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
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 the ETM remote sensing images of Guangzhou City in 2014, the spatial distribution results o f three environmental factors including vegetation coverage(NDVI), soil index(vegetation index of bare soil) and sl ...Based on the ETM remote sensing images of Guangzhou City in 2014, the spatial distribution results o f three environmental factors including vegetation coverage(NDVI), soil index(vegetation index of bare soil) and sl ope were obtained. By using comprehensive index method, the normalized environmental factors were weighted and superimposed, and the fi nal evaluation results of ecological environment in Guangzhou City were obtained. The results showed that overall situation of natural ecological environment in Guangzhou was not optimistic, that is, the area of land with bad, moderate, good and superior environment accounted for 59.70%, 35.79%, 4.50% and around 0.01% of total area of land in Guangzhou City respectively. Ecological environment was generally poor in the central urban districts in the south of Guangzhou City, while it was relatively better in the north and northeast. Attaching importance to the constr uction of greenbelts and greenways is an effective way to improve regional environmental quality and natural ecological e nvironment level.展开更多
Remote sensing provides us with an approach for the rapid identification and monitoring of spatiotemporal changes in the urban ecological environment at different scales.This study aimed to construct a remote sensing ...Remote sensing provides us with an approach for the rapid identification and monitoring of spatiotemporal changes in the urban ecological environment at different scales.This study aimed to construct a remote sensing assessment index for urban ecological livability with continuous fine spatiotemporal resolution data from Landsat and MODIS to overcome the dilemma of single image-based,single-factor analysis,due to the limitations of atmospheric conditions or the revisit period of satellite platforms.The proposed Ecological Livability Index(ELI)covers five primary ecological indicators-greenness,temperature,dryness,waterwetness,and atmospheric turbidity-which are geometrically aggregated by non-equal weights based on an entropy method.Considering multisource time-series data of each indicator,the ELl can quickly and comprehensively reflect the characteristics of the Ecological Livability Quality(ELQ)and is also comparable at different time scales.Based on the proposed ELl,the urban ecological livability in the central urban area of Wuhan,China,from 2002 to 2017,in the different seasons was analyzed every 5 years.The ELQ of Wuhan was found to be generally at the medium level(ELl=0.6)and showed an initial trend of degradation but then improved.Moreover,the ecological livability in spring and autumn and near rivers and lakes was found to be better,whereas urban expansion has led to the outward ecological degradation of Wuhan,but urban afforestation has enhanced the environment.In general,this paper demonstrates that the ELI has an exemplary embodiment in urban ecological research,which will support urban ecological protection planning and construction.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
Based on a total of 519 images,the composite images with the lowest possible cloud cover were generated at pixel level with image synthesis method on Google Earth Engine(GEE)platform.The Remote Sensing Ecological Inde...Based on a total of 519 images,the composite images with the lowest possible cloud cover were generated at pixel level with image synthesis method on Google Earth Engine(GEE)platform.The Remote Sensing Ecological Index(RSEI)was adopted,and calculated in an efficient way with the assistance of parallel cloud computing of the GEE platform.The RSEI was used in this paper to evaluate and monitor the eco-environmental quality of the Lhasa Metropolitan Area.Results show that:(1)The ecological quality is better in the west than in the east of Lhasa Metropolitan Area,with Lhasa as an approximate dividing point.The ecological quality improved and then deteriorated dramatically before 2000,with the mean RSEI value dropping from 0.51 to 0.46;the trend was followed by a gradual increase up until 2017,with the mean RSEI value increased from 0.46 to 0.55.(2)The RSEI is weakly and positively correlated with socioeconomic indicators.This indicates that the population growth and economic development did not negatively influence the ecological quality,but actually boosted it.(3)The GEE can serve as an efficient computing platform for the assessment and monitoring of eco-environmental quality in vast regions.展开更多
The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric ...The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information.In this study,the abandoned mining area in the Helan Mountains,China was taken as the study area.Based on hyperspectral remote sensing images of Zhuhai No.1 hyperspectral satellite,we used the pixel dichotomy model,which was constructed using the normalized difference vegetation index(NDVI),to estimate the vegetation coverage of the study area,and evaluated the vegetation growth status by five vegetation indices(NDVI,ratio vegetation index(RVI),photochemical vegetation index(PVI),red-green ratio index(RGI),and anthocyanin reflectance index 1(ARI1)).According to the results,the reclaimed vegetation growth status in the study area can be divided into four levels(unhealthy,low healthy,healthy,and very healthy).The overall vegetation growth status in the study area was generally at low healthy level,indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes.Furthermore,the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated,indicating that the original mining activities have had a large effect on vegetation ecology.After ecological restoration of abandoned mines,the vegetation coverage in the study area has increased to a certain extent,but the amplitude was not large.The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part,due to abandoned mines mainly concentrating in the northern part of the Helan Mountains.The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation,accurately analyze the plant growth status,and provide technical support for vegetation health evaluation.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
