of water layers may potentially alter the spatial distribution pattern of Chla. These findings can offer ideas into predicting the variation of Chla in marine ranching under global interannual events in the future. Furthermore, this can contribute to the comprehensive assessment of ecological benefits and the in-depth construction of marine ranching. Ultimately, it can provide essential data and scientific references for offshore ecological environment assessment and ecosystem restoration.

Research on Sales of New Energy Vehicles Based on ARIMA Model

Firstly, this article identifies seven indicators based on electric vehicles: battery endurance, number of public charging facilities, government subsidies, gasoline prices, electricity prices, carbon emissions, and number of power battery companies. Spearman correlation analysis is conducted between indicator data and sales of new energy electric vehicles. The correlation coefficients of the first five indicators are all greater than 0.6, which is the main influencing factor. Then, the sales of new energy vehicles are predicted using a yearly forecasting method. Due to the close correlation between the sales of new energy vehicles and the five main indicators, the ARIMA time series model is first used to predict the annual quantity of the five indicators. Then, using these five indicators as inputs and sales as outputs, a BP neural network model is established to predict the annual sales of new energy vehicles in China to be 46051748 units in ten years. Finally, quantifying the score of ecological environment assessment using four evaluation indicators: sulfur dioxide, smoke emissions, ammonia nitrogen, and carbon dioxide. The entropy weight method was used to determine the weights of each indicator, and the results were 37.25%, 30.96%, 21.24%, and 10.55%, respectively. Then apply it to the TOPSIS model to obtain ecological environment scores for different years, and analyze the correlation between the degree of electrification and ecological environment scores. Finally, it can be concluded that the larger the market share of new energy vehicles, the better the ecological environment.

Estimation of Picea Schrenkiana Canopy Density at Sub-Compartment Scale by Integration of Optical and Radar Satellite Images

This study proposes a novel approach to estimate canopy density in Picea Schrenkiana var. Tianschanica forest sub-compartments by integrating optical and radar satellite data. This effort is aimed at enhancing methodologies for forest resource surveys and monitoring, particularly vital for the sustainable development of semi-arid mountainous areas with fragile ecological environments. The study area is the West Tianshan Mountain Nature Reserve in Xinjiang, which is characterized by its unique dominant tree species, Picea Schrenkiana. A total of 411 characteristic factors were extracted from Gaofen-2 (GF-2) sub-meter optical satellite imagery, Gaofen-3 (GF-3) multi-polarization synthetic aperture radar satellite imagery, and digital elevation model (DEM) data. Consequently, 17 characteristic parameters were selected based on their correlation with canopy density data to construct an estimation model. Three distinct models were developed, including a multiple stepwise regression model (a linear approach), a Back Propagation (BP) neural network model (a neural network-based method), and a Cubist model (a decision tree-based technique). The results indicate that combining optical and radar image characteristics significantly enhances accuracy, with an Average Absolute Percentage Precision (AAPP) value improvement in estimation accuracy from 76.50% (with optical image) and 78.50% (with radar image) to 78.66% (with both). Of the three models, the BP neural network model achieved the highest overall accuracy (79.19%). At the sub-component scale, the BP neural network model demonstrated superior accuracy in low canopy density estimation (75.37%), whereas the Cubist model, leveraging radar image characteristics, excelled in medium density estimations (87.46%). Notably, the integrated Cubist model combining optical and radar data achieved the highest accuracy for high canopy density estimation (89.17%). This study highlights the effectiveness of integrating optical and radar data for precise canopy density assessment, contributing significantly to ecological resource monitoring methodologies and environmental assessments.

Temporal and spatial evolution of net primary productivity in the Three-River Headwaters Region under phenological changes and anthropogenic influence.

Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 , which is 0.132 times the average annual NPPC over the past 21years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.

