Ecological Environment Quality Evaluation Research Articles

Analysis of the evolution and influencing factors of ecological environment quality after the transformation of resource-exhausted cities based on GEE and RSEI: a case study of Xuzhou City, China

ABSTRACT This study used Google Earth Engine (GEE) to get and process Landsat images of Xuzhou from 2008 to 2020, and built remote sensing ecological indices (RSEI). This study analyzed the spatiotemporal features and drivers of ecological environment quality after Xuzhou’s transformation using landscape pattern index, spatial autocorrelation, and geographic detector methods. The results showed that: (1) The ecological environment quality of Xuzhou improved steadily but unevenly from 2008 to 2020; the west and central urban areas had poor but improving quality, while the east had the opposite trend; (2) The landscape pattern indices of ecological environment quality in different regions of Xuzhou did not change consistently from 2008 to 2020; (3) The spatial distribution of ecological environment quality had significant autocorrelation, with high-high clusters in the east and low-low clusters in the center and the urban areas of each district and county; (4) NDVI is the component index that has the greatest impact on the changes in the RSEI. Among the single factors, land use conditions have the strongest influence on ecological environmental quality. After the interaction of dual factors, the explanatory power is stronger than that of any single factor. The research results can support urban planning and design, ecological environment protection, etc. in Xuzhou, and offer insights for monitoring and evaluation of ecological environment quality after the transformation of resource-exhausted cities.

Spatial-temporal characteristics analysis and ecological environment quality evaluation of forest health care bases in Yunnan, Guizhou and Sichuan provinces

As the forest health care in China is still in the early stage of development, the construction standards of forest health care base are not unified yet, resulting in large differences in the evaluation criterion for the ecological environment of forest health care bases. So, it is urgent to develop a new forest health care ecological environment quality assessment method. Yunnan, Guizhou and Sichuan provinces of China were selected as the study area, the previous 6 batches of 165 national forest health care pilot construction bases were selected as the main data source. This study explored the spatial and temporal distribution characteristics of forest health care bases in the study area using standard deviation ellipses, kernel density estimation method and cold and hot spot analysis. Furthermore, this study evaluated the ecological environment quality of the forest health care bases with a new ecological environment quality evaluation index model, which assembled Fraction Vegetation Coverage (FVC), Wetness (WET), Evapotranspiration (ET), Land Surface Temperature (LST) and Normalized Difference Bare Soil Index (NDBSI). The results are as follows: (1) the forest health bases in the study area are mainly located by the east of the Hu Line with a northeast-southwest distribution direction characteristics, and gradually expanded into a shape of “high in the east and low in the west, multi-point development”. (2) the area with ecological environment quality in excellent, good and medium grade accounts for about 87.73 % in the study area, indicating that most of the study area is suitable for the construction of forest health care base. These results can provide a practical guidance for the further rational layout and balanced development of forest health care bases in the study area.

Comparison of Crown Volume Increment in Street Trees among Six Cities in Western Countries and China

The tree crown volume (CV), as a major indicator in the evaluation of ecological environment quality, can assess the health and carbon sequestration of urban trees. In this study, a new low-cost method, the plane calculation of angle disparity (PCAD), was employed to obtain the CV in China using satellite images from Google Earth. Meanwhile, primary data on street trees from four Western cities were acquired from online datasets. Nonparametric statistical methods showed no significant difference in CV per street tree between Beijing and Shanghai in China, ranging from 10 to 150 m3, almost one-seventh of that in the four cities (Paris and London in Europe and Los Angeles and Seattle in America). The CV of Platanus acerifolia in Paris and London exhibited values five times higher than those in Beijing and Shanghai. The annual crown volume increment (CVI) was less than 5 m3 in Beijing and Shanghai, significantly lower than in Seattle (66.55 m3). The purpose of the research was to verify the operability of the PCAD and compare the CVI in different cities all over the world, providing new ideas for urban tree management and carbon sequestration evaluation and a basis for government decision making in areas with a low CVI.

