Long-term monitoring of the ecological environment changes is helpful for the protection of the ecological environment.Based on the ecological environment of the Sahel region in Africa,we established a remote sensing ...Long-term monitoring of the ecological environment changes is helpful for the protection of the ecological environment.Based on the ecological environment of the Sahel region in Africa,we established a remote sensing ecological index(RSEI)model for this region by combining dryness,moisture,greenness,and desertification indicators.Using the Moderate-resolution Imaging Spectroradiometer(MODIS)data in Google Earth Engine(GEE)platform,this study analyzed the ecological environment quality of the Sahel region during the period of 2001-2020.We used liner regression and fluctuation analysis methods to study the trend and fluctuation of RSEI,and utilized the stepwise regression approach to analyze the contribution of each indicator to the RSEI.Further,the correlation analysis was used to analyze the correlation between RSEI and precipitation,and Hurst index was applied to evaluate the change trend of RSEI in the future.The results show that RSEI of the Sahel region exhibited spatial heterogeneity.Specifically,it exhibited a decrease in gradient from south to north of the Sahel region.Moreover,RSEI in parts of the Sahel region presented non-zonal features.Different land-cover types demonstrated different RSEI values and changing trends.We found that RSEI and precipitation were positively correlated,suggesting that precipitation is the controlling factor of RSEI.The areas where RSEI values presented an increasing trend were slightly less than the areas where RSEI values presented a decreasing trend.In the Sahel region,the areas with the ecological environment characterized by continuous deterioration and continuous improvement accounted for 44.02%and 28.29%of the total study area,respectively,and the areas in which the ecological environment was changing from improvement to deterioration and from deterioration to improvement accounted for 12.42%and 15.26%of the whole area,respectively.In the face of the current ecological environment and future change trends of RSEI in the Sahel region,the research results provide a reference for the construction of the"Green Great Wall"(GGW)ecological environment project in Africa.展开更多
The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry o...The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.展开更多
Based on multi-type,multi-temporal remote sensing data,we have monitored recent changes in cultivated land use and vegetation,in sandy areas and salinized desertification in the Green Corridor zone of the main channel...Based on multi-type,multi-temporal remote sensing data,we have monitored recent changes in cultivated land use and vegetation,in sandy areas and salinized desertification in the Green Corridor zone of the main channel of the Tarim River Basin.The results of our investigation show that the ecological environment in the Green Corridor of the main channel of the Tarim River Basin has conspicuously improved from 2002 to 2004.These improvements show up largely in such aspects as an increase in the rate of vegetation cover,a reduction in desertification land areas and a weakening in the intensity of sandy and the salinized land.On the other hand,the cultivated area in the Tarim River Basin significantly increased from 2002 to 2004.The rate of growth in cultivated areas during this period was significantly higher than that from 1999 to 2002.The increase in the use of irrigation resulting from the substantial increase in cultivated areas has a long-term potential restraining effect on the restoration of ecological functions of the Tarim River.展开更多
Otindag Sandy Land in China is an important ecological barrier to Beijing;the changes in its ecological quality are major concerns for sustainable development and planning of this area.Based on principal component ana...Otindag Sandy Land in China is an important ecological barrier to Beijing;the changes in its ecological quality are major concerns for sustainable development and planning of this area.Based on principal component analysis and path analysis,we first generated a modified remote sensing ecological index(MRSEI)coupled with satellite and ground observational data during 2001–2020 that integrated four local indicators(greenness,wetness,and heatness that reflect vegetation status,water,and heat conditions,respectively,as well as soil erosion).Then,we assessed the ecological quality in Otindag Sandy Land during 2001–2020 based on the MRSEI at different time scales(i.e.,the whole year,growing season,and non-growing season).MRSEI generally increased with an upward rate of 0.006/a during 2001–2020,with clear seasonal and spatial variations.Ecological quality was significantly improved in most regions of Otindag Sandy Land but degraded in the southern part.Regions with ecological degradation expanded to 18.64%of the total area in the non-growing season.The area with the worst grade of MRSEI shrunk by 15.83%of the total area from 2001 to 2020,while the area with the best grade of MRSEI increased by 9.77%of the total area.The temporal heterogeneity of ecological conditions indicated that the improvement process of ecological quality in the growing season may be interrupted or deteriorated in the following non-growing season.The implementation of ecological restoration measures in Otindag Sandy Land should not ignore the seasonal characteristics and spatial heterogeneity of local ecological quality.The results can explore the effectiveness of ecological restoration and provide scientific guides on sustainable development measures for drylands.展开更多
In order to understand the development status of ecological environment quality in the Aksu region of China, to effectively adjust the ecological environment quality, so as to promote the sustainable development of it...In order to understand the development status of ecological environment quality in the Aksu region of China, to effectively adjust the ecological environment quality, so as to promote the sustainable development of its social economy and ecological environment protection. This paper selects the Landsat series remote sensing images of the northern Aksu region in 2013, 2016, and 2019, and uses the tools such as ENVI5.3 and ArcGIS 10.8.1 to process the image data accordingly. The principal component analysis method is used to calculate the Remote Sensing Ecological Index (RSEI) of the northern Aksu region. The data show that: 1) The ecological environment quality index in the northern Aksu region in 2013, 2016, and 2019 was 0.706087, 0.25243 and 0.362991 respectively;2) The areas where the ecological environment quality declined significantly in the northern Aksu region were the human settlements and the Gobi, fan-shaped land and other special terrain areas;3) The humidity index and the heat index are the two factors that have the greatest impact on the ecological environment quality in the northern Aksu area. The data as a whole show that the ecological environment in the northern part of the Aksu region has deteriorated seriously, and the severely deteriorated area is close to the human living area.展开更多
Fast and effective remote sensing monitoring is an important means for analyzing the spatio-temporal changes in ecological quality in fragile karst regions.This study focuses on Guanling Autonomous County,a national-l...Fast and effective remote sensing monitoring is an important means for analyzing the spatio-temporal changes in ecological quality in fragile karst regions.This study focuses on Guanling Autonomous County,a national-level demonstration county for comprehensive desertification control.Based on Landsat TM/OLI remote sensing image data from 2005,2010,2015,and 2020,remote sensing ecological indices were used to analyze the spatio-temporal changes in ecological quality in Guanling Autonomous County from 2005 to 2020.The results show that:①the variance contribution rates of the first principal component for the four periods were 66.31%,71.59%,63.18%,and 75.24%,indicating that PC1 integrated most of the characteristics of the four indices,making the RSEI suitable for evaluating ecological quality in karst mountain areas;②the remote sensing ecological index grades have been increasing year by year,with an overall trend of improving ecological quality.The area of higher-grade ecological quality has increased spatially,while fragmented patches have gradually decreased,becoming more concentrated in the low-altitude areas in the northwest and east,and there is a trend of expansion towards higher-altitude areas;③the ecological environment quality in most areas has improved,with the improvement in RSEI spatio-temporal variation becoming more noticeable with increasing slope.Areas of higher-grade quality appeared in 2010,and the range of higher-grade quality expanded with increasing slope.展开更多
