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
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
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
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
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
The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region,China has undergone in recent years may face some challenges in its ecological environment.Therefore,an analysis of the spatiotem...The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region,China has undergone in recent years may face some challenges in its ecological environment.Therefore,an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development.First,we constructed an improved remote sensing-based ecological index(RSEI)in 1990,1995,2000,2005,2010,2015 and 2020 on the Google Earth Engine(GEE)platform and implemented change detection for their spatial distribution.Second,we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change(LUCC)data to analyze the reasons of RSEI changes.Finally,we investigated the applicability of improved RSEI to arid area.The results showed that mean of RSEI rose from 0.41 to 0.50,showing a slight upward trend.During the 30-a period,2.66% of the regions improved significantly,10.74% improved moderately and 32.21% improved slightly,respectively.The global Moran's I were 0.891,0.889,0.847 and 0.777 for 1990,2000,2010 and 2020,respectively,and the local indicators of spatial autocorrelation(LISA)distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis,and the low-low cluster was mainly distributed in the outer edge of the oasis.RSEI at the periphery of the oasis changes from low to high with time,with the fragmentation of RSEI distribution within the oasis increasing.Its distribution and changes are predominantly driven by anthropologic factors,including the expansion of artificial oasis into the desert,the replacement of desert ecosystems by farmland ecosystems,and the increase in the distribution of impervious surfaces.The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability.The high efficiency exhibited with this approach makes it convenient for rapid,high frequency and macroscopic monitoring of eco-environmental quality in study area.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
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
Landscape conversion becomes a continuous process in a natural landscape for any strategic development.In a forest landscape mosaic,the conversion from non-forest land to forest land implies a constructive approach.Va...Landscape conversion becomes a continuous process in a natural landscape for any strategic development.In a forest landscape mosaic,the conversion from non-forest land to forest land implies a constructive approach.Various bio-geographic processes are enriched and developed when the land was converted to forest land in a given landscape matrix.The present study evaluated how the increased forest cover improves the ecological quality of forest in Jhargram District of West Bengal State,India,from 1985 to 2015.The quality of forests includes dominance,fragmentation and connectivity,which are the basis ecological indicators of habitat structure.To address this issue,we extracted forest cover maps of 1985 and 2015 from land use/land cover classification.A grid framework was overlaid on these forest cover maps for patch-matrix model analysis.Reliable landscape ecological indices were used for the measurements of forest landscape quality in 1985 and 2015.Then a simple linear regression model was used to compare the results.Temporally,forest cover increased in Jhargram District from 1985 to 2015.The comparison of measurement indices depicts that although only a small amount of land was changed into forest land in the study area,this small change has greatly improved the structural compositional quality of the forest land.Compared with 1985,the forest land area increased by about 6930.56 hm^(2) in 2015.This increased forest cover improved the basic landscape ecological characters,such as inter patch connectivity,forest core area,forest habitat dependence,forest habitat dominance and forest edge effect.As a result,the ecosystem function in Jhargram District has been improved,which again attracts wildlife and enriches biodiversity.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
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
A Water Quality Index (WQI) is a simple numeric expression reflecting the quality of water in any ecosystem at a given time. The objective of this study was to develop a WQI for the man-made dam Francisco I. Madero lo...A Water Quality Index (WQI) is a simple numeric expression reflecting the quality of water in any ecosystem at a given time. The objective of this study was to develop a WQI for the man-made dam Francisco I. Madero located in Chihuahua, Mexico. Eight points were randomly selected in the dam area and at each point water samples were collected monthly from March 2011 to February 2012 at three depths;0.30 m, 5 m and 10 m. The following physical-chemical variables were measured: potential hydrogen (pH), electrical conductivity (EC), dissolved oxygen (DO), temperature (T), turbidity, total dissolved solids (TDS), total hardness (TH) and chlorides (Cl-). In a first step for data analysis, an analysis of variance (ANOVA) was performed for each variable considering a factorial treatment design 12 × 3 in which factor A was the month with 12 levels (sampling months) and factor B was the depth with three levels (0.30 m, 5 m and 10 m). In a second statistical step, the WQI was calculated for each month only for the surface sampling (0.30 m) and the resulting value was classified under three categories;2.5 as excellent water. The results showed the following ranges for single variables: pH of 7.63 - 10.65, EC of 190 - 320 μS·cm-1, DO of 1.30 - 12.1 mg·L-1, T of 11.30°C - 30°C, Turbidity of 0-1, 120 NTU, TDS of 170 - 220 mg·L-1, TH of 240 - 900 mg·L-1 and Cl- of 7.28 - 7034 mg·L-1. The calculated WQI demonstrated that water quality varies seasonally and was classified as poor in the rainy season to good in winter season. We conclude that in general the water from the dam is acceptable and suitable for ecological and a broad spectrum of other purposes.展开更多
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.