Reconnaissance of spatio-temporal variability in ecological stability with local adaptability based on multi-temporal LANDSAT archive in ganga river basin

Assessment of ecological environment is an indispensable part of the eco-environment protection and restoration. This study utilizes a remote sensing-based ecological index (RSEI) to better understand the environmental scenario in the Ganga basin. RSEI has been computed using five parameters: Wetness, Dryness, Greenness, Heat, and a newly incorporated parameter Albedo representative of land degradation. Median-based RSEI maps have been constructed using LANDSAT archives in Google Earth Engine (GEE) platform, covering three decades (1990–2021). The Ganga basin has been divided into five agro-climatic zones. For each zone and time frame (1990–99, 2000–09, 2010–19, and 2020–21), a median-based RSEI map has been generated. The analysis reveals that RSEI becomes poorer for sub-basin 1 (SB1), sub-basin 2 (SB2), and sub-basin 5 (SB5) in the 2010–19 period compared to the 1990–99 and 2000–09 periods. On the other hand, RSEI for sub-basin 3 (SB3) improved in the 2010–19 period compared to the previously mentioned periods. Sub-basin 4 (SB4) remained the least fluctuated region compared to the other sub-basins. The Global Moran's I value is highest for SB3 for the 1990–99 and 2000–09 periods, while for the 2010–19 and 2020–21 periods, SB2 has the highest Global Moran's I. This study incorporates big data analysis and can be indispensable in exploring the interactions between ecosystem services and anthropogenic activities in river basin systems.

Macroalgae as a sustainable biostimulant for crop production according to techno-economic and environmental criteria

One of the main hotspots in the agricultural sector is related to the extensive use of fertilizers and pesticides, which leads to direct environmental impacts, such as eutrophication, and indirect ones, such as the energy demand associated with their production. Faced with these limitations, the use of biostimulants has emerged as a suitable and effective strategy to improve crop productivity, avoid the use of chemicals and promote a more sustainable agricultural sector. This manuscript addresses the valorization of macroalgae for the production of biostimulants for crop cultivation according to three possible scenarios: steam autoclaving (SAE), boiling (BE), and supercritical fluid extraction (SFE). In order to evaluate their ecological potential, both techno-economic and environmental assessments have been developed, following the life cycle assessment methodology. The results obtained show that, from an environmental point of view, the use of energy resources and CO2, in the case of the SFE scenario, makes a significant contribution to the environmental profile. The optimization of the process could contribute to a reduction of the impact in the range of 12 %–41 %, which increases the sustainable potential of the biostimulant production. On the other hand, regarding the economic study, all scenarios are considered economically viable, since a minimum selling price (MSP) similar to the market average is obtained. However, by improving the process yield and the consumption of energy resources and materials, the MSP could be reduced by 19.81 %. In addition, this manuscript also shows that the application of this biostimulant in wheat production contributes to a significant reduction in environmental impact compared to a conventional crop stimulant.

Multi-Scenario Prediction of Land-Use Changes and Ecosystem Service Values in the Lhasa River Basin Based on the FLUS-Markov Model

The quantitative evaluation and prediction of ecosystem service value (ESV) in the Lhasa River Basin can provide a basis for ecological environment assessment and land-use optimization and adjustment in the future. Previous studies on the ESV in the Lhasa River Basin have focused mainly on static assessment and evolution analysis based on historical data, and have not considered future development trends. Moreover, most of the current driving factors selected in land use and ESV prediction studies are homogeneous, and do not reflect the geographical and cultural characteristics of the study area well. With the Lhasa River Basin as the research focus, 20 driving factors were selected according to the characteristics of the plateau alpine area, and the land-use changes under three developmental orientations, namely, natural evolution, ecological protection, and agricultural development, were predicted for the year 2030 with the FLUS-Markov model. Based on these predictions, the values of ecosystem services were calculated, and their spatiotemporal dynamic characteristics were analyzed. The results show that the model has high accuracy in simulating land-use change in the Lhasa River Basin, with a kappa coefficient of 0.989 and an overall accuracy of 99.33%, indicating a high applicability. The types of land use in the Lhasa River basin are dominated by the existence of grassland, unused land, and forest, with a combined proportion of 94.3%. The change trends of each land-use type in the basin under the three scenarios differ significantly, with grassland, cropland, and building land showing the most significant changes. The area of cropland increased only in the agricultural development scenario; the areas of forest and grassland increased only in the ecological protection scenario; and the expansion of building land was most effectively controlled in the ecological protection scenario. The ESV increased in all three scenarios, and the spatial distribution of the ESV per unit area in the middle and lower reaches was greater than that in the upper reaches. The ESV was the greatest in the ecological protection scenario, with grasslands, forests, and water bodies contributing more to the ESV of the basin. This study provides decision-making references for the effective utilization of land resources, ecological environmental protection planning, and urban construction in the Lhasa River Basin in the future.