In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to t...In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.展开更多
The middle reaches of the Yellow River represent a critically ecologically sensitive and fragile area within the Yellow River Basin(YRB),holding significant scientific value for ecological security assessment and envi...The middle reaches of the Yellow River represent a critically ecologically sensitive and fragile area within the Yellow River Basin(YRB),holding significant scientific value for ecological security assessment and environmental management strategies.This study comprehensively evaluates the evolution of the eco-environment in the“Two Mountains,Seven Rivers,and One Basin”(TSO)area of Shanxi Province from 2000 to 2020 based on fraction vegetation cover(FVC)derived from the Normalized Difference Vegetation Index(NDVI),net primary productivity(NPP)calculated via the Carnegie–Ames–Stanford approach(CASA),and the remote sensing ecological index(RSEI).The results indicate a significant improvement in the TSO’s eco-environment from 2000 to 2020,with the RSEI values increased from 0.34 in 2000 to 0.41 in 2020(an increase of 17.76%).Both FVC and NPP demonstrated notable upward trends,with FVC increasing by 22.74%and NPP by 53.11%.Spatially,FVC rose by 21.84%,19.72%and 26.06%,respectively in the Two Mountains,Seven Rivers,and the YRB in Shanxi Province.Similarly,the NPPs increased by 51.60%,48.60%,and 61.65%in these regions over the past 21 years.Both FVC and NPP exhibited decreasing patterns from southeast to northwest,with significant eco-environmental improvements in the northern region and slower recovery in the southern region.Precipitation was the primary causes influencing vegetation recovery,showing positive trends in the central and northern TSO regions,while this trend reversed in the southern.The RSEI value indicate substantial eco-environment improvements in the central and northern areas(Sanggan,Daqing and Hutuo River Basins),whereas the southern regions(e.g.,Zhang,Qin,Fen and Sushui River Basins)remain in poor grade.Human activities,particularly land use/cover changes marked by increased forestation and urbanization alongside decreased cultivated land,significantly affected vegetation cover patterns.This study provides scientific references for formulating policies on ecological construction and high-quality development in the YRB.展开更多
Regular quantitative assessments of regional ecological environment quality(EEQ)and driving force analyses are highly important for environmental protection and sustainable development.Northern China is a typical clim...Regular quantitative assessments of regional ecological environment quality(EEQ)and driving force analyses are highly important for environmental protection and sustainable development.Northern China is a typical climate-sensitive and ecologically vulnerable area,however,the changes in EEQ in this region and their underlying causes remain unclear.Traditional evaluations of EEQ rely primarily on the remote sensing ecological index(RSEI),which lacks assessments of indicators such as greenness(NDVI),humidity(WET),heat(LST),and dryness(NDBSI).To address these issues,this study employs the principal component analysis method and the Google Earth Engine to construct an RSEI suitable for long-term and large-scale applications and analyzes the spatio-temporal variations in the RSEI,NDVI,WET,NDBSI,and LST.Additionally,geographical detectors are utilized to analyze the driving factors affecting EEQ.The results indicate the following.(1)The RSEI shows a fluctuating upward trend,with an average value of 0.4566,indicating a gradual improvement in EEQ.The EEQ exhibited significant spatial heterogeneity,with a pattern of lower values in the west and higher values in the east.(2)The NDVI and WET exhibit fluctuating increasing trends,indicating improvements in both indices.The NDBSI shows a fluctuating decreasing trend,whereas the LST presents a fluctuating increasing trend,suggesting an improvement in the NDBSI and a slight deterioration in the LST.NDVI and WET demonstrate a spatial pattern characterized by low values in the west and high values in the east.NDBSI and LST demonstrate a spatial pattern characterized by low values in the east and high values in the west.(3)Land use types and precipitation are the primary driving factors influencing the spatial differentiation of the EEQ.The explanatory power of these driving factors significantly increases under their interactions,particularly the interaction between land use types and other driving factors.This study fills the gap in existing EEQ evaluations that analyze only the RSEI without considering the NDVI,WET,NDBSI,and LST.The findings provide new insights for EEQ assessments and serve as a scientific reference for environmental protection and sustainable development.展开更多
The Loess Plateau(LP),one of the most ecologically fragile regions in China,is affected by severe soil erosion and environmental degradation.Despite large-scale ecological restoration efforts made by Chinese governmen...The Loess Plateau(LP),one of the most ecologically fragile regions in China,is affected by severe soil erosion and environmental degradation.Despite large-scale ecological restoration efforts made by Chinese government in recent years,the region continues to face significant ecological challenges due to the combined impact of climate change and human activities.In this context,we developed a kernal Remote Sensing Ecological Index(kRSEI)using Moderate Resolution Imaging Spectroradiometer(MODIS)products on the Google Earth Engine(GEE)platform to analyze the spatiotemporal patterns and trends in ecological environmental quality(EEQ)across the LP from 2000 to 2022 and project future trajectories.Then,we applied partial correlation analysis and multivariate regression residual analysis to further quantify the relative contributions of climate change and human activities to EEQ.During the study period,the kRSEI values exhibited significant spatial heterogeneity,with a stepwise degradation pattern in the southeast to northwest across the LP.The maximum(0.51)and minimum(0.46)values of the kRSEI were observed in 2007 and 2021,respectively.Trend analyses revealed a decline in EEQ across the LP.Hurst exponent analysis predicted a trend of weak anti-persistent development in most of the plateau areas in the future.A positive correlation was identified between kRSEI and precipitation,particularly in the central and western regions;although,improvements were limited by a precipitation threshold of 837.66 mm/a.A moderate increase in temperature was shown to potentially benefit the ecological environment within a certain range;however,temperature of-1.00°C-7.95°C often had a negative impact on the ecosystem.Climate change and human activities jointly influenced 65.78%of LP area on EEQ,primarily having a negative impact.In terms of contribution,human activities played a dominant role in driving changes in EEQ across the plateau.These findings provide crucial insights for accurately assessing the ecological state of the LP and suggest the design of future restoration strategies.展开更多
Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid an...Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid and semi-arid areas.This study took the Helan Mountain,a typical arid and semi-arid area in China,as the study area.By adopting an Enhanced Remote Sensing Ecological Index(ERSEI)that integrates the habitat quality(HQ)index with the Remote Sensing Ecological Index(RSEI),we quantified the ecological environment quality of the Helan Mountain during 2010-2022 and analyzed the driving factors behind the changes.Principal Component Analysis(PCA)was used to validate the composite ERSEI,enabling the extraction of key features and the reduction of redundant information.The results showed that the contributions of first principal component(PC1)for ERSEI and RSEI were 80.23%and 78.72%,respectively,indicating that the ERSEI can provide higher precision and more details than the RSEI in assessing ecological environment quality.Temporally,the ERSEI in the Helan Mountain exhibited an initial decline followed by an increase from 2010 to 2022,with the average value of ERSEI ranging between 0.298 and 0.346.Spatially,the ERSEI showed a trend of being higher in the southwest and lower in the northeast,with high-quality ecological environments mainly concentrated in the western foothills at higher altitudes.The centroid of ERSEI shifted northeastward toward Helan County from 2010 to 2022.Temperature and digital elevation model(DEM)emerged as the primary drivers of ERSEI changes.This study highlights the necessity of using comprehensive monitoring tools to guide policy-making and conservation strategies,ensuring the resilience of fragile ecosystems in the face of ongoing climatic and anthropogenic pressures.The findings offer valuable insights for the sustainable management and conservation in arid and semi-arid ecosystems.展开更多