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.

Active–Passive Remote Sensing Evaluation of Ecological Environment Quality in Juye Mining Area, China

The coal industry is a crucial component of China’s energy sector. However, the persistent exploitation of coal resources has gravely impacted the ecological environment. While the Remote Sensing Ecology Index (RSEI) is predominantly used for assessing ecological quality, its primary focus has been urban or aquatic environments. There is limited research focused on the evaluation of the ecological environment quality in mining areas. Moreover, the information regarding surface deformation caused by coal mining extraction is an essential factor in the ecological monitoring of mining areas. Therefore, this study proposed the Modified Remote Sensing Ecology Index (MRSEI). This enhanced model merges active and passive remote sensing techniques and incorporates a deformation factor (Surface Deformation Index, SDI) to provide a holistic evaluation of mining area ecologies. Furthermore, for comparative verification, we developed the Eco-environmental Quality Index (EQI) model by selecting 12 ecological parameters and employing a hierarchical analysis. The Juye mining area in Shandong Province was selected as the region of study. MRSEI results from 2015 to 2021 indicate a decline in the ecological quality of the Juye mining area, with MRSEI values registering at 0.691, 0.644, and 0.617. The EQI model mirrors this decreasing trend over the same period. Despite MRSEI using fewer indicators, its assessments align closely with the multi-indicator EQI method. This validates the accuracy of the MRSEI method, providing reliable technical support for the monitoring and evaluation of ecological environment quality in mining areas.

Improvement of remote sensing ecological index and evaluation of ecological environment quality in Luanhe River Basin, China

To clarify ecological environment quality and its influencing factors, we constructed an improved remote sensing ecological index (ISREI) coupled with greenness, humidity, dryness and aerosol optical depth based on satellite remote sensing data. We evaluated the ecological environment quality of Luanhe River Basin by IRSEI, and investigated the influencing factors. The results showed that IRSEI were 0.488, 0.532, 0.563, and 0.586 in 2000, 2008, 2016, and 2022, respectively, indicating that ecological environment quality of the basin continued to rise. The ecological environment quality and its change were characterized by high in southeast and low in northwest, improvement in southeast and degradation in northwest. Annual precipitation, slope, land use, primary industry and tertiary industry were the key factors affecting the spatial variations of ecological environment quality. The interaction of these factors had a more significant impact on the ecological environment quality.

Research on the evaluation of ecological environment quality based on Fuzzy and PCA-AHP

Since the natural ecological environment tends to change slowly and the indicators are easy to quantify in a graded manner, while the social ecological environment tends to change rapidly under the intervention of human production and life, and it is difficult to quantify with the same grading standard in different regions and at different times. Therefore, we propose a Fuzzy comprehensive evaluation model for the evaluation of the quality of natural ecological environment and a PCA-AHP comprehensive evaluation model for the evaluation of the quality of social ecological environment. Based on the hierarchical analysis method, 12 indicators were selected from five criteria levels, namely water and soil conservation, ecological stability, water conservation, soil improvement and air purification, and the affiliation degree of each indicator to the set of comments was calculated using the Fuzzy comprehensive evaluation method. Taking the evaluation of ecological and environmental quality of 31 provincial regions in China as an example, 12 indicators were selected from three criterion levels, namely natural conditions, social economy and environmental pollution, and the combined weight values of each indicator were calculated using PCA and AHP, and the final ecological and environmental quality ranking of each province was obtained based on the data of each of the 31 provinces. The two experimental results were highly consistent with the actual expert evaluations, verifying the rationality of the Fuzzy comprehensive evaluation model and the PCA-AHP comprehensive evaluation model.