Mapping ecological states in semi-arid rangelands is crucial for effective land management and conservation efforts because it identifies difference in the ecological conditions across a landscape. This study presents...Mapping ecological states in semi-arid rangelands is crucial for effective land management and conservation efforts because it identifies difference in the ecological conditions across a landscape. This study presents an innovative approach for mapping two ecological states, Large Shrub Grass (LSG) and Large Shrub Eroded (LSE), within the Sandy Loam Upland and Deep (SLUD) ecological sites using a combination of drone and satellite data. The methodology leverages the Largest Patch Index (LPI) as a proxy metric to estimate eroded areas and classify ecological states. The integration of unmanned aerial vehicle (UAV) data with satellite-based remote sensing provides a scalable approach that can benefit various stakeholders involved in rangeland management. The study demonstrates the potential of this methodology by generating spatial layers at the landscape scale to inform on the state of rangeland ecosystems. The workflow showcases the power of remote sensing technology to map ecological states and addresses limitations in spatial coverage by integrating UAV and satellite data. By utilizing the bare ground LPI metric, which indicates the connectedness of bare ground, the methodology enables the classification of ecological states at a regional scale. This cost-effective approach potentially offers a standardized and reproducible method applicable across different sites and regions. The accuracy of the classification process is evaluated by comparing the results to ground-based polygons, dirt roads, and water locations. While the model performs well in identifying eroded areas, misclassifications occur in regions with mixed vegetation cover or low biomass. Future research should focus on incorporating temporal information from historical remote sensing archives to improve understanding of ecological state dynamics. Additionally, validation efforts can be enhanced by incorporating more ground-truth data and testing the methodology in diverse rangeland areas. The workflow serves as a blueprint for scaling up ecological states mapping in similar semi-arid rangelands. Further work should involve refining the approach through additional validation and exploring new remote sensing datasets. The methodology can be replicated in other regions to inform land management decisions, promote sustainable resource use, and advance the field of ecological states mapping.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
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
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
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
Ecological risk assessment(ERA) is an indispensable method for systematic monitoring of World Heritage Sites(WHSs) exposed to various anthropogenic factors and natural disasters. Remote sensing(RS) and geographical in...Ecological risk assessment(ERA) is an indispensable method for systematic monitoring of World Heritage Sites(WHSs) exposed to various anthropogenic factors and natural disasters. Remote sensing(RS) and geographical information systems(GIS) can eliminate many limitations in traditional ERA methods. In this study, changes in ecological risk at Huangshan Mountain, the first mixed WHS in China, over the period of 1984–2019 were explored using remote sensing images and products by considering both natural disasters and human disturbance. Results show that of the four land cover types in Huangshan Mountain, namely water, forest, building and farmland, the main land cover type is forest. During the 35 yr, lands categorised at low or relatively low ecological risk levels are dominant in Huangshan Mountain, with the lowest and highest ERIs(ecological risk index) in 1990 and 2010, respectively. The areas at the five ecological risk levels have declined as follows: relatively low > low > medium > relatively high > high. Changes in ecological risks are closely related to changes in land cover and natural disasters. Even though major natural disasters may affect the ecological risk level in the whole region, changes in land cover caused by human activities will shift the ecological risk level in some areas. Our attempts can be modified and applied to other sites, and offer policy implications for protection and preservation of WHSs.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
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Sponsored by National Natural Science Foundation of China(41271060)
文摘Based on the ETM remote sensing images of Guangzhou City in 2014, the spatial distribution results o f three environmental factors including vegetation coverage(NDVI), soil index(vegetation index of bare soil) and sl ope were obtained. By using comprehensive index method, the normalized environmental factors were weighted and superimposed, and the fi nal evaluation results of ecological environment in Guangzhou City were obtained. The results showed that overall situation of natural ecological environment in Guangzhou was not optimistic, that is, the area of land with bad, moderate, good and superior environment accounted for 59.70%, 35.79%, 4.50% and around 0.01% of total area of land in Guangzhou City respectively. Ecological environment was generally poor in the central urban districts in the south of Guangzhou City, while it was relatively better in the north and northeast. Attaching importance to the constr uction of greenbelts and greenways is an effective way to improve regional environmental quality and natural ecological e nvironment level.