Studying an ecological restoration zoning process under the background of ecological security patterns is of great significance to the rapid adjustment and optimization of a landscape pattern.In this study,a remote se...Studying an ecological restoration zoning process under the background of ecological security patterns is of great significance to the rapid adjustment and optimization of a landscape pattern.In this study,a remote sensing ecological index and a morphological spatial pattern analysis method were used to assess the quality of habitats and identify ecological sources in the city of Ningbo;ecological corridors,ecological pinch points,and ecological barrier points were extracted by using a circuit theory to construct ecological security patterns and ecological restoration zones.The results indicate:(1)There were 47 ecological sources,and 83 key ecological corridors in Ningbo,and the ecological land area was about 1898.39 km^(2),accounting for 19.89%of the total study area.(2)The ecological source areas were distributed in“one patch and three belts”,and the low-resistance ecological corridors were concentrated in southern Yuyao city,western Haishu district,and central and western Fenghua district;the ecological network in the western and southern regions was dense.(3)There were four types of ecological restoration zones that need to be established,which were prioritized restoration zones,prioritized protection zones,key conservation zones,and general conservation zones distributed hierarchically from inner part towards outside.(4)Ninghai county,Yuyao city,and Fenghua district had large ecological land areas,however,prioritized restoration and protection zones in Ninghai and Fenghua were also large.The analysis results are expected to provide a reference for optimizing a territorial ecological space in a city.展开更多
The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use...The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover,and the changes in ecological quality in this arid region over the last two decades are not well understood.This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level.In this study,we used the Moderate Resolution Imaging Spectroradiometer(MODIS)products to generate remote sensing ecological index(RSEI)on the Google Earth Engine(GEE)platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades(from 2000 to 2020).We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality.We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products.Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%.The ecological quality in Xinjiang has increased significantly over the last two decades,with the northern part of this region having a better ecological quality than the southern part.The areas with slightly improved ecological quality accounted for 31.26%of the total land area of Xinjiang,whereas only 3.55%of the land area was classified as having a slightly worsen(3.16%)or worsen(0.39%)ecological quality.The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature,precipitation,closed shrublands,grasslands and savannas were the top five environmental factors affecting the changes in RSEI.Environmental factors were allocated different weights for different RSEI categories.In general,the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial.Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.展开更多
For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological...For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.展开更多
Shuozhou is a typical coal mining city,and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China.The mining of coal resources is an important part of ensuring national...Shuozhou is a typical coal mining city,and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China.The mining of coal resources is an important part of ensuring national energy security,and at the same time,it inevitably has a certain impact on the ecology,such as coal dust generated by open-pit mining will affect air quality,soil,water and vegetation.It is of great significance to explore the temporal and spatial variation of ecological environment quality in coal mining cities for ecological protection and sustainable social and economic development.Based on the Google Earth Engine(GEE)platform,this paper combines the index-based coal dust index(ICDI)and Remote Sensing Ecological Index(RSEI)models to construct an improved RSEI(IRSEI)that can reflect coal mining cities.This paper explores the spatial-temporal evolution characteristics and spatial correlation of ecological environment quality in Shuozhou from 2000 to 2020.The results showed that the average value of IRSEI in Shuozhou was between 0.262 and 0.418,and the overall change showed an upward trend.The growth areas of ecological environment quality are mainly located in the eastern and southwestern areas with good vegetation growth,and these regions have vigorously implemented the Northern Shelter Forest Project,afforestation and greening projects,implemented the forest resource management and protection responsibility system,promoted the construction of ecological civilization,and significantly improved the ecological environment.While the declining areas are mainly located in the central and southern regions where mining activities and human activities are more intensive.The IRSEI in the study area showed a significant spatial positive correlation,and the agglomeration types of the spatial pattern were mainly high-high and low-low agglomeration types,with the high-high agglomeration types mainly distributed in the eastern and southwestern regions,and the low-low agglomeration types distributed in the northern and south-central regions of the study area.The trend of low and low agglomeration has decreased,which further proves that the ecological restoration measures taken by the government,such as returning farmland to forests,integrating protection and restoration of mountains,waters,forests,fields,lakes,grasslands,and sands,controlling soil erosion,and stage wise reclamation of coal mining subsidence areas,have improved the ecological environment quality of Shuozhou.This study provides a reference for understanding the spatiotemporal changes of the ecological environment of coal mining cities,and is conducive to formulating appropriate ecological protection strategies.展开更多
The Caohai Nature Reserve is one of the three major plateau freshwater lakes in China.Since the 1950s,human activities such as land reclamation and population relocation have greatly damaged Caohai.A rapid evaluation ...The Caohai Nature Reserve is one of the three major plateau freshwater lakes in China.Since the 1950s,human activities such as land reclamation and population relocation have greatly damaged Caohai.A rapid evaluation of the spatiotemporal evolution trend of the ecological quality of the Caohai Nature Reserve is significant for the maintenance and construction of the ecosystem in this area.The research is based on the Google Earth Engine(GEE)remote sensing cloud computing platform.Landsat TM/OLI images from May to October in five time periods:2000-2002,2004-2006,2009-2011,2014-2016,and 2019-2021 were obtained to reconstruct the optimal cloud image set by averaging the images in each time period.By constructing four ecological indicators:Greenness(NDVI),Wetness(Wet),Hotness(LST),and Dryness(NDBSI),and using Principal Component Analysis(PCA)method to obtain the Remote Sensing Ecological Index(RSEI)for the corresponding years,the spatiotemporal variation of ecological quality in the Caohai Nature Reserve over 20 years was analyzed.The results indicate:①the mean value of RSEI increased from 0.460 in 2000-2002 to 0.772 in 2019-2021,a 67.83%increase,indicating a significant improvement in the ecological quality of the reserve over the 20 years;②from the perspective of functional zoning of the Caohai Nature Reserve,the ecological quality of the core area showed a degrading trend,while the ecological quality of the buffer zone and experimental zone significantly improved;③with the implementation of ecological restoration projects,the ecological quality of the reserve gradually recovered and improved from 2014 to 2021.The trend of RSEI value changes is well correlated with human interventions,indicating that the PCA-based RSEI model can be effectively used for ecological quality assessment in lake areas.展开更多