Long-Term Ecological Environment Quality Evaluation and Its Driving Mechanism in Luoyang City

The quality of the ecological environment determines human well-being, and the degree of ecological environment quality has a significant impact on regional sustainable development. Currently, the assessment content of ecological environment quality in Luoyang is relatively single-indicator-based and is insufficient to comprehensively reflect the changes in the ecological environment quality of Luoyang city. Therefore, the study aims to use the Remote Sensing Ecological Index (RSEI), a comprehensive evaluation model, with Landsat remote sensing images and statistical yearbooks as the data sources, to evaluate the spatiotemporal dynamic changes in the ecological environment quality of Luoyang city from 2002 to 2022 through trend analysis and mutation testing; the study employs geographical detectors to analyze the driving factors about the changes in ecological environment quality. The study found that: (1) the average RSEI value in Luoyang city has increased by 0.102 in the past 20 years, indicating an overall improvement in the ecological environment quality of Luoyang city. (2) The northern region of the study area has lower RSEI values, while the southern region has better ecological environment quality, which corresponds to the fact that the northern part of Luoyang city has intensive human activities, while the southern part is characterized by higher vegetation coverage in mountainous areas. (3) The proportion of areas with medium and above ecological environment quality grades have increased from 47.2% to 67.5%, indicating a positive trend in future ecological environment quality changes. (4) The population change was the strongest single factor influencing the ecological environment quality change in Luoyang city. The interaction between temperature and GDP was relatively the strongest. The current ecological environment status in the study area is the result of the combined effects of natural and anthropogenic factors. The research conclusions contribute to improving regional ecological environment quality and are of great significance for the regional ecological environment planning and the achievement of sustainable development goals.

Dynamic Evaluation of Ecological Environment Quality in Coastal Cities from the Perspective of Water Quality: The Case of Fuzhou City

Urbanization has led to enormous pressure on the urban ecological environment, especially in coastal cities. It is important to evaluate the ecological quality of coastal cities. We compared the remote sensing-based ecological index (RSEI) and the water benefit-based ecological index (WBEI) indices of Fuzhou City, and selected the WBEI to assess the changes in the quality of the ecological environment in Fuzhou City from 2000 to 2020 and analyzed the relevant changes in land intensity. The results show that (1) the Fuzhou WBEI outperforms the RSEI in the evaluation of ecological quality in the study area, since the WBEI takes into account water efficiency and can more accurately represent the ecological environment of coastal cities; (2) during 2000–2020, the overall trend of ecological quality in Fuzhou is better, with nonsignificant decreasing areas in the western and northern mountainous areas and a significant increasing trend in the southeast coast; and (3) different land use types influence the urban ecological environment quality, with forests and man-made surfaces having a good correlation with the WBEI. The increase in forests contributes to the improvement of urban ecological environment quality, and the conversion of high-intensity arable land and construction land decreases urban ecological environment quality. This study can provide a basic reference for the assessment of ecological environment quality in Fuzhou City and provide experience for the ecological environment assessment of coastal cities.

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China.

Scientific territorial spatial planning is of great significance in the realization of the sustainable development goals in China, especially in the context of China's ecological civilization construction and territorial spatial planning. However, limited research has been carried out to understand the spatio-temporal change in EEQ and territorial spatial planning. In this study, Changsha County and six districts of Changsha City were selected as the research objects. Based on the remote sensing ecological index (RSEI) model, the spatio-temporal changes in the EEQ and spatial planning response in the study area during 2003-2018 were analyzed. The results reveal that (1) the EEQ of Changsha declined and then rose between 2003 and 2018, showing an overall decreasing trend. The average RSEI declined from 0.532 in 2003 to 0.500 in 2014 and then increased to 0.523 in 2018, with an overall decrease of 1.7%. (2) In terms of spatial pattern changes, the Xingma Group, the Airport Group and the Huangli Group in the east of the Xiangjiang River had the most serious EEQ degradation. The EEQ degradation of Changsha showed an expanding and polycentric decentralized grouping pattern. (3) Massive construction land expansion during rapid urbanization caused significant EEQ degradation in Changsha. Particularly, the areas with low EEQ were concentrated in the areas with concentrated industrial land. Scientific territorial spatial planning and strict control were conducive to regional EEQ improvement. (4) The prediction using the urban ecological model demonstrates that every 0.549 unit increase in NDVI or 0.2 unit decrease in NDBSI can improve the RSEI of the study area by 0.1 unit, thus improving EEQ. In the future territorial spatial planning and construction of Changsha, it is necessary to promote the transformation and upgrading of low-end industries into high-end manufacturing industries and control the scale of inefficient industrial land. The EEQ degradation caused by industrial land expansion needs to be noted. All of these findings can provide valuable information for relevant decision-makers to formulate ecological environment protection strategies and conduct future territorial spatial planning.