Evaluation of ecological environment governance quality in the top ten cities of Zhejiang province using entropy weight method and Rank-Sum Ratio method: A case study of air quality indicators

All In this study, we focused on evaluating the quality of ecological environment m governance in eleven cities within Zhejiang Province. We employed a comprehensive set of key indicators, including the proportion of days with air quality meeting or exceeding Grade II standards, annual average concentrations of sulfur dioxide (SO_2), nitrogen dioxide (NO_2), particulate matter with a diameter of 10 micrometers or less (PM10), the 95th percentile daily concentration of carbon monoxide (CO), and the 90th percentile 8-hour maximum concentration of ozone (O_3). We utilized methods such as entropy values, information utility values, and weight allocation techniques to conduct a holistic assessment of urban ecological environment governance.Our findings revealed significant advantages in terms of Ritchies fitting values (RSR fitting values) for Zhoushan and Lishui cities, ranking them in the third tier. This underscores the commendable efforts of these two cities in improving air quality. Simultaneously, Huzhou city, while displaying relatively lower fitting values, demonstrates substantial potential in ecological environment governance. Additionally, key indicators such as the 90th percentile 8-hour maximum concentration of ozone (O_3) and annual average concentration of particulate matter (PM10) play pivotal roles in the overall evaluation.The comprehensive assessment framework presented in this study offers a thorough and accurate perspective on urban ecological environment governance. This approach can guide policy formulation and environmental management, albeit requiring further refinement and practical implementation. In summary, our research provides valuable insights for advancing ecological civilization construction through an in-depth analysis of urban ecological environment governance in Zhejiang Province.

Mechanism and ecological environmental risk assessment of peroxymonosulfate for the treatment of heavy metals in soil

Oxidation technologies based on peroxymonosulfate (PMS) have been effectively used for the remediation of soil organic pollutants due to their high efficiency. However, the effects of advanced PMS-based oxidation technologies on other soil pollutants, such as heavy metals, remain unknown. In this study, changes in the form of heavy metals in soil after using PMS and the risk of pollution to the ecological environment were investigated. Furthermore, two risk assessment methods, the mung bean germination toxicity test and groundwater leaching soil column test, were employed to evaluate the soil before and after PMS treatment. The results showed that PMS has a strong ability to degrade complex compounds, enabling the transformation of heavy metals, such as Cd, Pb, and Zn, from stable to active states in the soil. The risk assessments showed that PMS treatment activated heavy metals in the soil, which delayed the growth of plants, increased heavy metal content in plant tissues and the risk of groundwater pollution. These findings provide a new perspective for understanding the effects of PMS on soil, thus facilitating the sustained and reliable development of future research in the field of advanced oxidation applied to soil treatment.