Urbanization in small-and medium-sized cities has often been overlooked in urban studies.Research on urbanization has predominantly focused on large metropolitan cities;however,urbanization in small-and medium-sized c...Urbanization in small-and medium-sized cities has often been overlooked in urban studies.Research on urbanization has predominantly focused on large metropolitan cities;however,urbanization in small-and medium-sized cities also contributes to the acceleration of urban sprawl.Urban growth boundary(UGB)is an ecological approach designed to limit urban development.This study aimedto analyze environmental protection priority zonesby combining ecological quality and sensitivity indices to identify the areas suitable for UGB implementation.Tegal City and its surrounding areas(including Tegal and Brebes regencies)of Indonesia were selected as the study area.The ecological quality index was calculated using the normalized difference vegetation index,humidity index,land surface temperature,and normalized difference bare soil index.These indices were subsequently subjected to principal component analysis(PCA)to extract orthogonal factors,which were summed to derive the final index value.In parallel,we mapped and evaluated ecological sensitivity based on spatial planning policies and regulations.The results revealed that ecological quality in Tegal and Brebes regencies was predominantly categorized as good and very good ecological quality,whereas TegalCity exhibited moderate and poor ecological quality.Additionally,over 45.00%of the area in Tegal and Brebes regencies demonstrated very high ecological sensitivity.Consequently,more than 50.00%of the area in Tegal and Brebes regencies,along with 27.00%of Tegal City,were classified as ecological constraint zone,making them potential regionsfor UGB development.The UGB is expected to curtail urban expansion,promote compact city planning,and preserve ecosystem services to achieve urban sustainability.This study implies that planningsmall-and medium-sized cities is important to prevent urban sprawl and maintain environmental health.Designing UGB to limit urban expansion should be enhanced by better knowledge about its ecological functions in supporting urban sustainability.展开更多
城市用地空间扩张对生态环境的影响映射出人类社会活动和生态环境保护之间的交互作用,系统地研究城市空间无序蔓延所诱发的城市土地利用方式变化对城市生态环境的影响程度,对助推中国生态文明建设目标具有重要现实意义。为探究合肥市城...城市用地空间扩张对生态环境的影响映射出人类社会活动和生态环境保护之间的交互作用,系统地研究城市空间无序蔓延所诱发的城市土地利用方式变化对城市生态环境的影响程度,对助推中国生态文明建设目标具有重要现实意义。为探究合肥市城市扩张对生态安全格局的影响程度,综合运用生态遥感指数、最小累积阻力模型、电路理论和斑块生成土地利用模拟模型,构建合肥市生态安全格局,识别生态夹点和生态障碍点,再从模拟验证的基础上(总体精度为94.71%,Kappa系数为90.04%,Fom值为0.102),预测了2030—2040年的城市扩张,并根据预测结果探讨城市扩张对区域生态安全格局影响程度。研究发现:合肥市生态环境质量整体呈现南高中低的分布格局,识别出合肥市生态源地共计35处,源地间活跃生态廊道70条,非活跃廊道共17条,生态夹点290个,生态障碍点112个。2020—2040年合肥市城乡、工矿居民用地、林地、水域和未利用土地面积将不断增加,而耕地以及草地面积将持续减少。2020—2040年期间城镇建成区分别侵占了生态廊道、源地、夹点、障碍点面积为55.95、10.51、1.04、1.35 km 2。研究结果可为今后快速发展城市的生态环境治理和国土空间生态保护修复工作提供理论依据和技术参考。展开更多
Eco-environmental quality is a measure of the suitability of the ecological environment for human survival and socioeconomic development.Understanding the spatial-temporal distribution and variation trend of eco-envir...Eco-environmental quality is a measure of the suitability of the ecological environment for human survival and socioeconomic development.Understanding the spatial-temporal distribution and variation trend of eco-environmental quality is essential for environmental protection and ecological balance.The remote sensing ecological index(RSEI)can quickly and objectively quantify eco-environmental quality and has been extensively utilized in regional ecological environment assessment.In this paper,Moderate Resolution Imaging Spectroradiometer(MODIS)images during the growing period(July-September)from 2000 to 2020 were obtained from the Google Earth Engine(GEE)platform to calculate the RSEI in the three northern regions of China(the Three-North region).The Theil-Sen median trend method combined with the Mann-Kendall test was used to analyze the spatial-temporal variation trend of eco-environmental quality,and the Hurst exponent and the Theil-Sen median trend were superimposed to predict the future evolution trend of eco-environmental quality.In addition,ten variables from two categories of natural and anthropogenic factors were analyzed to determine the drivers of the spatial differentiation of eco-environmental quality by the geographical detector.The results showed that from 2000 to 2020,the RSEI in the Three-North region exhibited obvious regional characteristics:the RSEI values in Northwest China were generally between 0.2 and 0.4;the RSEI values in North China gradually increased from north to south,ranging from 0.2 to 0.8;and the RSEI values in Northeast China were mostly above 0.6.The average RSEI value in the Three-North region increased at an average growth rate of 0.0016/a,showing the spatial distribution characteristics of overall improvement and local degradation in eco-environmental quality,of which the areas with improved,basically stable and degraded eco-environmental quality accounted for 65.39%,26.82%and 7.79%of the total study area,respectively.The Hurst exponent of the RSEI ranged from 0.20 to 0.76 and the future trend of eco-environmental quality was generally consistent with the trend over the past 21 years.However,the areas exhibiting an improvement trend in eco-environmental quality mainly had weak persistence,and there was a possibility of degradation in eco-environmental quality without strengthening ecological protection.Average relative humidity,accumulated precipitation and land use type were the dominant factors driving the spatial distribution of eco-environmental quality in the Three-North region,and two-factor interaction also had a greater influence on eco-environmental quality than single factors.The explanatory power of meteorological factors on the spatial distribution of eco-environmental quality was stronger than that of topographic factors.The effect of anthropogenic factors(such as population density and land use type)on eco-environmental quality gradually increased over time.This study can serve as a reference to protect the ecological environment in arid and semi-arid regions.展开更多
Desertification has had a significant impact on the ecological environment of the Yellow River Basin(YRB)in China.However,previous studies on the evaluation of the ecological environment quality(EEQ)in the YRB have pa...Desertification has had a significant impact on the ecological environment of the Yellow River Basin(YRB)in China.However,previous studies on the evaluation of the ecological environment quality(EEQ)in the YRB have paid limited attention to the indicator of desertification.It is of great significance to incorporate the desertification index into the spatiotemporal assessment of the EEQ in the YRB in order to protect the ecological environment in the region.In this study,based on multi-source remote sensing data from 91 cities in the YRB,this article proposes a desertification remote sensing ecological index(DRSEI)model,which builds upon the traditional Remote Sensing Ecological Index(RSEI)model,to analyze the spatiotemporal changes in the EEQ in the YRB from 2001 to 2021.Furthermore,using the geographic detector(GD),and geographically and temporally weighted regression(GTWR)model,the study assesses the impact of human and natural factors on the EEQ in the YRB.The research findings indicate that:(1)Compared to the traditional RSEI,the improved DRSEI shows a decreasing trend in the evaluation results of the EEQ.Among the 24 cities,the change in DRSEI exceeds 0.05 compared to RSEI,accounting for 26.37%of the YRB.The remaining 67 cities have changes within a range of less than 0.05,accounting for 73.63%of the YRB.(2)The results of the GD for individual and interactive effects reveal that rainfall and elevation have significant individual and interactive effects on the EEQ.Furthermore,after the interaction with natural factors,the explanatory power of human factors gradually increases over time.The spatial heterogeneity results of GTWR demonstrate that rainfall has a strong direct positive impact on the EEQ,accounting for 98.90%of the influence,while temperature exhibits a more pronounced direct inhibitory effect,accounting for 76.92%of the influence.Human activities have a strong negative impact on the EEQ and a weak positive impact.展开更多
基金This research was financially supported by the West Light Foundation of the Chinese Academy of Science(2017-XBQNXZ-B-018)the National Natural Science Foundation of China(41861144020)the National Key Research and Development Program of China-Joint Research on Technology to Combat Desertification for African Countries of the“Great Green Wall”(2018YFE0106000).