基金supported by the National Natural Science Foundation of China[grant number 41701394]National Key Research and Development Program of China[grant number 2018YFB2100500].
文摘Remote sensing provides us with an approach for the rapid identification and monitoring of spatiotemporal changes in the urban ecological environment at different scales.This study aimed to construct a remote sensing assessment index for urban ecological livability with continuous fine spatiotemporal resolution data from Landsat and MODIS to overcome the dilemma of single image-based,single-factor analysis,due to the limitations of atmospheric conditions or the revisit period of satellite platforms.The proposed Ecological Livability Index(ELI)covers five primary ecological indicators-greenness,temperature,dryness,waterwetness,and atmospheric turbidity-which are geometrically aggregated by non-equal weights based on an entropy method.Considering multisource time-series data of each indicator,the ELl can quickly and comprehensively reflect the characteristics of the Ecological Livability Quality(ELQ)and is also comparable at different time scales.Based on the proposed ELl,the urban ecological livability in the central urban area of Wuhan,China,from 2002 to 2017,in the different seasons was analyzed every 5 years.The ELQ of Wuhan was found to be generally at the medium level(ELl=0.6)and showed an initial trend of degradation but then improved.Moreover,the ecological livability in spring and autumn and near rivers and lakes was found to be better,whereas urban expansion has led to the outward ecological degradation of Wuhan,but urban afforestation has enhanced the environment.In general,this paper demonstrates that the ELI has an exemplary embodiment in urban ecological research,which will support urban ecological protection planning and construction.
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.
基金Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401)。
文摘Based on a total of 519 images,the composite images with the lowest possible cloud cover were generated at pixel level with image synthesis method on Google Earth Engine(GEE)platform.The Remote Sensing Ecological Index(RSEI)was adopted,and calculated in an efficient way with the assistance of parallel cloud computing of the GEE platform.The RSEI was used in this paper to evaluate and monitor the eco-environmental quality of the Lhasa Metropolitan Area.Results show that:(1)The ecological quality is better in the west than in the east of Lhasa Metropolitan Area,with Lhasa as an approximate dividing point.The ecological quality improved and then deteriorated dramatically before 2000,with the mean RSEI value dropping from 0.51 to 0.46;the trend was followed by a gradual increase up until 2017,with the mean RSEI value increased from 0.46 to 0.55.(2)The RSEI is weakly and positively correlated with socioeconomic indicators.This indicates that the population growth and economic development did not negatively influence the ecological quality,but actually boosted it.(3)The GEE can serve as an efficient computing platform for the assessment and monitoring of eco-environmental quality in vast regions.
基金This research was supported by the Ningxia Hui Autonomous Region Key Research and Development Plan(2022BEG03052).