Ecological Environment Assessment and Driving Mechanism Analysis of Nagqu and Amdo Sections of Qinghai-Xizang Highway Based on Improved Remote Sensing Ecological Index

The ecological environment along the Qinghai-Xizang highway is an important part of the construction of the ecological civilization in the Xizang region, and current research generally suffers from difficulties in data acquisition, low timeliness, and failure to consider the unique "alpine saline" environmental conditions in the study area due to the unique geographical environment of the Qinghai-Xizang plateau. Based on the GEE platform and the unique geographical environment of the study area, the remote sensing ecological index (RSEI) was improved, and a new saline remote sensing ecological index (SRSEI) applicable to the alpine saline region was constructed by using principal component analysis as an ecological environment quality evaluation index. The spatial distribution pattern and temporal variation trend of ecological environment quality along the Qinghai-Xizang Highway Nagqu-Amdo section were analyzed at multiple spatial and temporal scales using the ArcGIS 10.3 platform and geographic probes, and the driving mechanisms of eight control factors, including natural and human-made, on the spatial and temporal changes in SRSEI were investigated. The results showed that:① compared with RSEI, SRSEI was more sensitive to vegetation and had a stronger discriminatory ability in areas with sparse vegetation and severe salinization, which is suitable for ecological quality evaluation in alpine saline areas. ② The spatial scale of ecological environment quality in the study area had obvious geographical differentiation, and the areas with poor ecological quality were mainly concentrated in the northern Amdo County, whereas the areas with excellent and good quality grades were mainly distributed in the central-western and southeastern Nagqu areas. On the temporal scale, the ecological environment of the study area as a whole showed an improvement trend over 32 years, and the vegetation cover in the central-western and southeastern areas increased significantly, which had a strong improvement effect on the ecological environment. The improvement area was 1 425.98 km2, accounting for 99.82%. The mean value of SRSEI was 0.49, with an overall fluctuating upward trend and an average increase of 0.015 7 a-1. ③ The land use pattern was the most driving influence factor in the change of ecological environment quality in the study area, with an average q value of 0.157 6 over multiple years, and the influence of environmental factors was low. The multi-factor interaction results showed that the ecological environment in the study area was the result of multiple factors acting together, all factors had synergistic enhancement under the interaction, the influence of human factors was gradually increasing, and the interaction of the net primary productivity (NPP) of vegetation and land use pattern was the main interactive control factor of ecological environment quality in the study area. This study can provide a theoretical basis for ecological environmental protection and sustainable development along the Nagqu to Amdo section.

Highway Ecological Environmental Assessment Based on Modified Remote Sensing Index—Taking the Lhasa–Nyingchi Motorway as an Example

The Lhasa to Nyingchi Expressway in Xizang made efforts to protect the ecological environment during its construction, but it still caused varying degrees of damage to the fragile ecosystems along the route. Accurately assessing the process of change in the ecological environment quality in this region holds significant research value. This study selected the Linzhi-to-Gongbo’gyamda section of the Lhasa-to-Nyingchi Expressway as the research area. Firstly, based on the remote sensing ecological index (RSEI), this study constructed an ecological environmental quality evaluation system for the Xizang region. Subsequently, using the Google Earth Engine (GEE) platform, sub-indicators were extracted, and the combination weighting method of game theory was employed to determine indicator weights. This process resulted in the calculation of the MRSEI for the study area from 2012 to 2020. Finally, by utilizing the spatial distribution of the MRSEI, monitoring the level of MRSEI changes, and employing the transition matrix, this study analyzed the changing trend of the ecological environmental quality from 2012 to 2020. The results indicate that the MRSEI are 0.5885, 0.5951, 0.5296, 0.6202, 0.59, 0.5777, 0.5898, 0.5703, and 0.5987, showing a gradual increasing trend with an initial decrease followed by an ascent. This trend is mainly attributed to concentrated road construction and subsequent ecological restoration, leading to an improvement in the restoration effect. Simultaneously, the ecological environmental quality remains relatively stable, with 69.5% of the region showing no change, and the remaining 30.5% experiencing improvement exceeding degradation. Specifically, there were significant improvements in the land with ecological quality levels categorized as poor, fair, moderate, and good. The types of degradation primarily involved lands originally classified as excellent and good degrading to good and moderate levels, respectively. The above results serve as a theoretical reference for the ecological restoration project of the Lhasa-to-Nyingchi Expressway.