文摘Long-term monitoring of the ecological environment changes is helpful for the protection of the ecological environment.Based on the ecological environment of the Sahel region in Africa,we established a remote sensing ecological index(RSEI)model for this region by combining dryness,moisture,greenness,and desertification indicators.Using the Moderate-resolution Imaging Spectroradiometer(MODIS)data in Google Earth Engine(GEE)platform,this study analyzed the ecological environment quality of the Sahel region during the period of 2001-2020.We used liner regression and fluctuation analysis methods to study the trend and fluctuation of RSEI,and utilized the stepwise regression approach to analyze the contribution of each indicator to the RSEI.Further,the correlation analysis was used to analyze the correlation between RSEI and precipitation,and Hurst index was applied to evaluate the change trend of RSEI in the future.The results show that RSEI of the Sahel region exhibited spatial heterogeneity.Specifically,it exhibited a decrease in gradient from south to north of the Sahel region.Moreover,RSEI in parts of the Sahel region presented non-zonal features.Different land-cover types demonstrated different RSEI values and changing trends.We found that RSEI and precipitation were positively correlated,suggesting that precipitation is the controlling factor of RSEI.The areas where RSEI values presented an increasing trend were slightly less than the areas where RSEI values presented a decreasing trend.In the Sahel region,the areas with the ecological environment characterized by continuous deterioration and continuous improvement accounted for 44.02%and 28.29%of the total study area,respectively,and the areas in which the ecological environment was changing from improvement to deterioration and from deterioration to improvement accounted for 12.42%and 15.26%of the whole area,respectively.In the face of the current ecological environment and future change trends of RSEI in the Sahel region,the research results provide a reference for the construction of the"Green Great Wall"(GGW)ecological environment project in Africa.
基金This work was funded by the National Natural Science Foundation of China(U1603242)the Major Science and Technology Projects in Inner Mongolia,China(ZDZX2018054).
文摘The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.
基金Financial support for this work was provided by the National Natural Science Foundation of China (No. 41040011)the Fun-damental Research Funds for the Central Universities (No.CHD2010JC103)
文摘Based on multi-type,multi-temporal remote sensing data,we have monitored recent changes in cultivated land use and vegetation,in sandy areas and salinized desertification in the Green Corridor zone of the main channel of the Tarim River Basin.The results of our investigation show that the ecological environment in the Green Corridor of the main channel of the Tarim River Basin has conspicuously improved from 2002 to 2004.These improvements show up largely in such aspects as an increase in the rate of vegetation cover,a reduction in desertification land areas and a weakening in the intensity of sandy and the salinized land.On the other hand,the cultivated area in the Tarim River Basin significantly increased from 2002 to 2004.The rate of growth in cultivated areas during this period was significantly higher than that from 1999 to 2002.The increase in the use of irrigation resulting from the substantial increase in cultivated areas has a long-term potential restraining effect on the restoration of ecological functions of the Tarim River.
基金the financial support given by the Special Funds for Science and Technology Innovation on Carbon Peak Carbon Neutral of Jiangsu Province,China(BK20220017)the Innovation Development Project of China Meteorological Administration(CXFZ2023J073)the National Key R&D Program of China(2018YFC1506606).
文摘Otindag Sandy Land in China is an important ecological barrier to Beijing;the changes in its ecological quality are major concerns for sustainable development and planning of this area.Based on principal component analysis and path analysis,we first generated a modified remote sensing ecological index(MRSEI)coupled with satellite and ground observational data during 2001–2020 that integrated four local indicators(greenness,wetness,and heatness that reflect vegetation status,water,and heat conditions,respectively,as well as soil erosion).Then,we assessed the ecological quality in Otindag Sandy Land during 2001–2020 based on the MRSEI at different time scales(i.e.,the whole year,growing season,and non-growing season).MRSEI generally increased with an upward rate of 0.006/a during 2001–2020,with clear seasonal and spatial variations.Ecological quality was significantly improved in most regions of Otindag Sandy Land but degraded in the southern part.Regions with ecological degradation expanded to 18.64%of the total area in the non-growing season.The area with the worst grade of MRSEI shrunk by 15.83%of the total area from 2001 to 2020,while the area with the best grade of MRSEI increased by 9.77%of the total area.The temporal heterogeneity of ecological conditions indicated that the improvement process of ecological quality in the growing season may be interrupted or deteriorated in the following non-growing season.The implementation of ecological restoration measures in Otindag Sandy Land should not ignore the seasonal characteristics and spatial heterogeneity of local ecological quality.The results can explore the effectiveness of ecological restoration and provide scientific guides on sustainable development measures for drylands.
文摘In order to understand the development status of ecological environment quality in the Aksu region of China, to effectively adjust the ecological environment quality, so as to promote the sustainable development of its social economy and ecological environment protection. This paper selects the Landsat series remote sensing images of the northern Aksu region in 2013, 2016, and 2019, and uses the tools such as ENVI5.3 and ArcGIS 10.8.1 to process the image data accordingly. The principal component analysis method is used to calculate the Remote Sensing Ecological Index (RSEI) of the northern Aksu region. The data show that: 1) The ecological environment quality index in the northern Aksu region in 2013, 2016, and 2019 was 0.706087, 0.25243 and 0.362991 respectively;2) The areas where the ecological environment quality declined significantly in the northern Aksu region were the human settlements and the Gobi, fan-shaped land and other special terrain areas;3) The humidity index and the heat index are the two factors that have the greatest impact on the ecological environment quality in the northern Aksu area. The data as a whole show that the ecological environment in the northern part of the Aksu region has deteriorated seriously, and the severely deteriorated area is close to the human living area.
基金Supported by Guizhou Provincial Key Technology R&D Program ([2023]General 211)Guizhou Science and Technology Innovation Base Construction Project (Qian Ke He Zhong Yin Di[2023]005).
文摘Fast and effective remote sensing monitoring is an important means for analyzing the spatio-temporal changes in ecological quality in fragile karst regions.This study focuses on Guanling Autonomous County,a national-level demonstration county for comprehensive desertification control.Based on Landsat TM/OLI remote sensing image data from 2005,2010,2015,and 2020,remote sensing ecological indices were used to analyze the spatio-temporal changes in ecological quality in Guanling Autonomous County from 2005 to 2020.The results show that:①the variance contribution rates of the first principal component for the four periods were 66.31%,71.59%,63.18%,and 75.24%,indicating that PC1 integrated most of the characteristics of the four indices,making the RSEI suitable for evaluating ecological quality in karst mountain areas;②the remote sensing ecological index grades have been increasing year by year,with an overall trend of improving ecological quality.The area of higher-grade ecological quality has increased spatially,while fragmented patches have gradually decreased,becoming more concentrated in the low-altitude areas in the northwest and east,and there is a trend of expansion towards higher-altitude areas;③the ecological environment quality in most areas has improved,with the improvement in RSEI spatio-temporal variation becoming more noticeable with increasing slope.Areas of higher-grade quality appeared in 2010,and the range of higher-grade quality expanded with increasing slope.
文摘In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.
基金This research was supported by the Fundamental Research Program of Shanxi Province(202203021212497,20210302123265)the Shanxi Normal University School Fund(Research Project on Major Issues of High-Quality Development in Shanxi Province,GZLFZ2327).