A Hybrid Evaluation Method of Ecological Environment Quality Based on Entropy and Matter-Element Extension Model

The ecological environment of China is facing much more pressure with the continuous growth of population and energy usage. China pays more attention to improving the ecological environment quality with the ecological civilization development in the situation. The key problem is to construct a scientific and reasonable comprehensive evaluation index system guiding the ecological environment quality improvement. This paper creates a comprehensive evaluation index system of ecological environment quality based on the Pressure-State-Response (PSR) framework and uses a hybrid model with the entropy weight method and matter-element extension to evaluate China’s ecological environment quality from 2016 to 2020. The results show the overall ecological environment quality evaluation level in China is continuously improved. The results also show that China should pay much attention to the four main factors, which are population density, carbon emissions, per capita energy consumption, and per capita arable land, it should take some policies to improve the four factors. The case study has proven the effectiveness and practicality of the hybrid method and the comprehensive evaluation index system.

Dynamic Monitoring and Driving Factors Analysis of Ecological Environment Quality in Poyang Lake Basin

The ecological environment of Poyang Lake basin is an important part of the construction of ecological civilizations in the south of China. Based on the Landsat satellite remote sensing images, using the principal component analysis (PCA) method to construct the remote sensing ecological index (RSEI) as an evaluation index of ecological environment quality, introducing the Geodetector model to quantitatively detect the explanatory power of different influencing factors on the spatial divergence of the ecological environment, and exploring the changes in ecological environment quality in the Poyang Lake basin from 1990 to 2020 and the impact of different driving factors. The results of the study showed that there were obvious regional differences in the ecological environment quality in the basin. The areas with bad and poor ecological quality were mainly distributed in the central and northern plains; the areas with high and good quality grades were mainly distributed in the hilly and mountainous region of the southwestern part of the basin; the overall ecological environment of the Poyang Lake basin has been improving over the past 30 years; and the improved areas were mainly distributed in low-altitude areas. Geodetector results showed that population density was the factor with the highest explanatory power for the spatial divergence of ecological environment quality in the Poyang Lake basin. Among different natural factors, topographic factors (slope, aspect) had a higher driving force than meteorological factors (temperature, precipitation). The night light index factor showed an increasing yearly trend, indicating that the ecological environment quality of the Poyang Lake basin was gradually increased due to the influence of urbanization development. The construction of the RSEI model based on Google Earth Engine could not only effectively ensure the accuracy of ecological environment quality evaluation in different years but could also quickly realize image preprocessing and index calculations, which greatly improved the efficiency of ecological environment evaluation. These research results can provide a theoretical basis and scientific data support for the ecological environment protection work in the Poyang Lake basin.