Dynamic monitoring of vegetation growth in Engebei ecological demonstration area based on remote sensing

Vegetation growth and the ecological environment affect each other. Understanding vegetation growth trend and their spatial pattern evolution is of great significance for ecological environment assessment and protection. The spatial trend and pattern evolution of different vegetation growth in the ecological area are included in vegetation planning, which can be used as a reference for vegetation planning and development. Based on Landsat remote sensing data, the spatial evolution trend and dynamic evolution of vegetation patterns at different levels in the Engebei Ecological Demonstration Zone from 2000 to 2021 were revealed, and the degree of ecological vulnerability was determined. The results show that: during the growing season from 2000 to 2021, the vegetation growth of the study area showed an overall improvement trend (about 63.44%), and the vegetation growth trends was mainly not significant change (about 97.12%). The improvement of vegetation growth in the southern desert region was higher than that in the northern arid steppe region. In the future, the main growth types were non-significant improvement of sustainability, non-significant improvement of anti-sustainability, non-significant degradation of anti-sustainability, and non-significant degradation, accounting for 38.84%, 23.81%, 17.30%, and 17.16%, respectively. The spatial distribution of vegetation of different grades mainly showed aggregation patterns, and the spatial distribution evolvement was more and more uniform, the distribution range was gradually expanded, and the orientation was gradually weakened. The numerical clustering degree of ecological vulnerability of vegetation was constantly declining. The results can provide a scientific basis for vegetation planning in the Engebei ecological demonstration area.

Research on CLUFS and Its Application in Rapid Prediction of the Impact of Regulating Services Value in Construction Projects

With the development of human society and the acceleration of urbanization, the impact of construction projects on the ecological environment is increasingly attracting attention. Conducting an ecological environmental impact assessment of construction projects is crucial to protect the ecological environment and achieve sustainable development. To estimate how construction projects would affect the value of ecosystem services, this paper develops the China Land Use Feature Data Sets (CLUFS) and uses the Beijing “One Line Four Mines” project as an example. Research found that the project’s conservation and restoration zone and the landscape construction zone will significantly enhance the ecosystem regulation services value. The conservation and restoration zone will increase by 30% from the current 1.413 billion yuan per year to 1.836 billion yuan per year, and the landscape construction zone will increase by 69% from the current 400 million yuan per year to 676 million yuan per year. The tourism development zone, dominated by urban construction, will result in a decrease in ecosystem regulation services, from 19.26 million yuan per year to 17.60 million yuan per year by 9%. Overall, the “One Line Four Mines” project achieved a balance of ecological value and surplus. The method proposed in this paper for predicting the impact of ecosystem regulation services value on construction projects can be used to quickly evaluate the effects of different planning schemes on the ecosystem services value of land parcels to help urban planning decision-makers control the condition of land use. It can provide new indicators for the ecological environment department to incorporate ecological benefits into the evaluation system of planning schemes and new methods for evaluating the ecological protection effectiveness of projects.

Retracted: Application of Computer Vision and Sensor Technology in Multivariate Assessment of Ecological Environment Carrying Capacity

Retracted: Application of Computer Vision and Sensor Technology in Multivariate Assessment of Ecological Environment Carrying Capacity

Lost in Translation: Overcoming Distinctions in Worldviews in Environmental Impact Assessments in Canada and Russia

How would the usage of Indigenous languages contribute to overcoming the epistemological gap between Traditional Ecological Knowledge and Environmental Impact Assessments? This article examines incommensurabilities that arise in Sakha-Russian and Cree-English translations of EIA through the translations of the most common words in samples. Without being embedded in Indigenous languages, TEK and other knowledges are easily decontextualized, and results in the loss of layers of meaning. This study adopted a linguistic anthropological approach to language combined with content analysis and guided by a poststructuralist mode of analysis. We argue policies around EIA/EAs must be shifted to center Indigenous languages as the source of TEK and ensure that there is space for these languages to be used in the consultation processes.