文摘The middle reaches of the Yellow River represent a critically ecologically sensitive and fragile area within the Yellow River Basin(YRB),holding significant scientific value for ecological security assessment and environmental management strategies.This study comprehensively evaluates the evolution of the eco-environment in the“Two Mountains,Seven Rivers,and One Basin”(TSO)area of Shanxi Province from 2000 to 2020 based on fraction vegetation cover(FVC)derived from the Normalized Difference Vegetation Index(NDVI),net primary productivity(NPP)calculated via the Carnegie–Ames–Stanford approach(CASA),and the remote sensing ecological index(RSEI).The results indicate a significant improvement in the TSO’s eco-environment from 2000 to 2020,with the RSEI values increased from 0.34 in 2000 to 0.41 in 2020(an increase of 17.76%).Both FVC and NPP demonstrated notable upward trends,with FVC increasing by 22.74%and NPP by 53.11%.Spatially,FVC rose by 21.84%,19.72%and 26.06%,respectively in the Two Mountains,Seven Rivers,and the YRB in Shanxi Province.Similarly,the NPPs increased by 51.60%,48.60%,and 61.65%in these regions over the past 21 years.Both FVC and NPP exhibited decreasing patterns from southeast to northwest,with significant eco-environmental improvements in the northern region and slower recovery in the southern region.Precipitation was the primary causes influencing vegetation recovery,showing positive trends in the central and northern TSO regions,while this trend reversed in the southern.The RSEI value indicate substantial eco-environment improvements in the central and northern areas(Sanggan,Daqing and Hutuo River Basins),whereas the southern regions(e.g.,Zhang,Qin,Fen and Sushui River Basins)remain in poor grade.Human activities,particularly land use/cover changes marked by increased forestation and urbanization alongside decreased cultivated land,significantly affected vegetation cover patterns.This study provides scientific references for formulating policies on ecological construction and high-quality development in the YRB.
基金National Natural Science Foundation of China,No.41971268。
文摘Regular quantitative assessments of regional ecological environment quality(EEQ)and driving force analyses are highly important for environmental protection and sustainable development.Northern China is a typical climate-sensitive and ecologically vulnerable area,however,the changes in EEQ in this region and their underlying causes remain unclear.Traditional evaluations of EEQ rely primarily on the remote sensing ecological index(RSEI),which lacks assessments of indicators such as greenness(NDVI),humidity(WET),heat(LST),and dryness(NDBSI).To address these issues,this study employs the principal component analysis method and the Google Earth Engine to construct an RSEI suitable for long-term and large-scale applications and analyzes the spatio-temporal variations in the RSEI,NDVI,WET,NDBSI,and LST.Additionally,geographical detectors are utilized to analyze the driving factors affecting EEQ.The results indicate the following.(1)The RSEI shows a fluctuating upward trend,with an average value of 0.4566,indicating a gradual improvement in EEQ.The EEQ exhibited significant spatial heterogeneity,with a pattern of lower values in the west and higher values in the east.(2)The NDVI and WET exhibit fluctuating increasing trends,indicating improvements in both indices.The NDBSI shows a fluctuating decreasing trend,whereas the LST presents a fluctuating increasing trend,suggesting an improvement in the NDBSI and a slight deterioration in the LST.NDVI and WET demonstrate a spatial pattern characterized by low values in the west and high values in the east.NDBSI and LST demonstrate a spatial pattern characterized by low values in the east and high values in the west.(3)Land use types and precipitation are the primary driving factors influencing the spatial differentiation of the EEQ.The explanatory power of these driving factors significantly increases under their interactions,particularly the interaction between land use types and other driving factors.This study fills the gap in existing EEQ evaluations that analyze only the RSEI without considering the NDVI,WET,NDBSI,and LST.The findings provide new insights for EEQ assessments and serve as a scientific reference for environmental protection and sustainable development.
基金funded by the National Natural Science Foundation of China(42361017)the Gansu Provincial Science and Technology Program-Special Program for Key Research and Development(R&D)on Ecological Civilization Construction in Gansu Province(24YFFA050)the Gansu Agricultural University-Gansu Provincial Academy of Natural Resources Planning Joint Graduate Training Base Project(GAU2024-003)。
文摘The Loess Plateau(LP),one of the most ecologically fragile regions in China,is affected by severe soil erosion and environmental degradation.Despite large-scale ecological restoration efforts made by Chinese government in recent years,the region continues to face significant ecological challenges due to the combined impact of climate change and human activities.In this context,we developed a kernal Remote Sensing Ecological Index(kRSEI)using Moderate Resolution Imaging Spectroradiometer(MODIS)products on the Google Earth Engine(GEE)platform to analyze the spatiotemporal patterns and trends in ecological environmental quality(EEQ)across the LP from 2000 to 2022 and project future trajectories.Then,we applied partial correlation analysis and multivariate regression residual analysis to further quantify the relative contributions of climate change and human activities to EEQ.During the study period,the kRSEI values exhibited significant spatial heterogeneity,with a stepwise degradation pattern in the southeast to northwest across the LP.The maximum(0.51)and minimum(0.46)values of the kRSEI were observed in 2007 and 2021,respectively.Trend analyses revealed a decline in EEQ across the LP.Hurst exponent analysis predicted a trend of weak anti-persistent development in most of the plateau areas in the future.A positive correlation was identified between kRSEI and precipitation,particularly in the central and western regions;although,improvements were limited by a precipitation threshold of 837.66 mm/a.A moderate increase in temperature was shown to potentially benefit the ecological environment within a certain range;however,temperature of-1.00°C-7.95°C often had a negative impact on the ecosystem.Climate change and human activities jointly influenced 65.78%of LP area on EEQ,primarily having a negative impact.In terms of contribution,human activities played a dominant role in driving changes in EEQ across the plateau.These findings provide crucial insights for accurately assessing the ecological state of the LP and suggest the design of future restoration strategies.
基金funded by the Fujian Province's Foreign Cooperation Project in 2023(2023I0047)the Fujian Provincial Natural Science Foundation Project(2023J011432,2024J011195)+3 种基金the Ministry of Education's Supply-demand Docking Employment and Education Project(2024011223947)the Open Project Fund of Hunan Provincial Key Laboratory for Remote Sensing Monitoring of Ecological Environment in Dongting Lake Area(DTH Key Lab.2024-04,2022-04)the Fujian Provincial Natural Science Foundation Guiding Project(2024Y0057)the Fujian Province Social Science Plan Project(FJ2024BF071).
文摘Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid and semi-arid areas.This study took the Helan Mountain,a typical arid and semi-arid area in China,as the study area.By adopting an Enhanced Remote Sensing Ecological Index(ERSEI)that integrates the habitat quality(HQ)index with the Remote Sensing Ecological Index(RSEI),we quantified the ecological environment quality of the Helan Mountain during 2010-2022 and analyzed the driving factors behind the changes.Principal Component Analysis(PCA)was used to validate the composite ERSEI,enabling the extraction of key features and the reduction of redundant information.The results showed that the contributions of first principal component(PC1)for ERSEI and RSEI were 80.23%and 78.72%,respectively,indicating that the ERSEI can provide higher precision and more details than the RSEI in assessing ecological environment quality.Temporally,the ERSEI in the Helan Mountain exhibited an initial decline followed by an increase from 2010 to 2022,with the average value of ERSEI ranging between 0.298 and 0.346.Spatially,the ERSEI showed a trend of being higher in the southwest and lower in the northeast,with high-quality ecological environments mainly concentrated in the western foothills at higher altitudes.The centroid of ERSEI shifted northeastward toward Helan County from 2010 to 2022.Temperature and digital elevation model(DEM)emerged as the primary drivers of ERSEI changes.This study highlights the necessity of using comprehensive monitoring tools to guide policy-making and conservation strategies,ensuring the resilience of fragile ecosystems in the face of ongoing climatic and anthropogenic pressures.The findings offer valuable insights for the sustainable management and conservation in arid and semi-arid ecosystems.