东北虎豹国家公园生态环境质量动态评价及其气候响应

PDF HTML阅读 XML下载 导出引用 引用提醒 东北虎豹国家公园生态环境质量动态评价及其气候响应 DOI: 10.5846/stxb202204130981 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 吉林省科技发展项目（20210203152SF）；中国气象局创新发展专项（CXFZ2021J076） Dynamic evaluation of ecological environment quality and climate response in Northeastern China Tiger and Leopard National Park Author: Affiliation: Fund Project: 省、部研究计划基金 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:人类活动及气候变化对东北虎豹国家公园生态环境产生深刻的影响，探究该地区生态环境质量的时空演变规律对园区可持续发展具有重要意义。在原有遥感生态指数基础上，选用增强型植被指数代替原绿度指标中的归一化植被指数，构建2001-2020年植被生长季遥感生态指数，探讨园区内核心保护区、虎豹潜在栖息地及主要人口聚集区三大管控区生态环境质量时空变化特征，并基于像元尺度分析其对气候因素的响应。结果表明：（1）近20年虎豹公园生态环境质量呈波动微弱下降趋势，2015年后生态环境质量逐步提升，2020年达到良好水平；（2）园区内各管控区生态环境质量具有明显的空间分异性，东部核心保护区中部及虎豹潜在栖息地中部以南地区生态环境质量较好，主要人口聚集区相对较差。（3）近20年虎豹公园生态环境质量稳定性较差。未来生态环境质量变化趋势为上升的面积占60.86%，表明未来生态环境趋势总体向好，但局部地区仍存在持续恶化态势。（4）虎豹公园生态环境质量主要受降水的影响，与降水呈显著正相关关系，与气温及日照的相关性较弱。 Abstract:Human activities and climate change have a profound impact on the ecological environment of the Northeastern China Tiger and Leopard National Park (NCTL-NP), and exploring the temporal and spatial evolution of the ecological environment quality in this area is of great significance for the sustainable development of the park. In this paper,we selected the enhanced vegetation index (EVI) to replace the NDVI in the original greenness index, and constructed the remote sensing ecological index (RSEI) for the vegetation growing season from 2001 to 2020 based on the original remote sensing ecological index. Then, we analyzed the temporal and spatial variation characteristics of the ecological environment quality and their responses to climatic factors in the three major control areas of potential habitats and main population agglomeration areas based on the pixel scale. The results show that:(1) The ecological environment quality of NCTL-NP has shown a fluctuating and weak downward trend in the past 20 years. After 2015, the ecological environment quality has gradually improved and reached a good level in 2020; (2) The ecological environment quality of each control area in the park has obvious spatial heterogeneity, the quality of the ecological environment in the central part of the eastern core reserve and the southern part of the potential habitat of tigers and leopards is relatively good, while the main population agglomeration areas are relatively poor. (3) In the past 20 years, the ecological environment quality of NCTL-NP has been extremely unstable.The area with an upward trend in the quality of the ecological environment in the future accounted for 60.86%, indicating that the trend of the ecological environment in the future is generally good, but there is still a continuous deterioration trend in some areas. (4) The ecological environment quality of NCTL-NP is mainly affected by precipitation, which has a significant positive correlation with precipitation, and a weak correlation with temperature and sunshine. 参考文献 相似文献 引证文献

Impact of Land Cover Change on a Typical Mining Region and Its Ecological Environment Quality Evaluation Using Remote Sensing Based Ecological Index (RSEI)

Ecological environment in mining cities has become an important part of ecological construction. This paper takes Tongling, a mining city, as the research area, and uses Landsat series remote sensing images from 2000 to 2020 as data sources. Using the principal component analysis method and the Remote Sensing Ecological Index (RSEI) integrated with four indexes of greenness, humidity, dryness, and heat, the ecological disturbance of the mining area was evaluated and studied. Meanwhile, the land cover spatiotemporal classification of Tongling city was extracted by the maximum likelihood method. Furthermore, landscape metrics were used, based on the information on open-pit mining areas, to quantitatively analyze the ecological environment quality and its change characteristics in the study area. The results show that (1) RSEI can better characterize the ecological quality of Tongling city, greenness and humidity are positively correlated with it, dryness and heat are negatively correlated with it, and dryness and RSEI have the highest correlation coefficient, indicating that urban expansion will cause ecological environment deterioration to a certain extent. (2) The ecological environment quality of the research area showed a “decline-rising” trend, and the mean value of RSEI decreased from 0.706 to 0.644. Spatially, the areas with poor RSEI are mainly distributed in the central urban area and the open-pit mining area in the south. (3) Land cover change leads to changes in landscape metrics, and most landscape-level metrics are positively or negatively correlated with RSEI. The more concentrated the land cover type distribution is, the smaller the change is, and the more regional RSEI can be improved. (4) The mean value of RESI of the ten open-pit mining areas in Tongling city decreased significantly, with a maximum decrease of 52.73%. Among them, the RESI decline rate in the area around the no.1 open pit mine is 0.034/year. The ecological degradation in Tongling city is attributed to the rapid expansion of built-up areas and the development of the mining industry. The research results can provide a scientific basis for protecting the ecological environment of mining cities.