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.
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.
基金funded by the National Natural Science Foundation of China(42161049,41761019,41061052).
文摘The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region,China has undergone in recent years may face some challenges in its ecological environment.Therefore,an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development.First,we constructed an improved remote sensing-based ecological index(RSEI)in 1990,1995,2000,2005,2010,2015 and 2020 on the Google Earth Engine(GEE)platform and implemented change detection for their spatial distribution.Second,we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change(LUCC)data to analyze the reasons of RSEI changes.Finally,we investigated the applicability of improved RSEI to arid area.The results showed that mean of RSEI rose from 0.41 to 0.50,showing a slight upward trend.During the 30-a period,2.66% of the regions improved significantly,10.74% improved moderately and 32.21% improved slightly,respectively.The global Moran's I were 0.891,0.889,0.847 and 0.777 for 1990,2000,2010 and 2020,respectively,and the local indicators of spatial autocorrelation(LISA)distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis,and the low-low cluster was mainly distributed in the outer edge of the oasis.RSEI at the periphery of the oasis changes from low to high with time,with the fragmentation of RSEI distribution within the oasis increasing.Its distribution and changes are predominantly driven by anthropologic factors,including the expansion of artificial oasis into the desert,the replacement of desert ecosystems by farmland ecosystems,and the increase in the distribution of impervious surfaces.The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability.The high efficiency exhibited with this approach makes it convenient for rapid,high frequency and macroscopic monitoring of eco-environmental quality in study area.
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.
文摘Landscape conversion becomes a continuous process in a natural landscape for any strategic development.In a forest landscape mosaic,the conversion from non-forest land to forest land implies a constructive approach.Various bio-geographic processes are enriched and developed when the land was converted to forest land in a given landscape matrix.The present study evaluated how the increased forest cover improves the ecological quality of forest in Jhargram District of West Bengal State,India,from 1985 to 2015.The quality of forests includes dominance,fragmentation and connectivity,which are the basis ecological indicators of habitat structure.To address this issue,we extracted forest cover maps of 1985 and 2015 from land use/land cover classification.A grid framework was overlaid on these forest cover maps for patch-matrix model analysis.Reliable landscape ecological indices were used for the measurements of forest landscape quality in 1985 and 2015.Then a simple linear regression model was used to compare the results.Temporally,forest cover increased in Jhargram District from 1985 to 2015.The comparison of measurement indices depicts that although only a small amount of land was changed into forest land in the study area,this small change has greatly improved the structural compositional quality of the forest land.Compared with 1985,the forest land area increased by about 6930.56 hm^(2) in 2015.This increased forest cover improved the basic landscape ecological characters,such as inter patch connectivity,forest core area,forest habitat dependence,forest habitat dominance and forest edge effect.As a result,the ecosystem function in Jhargram District has been improved,which again attracts wildlife and enriches biodiversity.
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 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.
文摘A Water Quality Index (WQI) is a simple numeric expression reflecting the quality of water in any ecosystem at a given time. The objective of this study was to develop a WQI for the man-made dam Francisco I. Madero located in Chihuahua, Mexico. Eight points were randomly selected in the dam area and at each point water samples were collected monthly from March 2011 to February 2012 at three depths;0.30 m, 5 m and 10 m. The following physical-chemical variables were measured: potential hydrogen (pH), electrical conductivity (EC), dissolved oxygen (DO), temperature (T), turbidity, total dissolved solids (TDS), total hardness (TH) and chlorides (Cl-). In a first step for data analysis, an analysis of variance (ANOVA) was performed for each variable considering a factorial treatment design 12 × 3 in which factor A was the month with 12 levels (sampling months) and factor B was the depth with three levels (0.30 m, 5 m and 10 m). In a second statistical step, the WQI was calculated for each month only for the surface sampling (0.30 m) and the resulting value was classified under three categories;2.5 as excellent water. The results showed the following ranges for single variables: pH of 7.63 - 10.65, EC of 190 - 320 μS·cm-1, DO of 1.30 - 12.1 mg·L-1, T of 11.30°C - 30°C, Turbidity of 0-1, 120 NTU, TDS of 170 - 220 mg·L-1, TH of 240 - 900 mg·L-1 and Cl- of 7.28 - 7034 mg·L-1. The calculated WQI demonstrated that water quality varies seasonally and was classified as poor in the rainy season to good in winter season. We conclude that in general the water from the dam is acceptable and suitable for ecological and a broad spectrum of other purposes.