基金National Natural Science Foundation of China,No.41976209。
文摘Studying an ecological restoration zoning process under the background of ecological security patterns is of great significance to the rapid adjustment and optimization of a landscape pattern.In this study,a remote sensing ecological index and a morphological spatial pattern analysis method were used to assess the quality of habitats and identify ecological sources in the city of Ningbo;ecological corridors,ecological pinch points,and ecological barrier points were extracted by using a circuit theory to construct ecological security patterns and ecological restoration zones.The results indicate:(1)There were 47 ecological sources,and 83 key ecological corridors in Ningbo,and the ecological land area was about 1898.39 km^(2),accounting for 19.89%of the total study area.(2)The ecological source areas were distributed in“one patch and three belts”,and the low-resistance ecological corridors were concentrated in southern Yuyao city,western Haishu district,and central and western Fenghua district;the ecological network in the western and southern regions was dense.(3)There were four types of ecological restoration zones that need to be established,which were prioritized restoration zones,prioritized protection zones,key conservation zones,and general conservation zones distributed hierarchically from inner part towards outside.(4)Ninghai county,Yuyao city,and Fenghua district had large ecological land areas,however,prioritized restoration and protection zones in Ninghai and Fenghua were also large.The analysis results are expected to provide a reference for optimizing a territorial ecological space in a city.
基金the Key Laboratory Open Subjects of Xinjiang Uygur Autonomous Region Science and Technology Department(2020D04038)the Key Project of Natural Science Foundation of Xinjiang Uygur Autonomous Region(2021D01D06)the National Natural Science Foundation of China(41961059).
文摘The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover,and the changes in ecological quality in this arid region over the last two decades are not well understood.This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level.In this study,we used the Moderate Resolution Imaging Spectroradiometer(MODIS)products to generate remote sensing ecological index(RSEI)on the Google Earth Engine(GEE)platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades(from 2000 to 2020).We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality.We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products.Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%.The ecological quality in Xinjiang has increased significantly over the last two decades,with the northern part of this region having a better ecological quality than the southern part.The areas with slightly improved ecological quality accounted for 31.26%of the total land area of Xinjiang,whereas only 3.55%of the land area was classified as having a slightly worsen(3.16%)or worsen(0.39%)ecological quality.The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature,precipitation,closed shrublands,grasslands and savannas were the top five environmental factors affecting the changes in RSEI.Environmental factors were allocated different weights for different RSEI categories.In general,the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial.Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.
基金supported by the Guangxi Natural Science Foundation(2020GXNSFAA297266)Doctoral Research Foundation of Guilin University of Technology(GUTQDJJ2007059)Guangxi Hidden Metallic Mineral Exploration Key Laboratory。
文摘For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.
基金This research was funded by the National Natural Science Foundation of China(42377472,42174055)Jiangxi Provincial Social Science Foundation Project(23GL34)+4 种基金Humanities and social science research project of universities in Jiangxi Province(GL22228)Open Fund of Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of the Ministry of Natural Resources(MEMI-2021-2022-28)Science and Technology Research Project of Jiangxi Provincial Department of Education(GJJ2200741)the Graduate Innovation Fund of Jiangxi(YC2023-S557)the Doctoral Research Initiation fund of East China University of Technology(DHBK2019184).
文摘Shuozhou is a typical coal mining city,and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China.The mining of coal resources is an important part of ensuring national energy security,and at the same time,it inevitably has a certain impact on the ecology,such as coal dust generated by open-pit mining will affect air quality,soil,water and vegetation.It is of great significance to explore the temporal and spatial variation of ecological environment quality in coal mining cities for ecological protection and sustainable social and economic development.Based on the Google Earth Engine(GEE)platform,this paper combines the index-based coal dust index(ICDI)and Remote Sensing Ecological Index(RSEI)models to construct an improved RSEI(IRSEI)that can reflect coal mining cities.This paper explores the spatial-temporal evolution characteristics and spatial correlation of ecological environment quality in Shuozhou from 2000 to 2020.The results showed that the average value of IRSEI in Shuozhou was between 0.262 and 0.418,and the overall change showed an upward trend.The growth areas of ecological environment quality are mainly located in the eastern and southwestern areas with good vegetation growth,and these regions have vigorously implemented the Northern Shelter Forest Project,afforestation and greening projects,implemented the forest resource management and protection responsibility system,promoted the construction of ecological civilization,and significantly improved the ecological environment.While the declining areas are mainly located in the central and southern regions where mining activities and human activities are more intensive.The IRSEI in the study area showed a significant spatial positive correlation,and the agglomeration types of the spatial pattern were mainly high-high and low-low agglomeration types,with the high-high agglomeration types mainly distributed in the eastern and southwestern regions,and the low-low agglomeration types distributed in the northern and south-central regions of the study area.The trend of low and low agglomeration has decreased,which further proves that the ecological restoration measures taken by the government,such as returning farmland to forests,integrating protection and restoration of mountains,waters,forests,fields,lakes,grasslands,and sands,controlling soil erosion,and stage wise reclamation of coal mining subsidence areas,have improved the ecological environment quality of Shuozhou.This study provides a reference for understanding the spatiotemporal changes of the ecological environment of coal mining cities,and is conducive to formulating appropriate ecological protection strategies.
基金Supported by Joint Project between Bijie Science and Technology Bureau and Guizhou University of Engineering Science (Bike Lianhe Zi (Guigongcheng)[2021]03)Guizhou Provincial Key Technology R&D Program (Qiankehe[2023]General 211).
文摘The Caohai Nature Reserve is one of the three major plateau freshwater lakes in China.Since the 1950s,human activities such as land reclamation and population relocation have greatly damaged Caohai.A rapid evaluation of the spatiotemporal evolution trend of the ecological quality of the Caohai Nature Reserve is significant for the maintenance and construction of the ecosystem in this area.The research is based on the Google Earth Engine(GEE)remote sensing cloud computing platform.Landsat TM/OLI images from May to October in five time periods:2000-2002,2004-2006,2009-2011,2014-2016,and 2019-2021 were obtained to reconstruct the optimal cloud image set by averaging the images in each time period.By constructing four ecological indicators:Greenness(NDVI),Wetness(Wet),Hotness(LST),and Dryness(NDBSI),and using Principal Component Analysis(PCA)method to obtain the Remote Sensing Ecological Index(RSEI)for the corresponding years,the spatiotemporal variation of ecological quality in the Caohai Nature Reserve over 20 years was analyzed.The results indicate:①the mean value of RSEI increased from 0.460 in 2000-2002 to 0.772 in 2019-2021,a 67.83%increase,indicating a significant improvement in the ecological quality of the reserve over the 20 years;②from the perspective of functional zoning of the Caohai Nature Reserve,the ecological quality of the core area showed a degrading trend,while the ecological quality of the buffer zone and experimental zone significantly improved;③with the implementation of ecological restoration projects,the ecological quality of the reserve gradually recovered and improved from 2014 to 2021.The trend of RSEI value changes is well correlated with human interventions,indicating that the PCA-based RSEI model can be effectively used for ecological quality assessment in lake areas.