Effect evaluation of ecological water conveyance in Tarim River Basin, China

Ecological water conveyance is an important way to promote the restoration of degraded ecosystems in arid watersheds. However, there are few previous research results on how to quantitatively evaluate the effect of ecological water conveyance on ecological restoration. In this regard, this paper selects the Tarim River Basin as a typical area, analyzing the changes of desert riparian vegetation and hydrological elements, constructing a watershed ecological environment quality evaluation system, and comprehensively evaluating the ecological water conveyance effect of the damaged desert forest ecosystem. The conclusion showed that the proportion of the pixel area with an upward trend of Fractional Vegetation Cover (FVC) from 2000 to 2021 is as high as 84.3%. The plant diversity index in the ecological water conveyance area showed the characteristics of first obvious increase and then stable. The main body of groundwater depth showed an upward trend, and the Temperature Vegetation Dryness Index (TVDI) showed a downward trend of pixel area accounting for 57.0%, which indicated that ecological water conveyance had played a positive role in groundwater recharge and ecological restoration along the Tarim River. The ecological environment quality of the river basin showed a trend of transition from low-grade to high-grade, and the area with excellent ecological quality had increased from 4,635.50 km2 in 2000 to 12,335.0 km2 in 2021. The above research provides important scientific reference for the protection and restoration of vegetation degradation in arid watersheds.

Evaluation of Ecological Environment Quality in Chongqing Main City Area Based on Principal Component Analysis

With the rapid development of social productive forces in China, the process of urbanization has been accelerating, resulting in the deterioration of urban environmental quality and the destruction of ecosystems, such as debris flow, drought, water bloom, large-scale haze weather, and other ecological and environmental problems. The quality of the urban ecological environment is not only related to the stability of urban ecological function but also affects the sustainable development of the city. Many scholars have studied the problem of ecoenvironmental quality assessment, but there are still some shortcomings in the evaluation process, such as the construction of the index system and the application of related methods. Taking Chongqing as the research object, after referring to the representative evaluation index system in China, the evaluation index system of ecological environment quality in Chongqing was constructed from three aspects of nature, economy, and society. In this article, the principal component analysis (PCA) method is used to construct the ecoenvironmental quality evaluation system of Chongqing, and the economic development, pollutant control, natural protection and pollution reduction investment, urban and rural cooperation, land area, and other aspects are comprehensively evaluated. The relationship between simulated variables and the regression equation was also assessed. Through the comparative analysis of the two evaluation methods, it can be seen that the evaluation results of the PCA method and the fuzzy comprehensive evaluation method are basically the same in the longitudinal trend, which shows that the application of this method in the field of ecological environment quality evaluation has certain scientific rationality.