文摘The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information.In this study,the abandoned mining area in the Helan Mountains,China was taken as the study area.Based on hyperspectral remote sensing images of Zhuhai No.1 hyperspectral satellite,we used the pixel dichotomy model,which was constructed using the normalized difference vegetation index(NDVI),to estimate the vegetation coverage of the study area,and evaluated the vegetation growth status by five vegetation indices(NDVI,ratio vegetation index(RVI),photochemical vegetation index(PVI),red-green ratio index(RGI),and anthocyanin reflectance index 1(ARI1)).According to the results,the reclaimed vegetation growth status in the study area can be divided into four levels(unhealthy,low healthy,healthy,and very healthy).The overall vegetation growth status in the study area was generally at low healthy level,indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes.Furthermore,the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated,indicating that the original mining activities have had a large effect on vegetation ecology.After ecological restoration of abandoned mines,the vegetation coverage in the study area has increased to a certain extent,but the amplitude was not large.The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part,due to abandoned mines mainly concentrating in the northern part of the Helan Mountains.The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation,accurately analyze the plant growth status,and provide technical support for vegetation health evaluation.
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.
文摘Mapping ecological states in semi-arid rangelands is crucial for effective land management and conservation efforts because it identifies difference in the ecological conditions across a landscape. This study presents an innovative approach for mapping two ecological states, Large Shrub Grass (LSG) and Large Shrub Eroded (LSE), within the Sandy Loam Upland and Deep (SLUD) ecological sites using a combination of drone and satellite data. The methodology leverages the Largest Patch Index (LPI) as a proxy metric to estimate eroded areas and classify ecological states. The integration of unmanned aerial vehicle (UAV) data with satellite-based remote sensing provides a scalable approach that can benefit various stakeholders involved in rangeland management. The study demonstrates the potential of this methodology by generating spatial layers at the landscape scale to inform on the state of rangeland ecosystems. The workflow showcases the power of remote sensing technology to map ecological states and addresses limitations in spatial coverage by integrating UAV and satellite data. By utilizing the bare ground LPI metric, which indicates the connectedness of bare ground, the methodology enables the classification of ecological states at a regional scale. This cost-effective approach potentially offers a standardized and reproducible method applicable across different sites and regions. The accuracy of the classification process is evaluated by comparing the results to ground-based polygons, dirt roads, and water locations. While the model performs well in identifying eroded areas, misclassifications occur in regions with mixed vegetation cover or low biomass. Future research should focus on incorporating temporal information from historical remote sensing archives to improve understanding of ecological state dynamics. Additionally, validation efforts can be enhanced by incorporating more ground-truth data and testing the methodology in diverse rangeland areas. The workflow serves as a blueprint for scaling up ecological states mapping in similar semi-arid rangelands. Further work should involve refining the approach through additional validation and exploring new remote sensing datasets. The methodology can be replicated in other regions to inform land management decisions, promote sustainable resource use, and advance the field of ecological states mapping.
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 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Under the auspices of the National Key Research and Development Program of China (No. 2020YFC1521903)National Key Research and Development Program of China (No. 2018YFD1100104)。
文摘Ecological risk assessment(ERA) is an indispensable method for systematic monitoring of World Heritage Sites(WHSs) exposed to various anthropogenic factors and natural disasters. Remote sensing(RS) and geographical information systems(GIS) can eliminate many limitations in traditional ERA methods. In this study, changes in ecological risk at Huangshan Mountain, the first mixed WHS in China, over the period of 1984–2019 were explored using remote sensing images and products by considering both natural disasters and human disturbance. Results show that of the four land cover types in Huangshan Mountain, namely water, forest, building and farmland, the main land cover type is forest. During the 35 yr, lands categorised at low or relatively low ecological risk levels are dominant in Huangshan Mountain, with the lowest and highest ERIs(ecological risk index) in 1990 and 2010, respectively. The areas at the five ecological risk levels have declined as follows: relatively low > low > medium > relatively high > high. Changes in ecological risks are closely related to changes in land cover and natural disasters. Even though major natural disasters may affect the ecological risk level in the whole region, changes in land cover caused by human activities will shift the ecological risk level in some areas. Our attempts can be modified and applied to other sites, and offer policy implications for protection and preservation of WHSs.
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.