基金funded by the Directorate of Research and Community Service, Ministry of Education, Culture, Research, and Technology, Indonesia (027/E5/PG.02.00.PL/2024)Bogor Agricultural University for their invaluable support and resources that made this research possibleDirectorate of Research and Community Service, Ministry of Education, Culture, Research, and Technology, Indonesia, for their financial and administrative support
文摘Urbanization in small-and medium-sized cities has often been overlooked in urban studies.Research on urbanization has predominantly focused on large metropolitan cities;however,urbanization in small-and medium-sized cities also contributes to the acceleration of urban sprawl.Urban growth boundary(UGB)is an ecological approach designed to limit urban development.This study aimedto analyze environmental protection priority zonesby combining ecological quality and sensitivity indices to identify the areas suitable for UGB implementation.Tegal City and its surrounding areas(including Tegal and Brebes regencies)of Indonesia were selected as the study area.The ecological quality index was calculated using the normalized difference vegetation index,humidity index,land surface temperature,and normalized difference bare soil index.These indices were subsequently subjected to principal component analysis(PCA)to extract orthogonal factors,which were summed to derive the final index value.In parallel,we mapped and evaluated ecological sensitivity based on spatial planning policies and regulations.The results revealed that ecological quality in Tegal and Brebes regencies was predominantly categorized as good and very good ecological quality,whereas TegalCity exhibited moderate and poor ecological quality.Additionally,over 45.00%of the area in Tegal and Brebes regencies demonstrated very high ecological sensitivity.Consequently,more than 50.00%of the area in Tegal and Brebes regencies,along with 27.00%of Tegal City,were classified as ecological constraint zone,making them potential regionsfor UGB development.The UGB is expected to curtail urban expansion,promote compact city planning,and preserve ecosystem services to achieve urban sustainability.This study implies that planningsmall-and medium-sized cities is important to prevent urban sprawl and maintain environmental health.Designing UGB to limit urban expansion should be enhanced by better knowledge about its ecological functions in supporting urban sustainability.
文摘城市用地空间扩张对生态环境的影响映射出人类社会活动和生态环境保护之间的交互作用,系统地研究城市空间无序蔓延所诱发的城市土地利用方式变化对城市生态环境的影响程度,对助推中国生态文明建设目标具有重要现实意义。为探究合肥市城市扩张对生态安全格局的影响程度,综合运用生态遥感指数、最小累积阻力模型、电路理论和斑块生成土地利用模拟模型,构建合肥市生态安全格局,识别生态夹点和生态障碍点,再从模拟验证的基础上(总体精度为94.71%,Kappa系数为90.04%,Fom值为0.102),预测了2030—2040年的城市扩张,并根据预测结果探讨城市扩张对区域生态安全格局影响程度。研究发现:合肥市生态环境质量整体呈现南高中低的分布格局,识别出合肥市生态源地共计35处,源地间活跃生态廊道70条,非活跃廊道共17条,生态夹点290个,生态障碍点112个。2020—2040年合肥市城乡、工矿居民用地、林地、水域和未利用土地面积将不断增加,而耕地以及草地面积将持续减少。2020—2040年期间城镇建成区分别侵占了生态廊道、源地、夹点、障碍点面积为55.95、10.51、1.04、1.35 km 2。研究结果可为今后快速发展城市的生态环境治理和国土空间生态保护修复工作提供理论依据和技术参考。
基金supported by the National Natural Science Foundation of China(31971578)the Scientific Research Fund of Changsha Science and Technology Bureau(kq2004095)+2 种基金the National Bureau to Combat Desertification,State Forestry Administration of China(101-9899)the Training Fund of Young Professors from Hunan Provincial Education Department(90102-7070220090001)the Postgraduate Scientific Research Innovation Project of Hunan Province(CX20220707)。
文摘Eco-environmental quality is a measure of the suitability of the ecological environment for human survival and socioeconomic development.Understanding the spatial-temporal distribution and variation trend of eco-environmental quality is essential for environmental protection and ecological balance.The remote sensing ecological index(RSEI)can quickly and objectively quantify eco-environmental quality and has been extensively utilized in regional ecological environment assessment.In this paper,Moderate Resolution Imaging Spectroradiometer(MODIS)images during the growing period(July-September)from 2000 to 2020 were obtained from the Google Earth Engine(GEE)platform to calculate the RSEI in the three northern regions of China(the Three-North region).The Theil-Sen median trend method combined with the Mann-Kendall test was used to analyze the spatial-temporal variation trend of eco-environmental quality,and the Hurst exponent and the Theil-Sen median trend were superimposed to predict the future evolution trend of eco-environmental quality.In addition,ten variables from two categories of natural and anthropogenic factors were analyzed to determine the drivers of the spatial differentiation of eco-environmental quality by the geographical detector.The results showed that from 2000 to 2020,the RSEI in the Three-North region exhibited obvious regional characteristics:the RSEI values in Northwest China were generally between 0.2 and 0.4;the RSEI values in North China gradually increased from north to south,ranging from 0.2 to 0.8;and the RSEI values in Northeast China were mostly above 0.6.The average RSEI value in the Three-North region increased at an average growth rate of 0.0016/a,showing the spatial distribution characteristics of overall improvement and local degradation in eco-environmental quality,of which the areas with improved,basically stable and degraded eco-environmental quality accounted for 65.39%,26.82%and 7.79%of the total study area,respectively.The Hurst exponent of the RSEI ranged from 0.20 to 0.76 and the future trend of eco-environmental quality was generally consistent with the trend over the past 21 years.However,the areas exhibiting an improvement trend in eco-environmental quality mainly had weak persistence,and there was a possibility of degradation in eco-environmental quality without strengthening ecological protection.Average relative humidity,accumulated precipitation and land use type were the dominant factors driving the spatial distribution of eco-environmental quality in the Three-North region,and two-factor interaction also had a greater influence on eco-environmental quality than single factors.The explanatory power of meteorological factors on the spatial distribution of eco-environmental quality was stronger than that of topographic factors.The effect of anthropogenic factors(such as population density and land use type)on eco-environmental quality gradually increased over time.This study can serve as a reference to protect the ecological environment in arid and semi-arid regions.
基金supported by the National Science Foundation of China (Grant Number: 72004116)the Hubei Social Science Foundation (Grant NO. 2022CFB292)
文摘Desertification has had a significant impact on the ecological environment of the Yellow River Basin(YRB)in China.However,previous studies on the evaluation of the ecological environment quality(EEQ)in the YRB have paid limited attention to the indicator of desertification.It is of great significance to incorporate the desertification index into the spatiotemporal assessment of the EEQ in the YRB in order to protect the ecological environment in the region.In this study,based on multi-source remote sensing data from 91 cities in the YRB,this article proposes a desertification remote sensing ecological index(DRSEI)model,which builds upon the traditional Remote Sensing Ecological Index(RSEI)model,to analyze the spatiotemporal changes in the EEQ in the YRB from 2001 to 2021.Furthermore,using the geographic detector(GD),and geographically and temporally weighted regression(GTWR)model,the study assesses the impact of human and natural factors on the EEQ in the YRB.The research findings indicate that:(1)Compared to the traditional RSEI,the improved DRSEI shows a decreasing trend in the evaluation results of the EEQ.Among the 24 cities,the change in DRSEI exceeds 0.05 compared to RSEI,accounting for 26.37%of the YRB.The remaining 67 cities have changes within a range of less than 0.05,accounting for 73.63%of the YRB.(2)The results of the GD for individual and interactive effects reveal that rainfall and elevation have significant individual and interactive effects on the EEQ.Furthermore,after the interaction with natural factors,the explanatory power of human factors gradually increases over time.The spatial heterogeneity results of GTWR demonstrate that rainfall has a strong direct positive impact on the EEQ,accounting for 98.90%of the influence,while temperature exhibits a more pronounced direct inhibitory effect,accounting for 76.92%of the influence.Human activities have a strong negative impact on the EEQ and a weak positive impact.