Dynamic monitoring and evaluation of ecological environment quality in Zhouqu County, Gansu, China based on Google Earth Engine cloud platform

Zhouqu County is located in the transition region from the Qinghai-Tibet Plateau to the Qinba Mountains, and is an important part of the ecological barrier in the upper stream of the Yangtze River. In this study, we used the Google Earth Engine cloud processing platform to perform inter-image optimal reconstruction of Landsat surface reflectance images from 1998-2019. We calculated four indicators of regional wet, green, dry, and hot. The component indicators were coupled by principal component analysis to construct remote sensing ecological index (RSEI) and to analyze the spatial and temporal variations of ecological environment quality in Zhouqu County. The results showed that the contribution of the four component indicators to the eigenvalues of the coupled RSEI were above 70%, with even distribution of the loadings, indicating that the RSEI integrated most of the features of the component indicators. From 1998 to 2019, the RSEI of Zhouqu County ranged from 0.55 to 0.63, showing an increasing trend with a growth rate of 0.04·(10 a)-1, and the area of better grade increased by 425.56 km2. The area with altitude ≤2200 m was dominated by medium and lower ecological environment quality grade, while the area of better ecological environment quality grade area increased by 16.5%. The ecological and environmental quality of the region from 2200 to 3300 m was dominated by good grades, increasing to 71.3% in 2019, with the area of medium and below ecological and environmental quality grades decreasing year by year. The area with altitude ≥3300 m was dominated by the medium ecological quality grade. The medium and below ecological quality grades showed a "U" shape trend during the study period. The trend of ecological environment quality in Zhouqu County was becoming better, but with fluctuations. It is necessary to continuously strengthen the protection and management of ecological environment in order to guarantee the continuous improvement of ecological environment quality.

DYNAMIC MONITORING OF ECOLOGICAL ENVIRONMENT QUALITY IN GANSU PROVINCE SUPPORTED BY GOOGLE EARTH ENGINE

Abstract. With the rapid development of remote sensing technology, this technology has been widely used in the field of ecological environment monitoring. The Remote Sensing Ecological Index (RSEI) is based on remote sensing data and integrates the four factors of greenness, dryness, wetness, and heat. This study took Gansu Province as the research object and calculated its remote sensing ecological index in 2000, 2010 and 2020. The results showed: (1) In general, the average RSEI increased from 0.2665 to 0.3299, reflecting the positive trend of ecological environment quality in Gansu Province. (2) The ecological environment grades in Gansu Province were mainly poor and bad grades, which accounted for about 78% in 2000 and dropped to 65% in 2020. (3) In terms of space, the RSEI index showed a decreasing characteristic from southeast to northwest. The areas with better ecological quality were the Longnan Mountains and the Gannan Plateau, while the areas with poorer ecological quality are the Hexi Corridor. (4) From 2000 to 2010, the ecological environment quality improved slightly, and the area with slight improvement accounted for 30.17%. From 2010 to 2020, the ecological environment was relatively stable, and the stable area accounted for 71.15%. This study supplements the blank of ecological environment quality evaluation in Gansu Province and aims to provide a reference for ecological environment protection and sustainable development in Gansu Province.

Research on Ecoenvironmental Quality Evaluation System Based on Big Data Analysis.

Comprehensive and objective evaluation of ecological environment quality is of great significance to regional sustainable development. In this study, Landsat remote sensing images of 1991, 2000, 2004, 2010, 2013, 2018, and 2019 are selected to evaluate the changes of ecological environment quality in the Headwaters of Dongjiangyuan River by using remote sensing ecological index RSEI. The influencing factors of ecological environment change in Dongjiangyuan River are also discussed. The results showed that, from 1991 to 2019, the ecoenvironmental quality of the Dongjiangyuan River showed a good trend of development. Humidity index, greenness index, and dryness index all fluctuated in a small range; the greenness and dryness showed an overall increase. The average temperature in the Headwaters of the Dongjiangyuan River presents a rising trend. This study establishes the evaluation system of ecological environment quality from two dimensions of time and space and gives the change rule of environmental quality quantitatively, which provides the theoretical basis for the ecological environment management of Dongjiangyuan River.

Ecological environment quality evaluation of the Sahel region in Africa based on remote sensing ecological index

Ecological environment quality evaluation of the Sahel region in Africa based on remote sensing ecological index