Spatiotemporal Evolution of Ecological Quality in Typical Karst Ecologically Fragile Areas Based on Remote Sensing Ecological Indexes

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.

Spatiotemporal variations in ecological quality of Otindag Sandy Land based on a new modified remote sensing ecological index

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.

Assessment on eco-environmental quality of the Yellow River Basin by considering desertification index

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.

Ecological environmental quality evaluation and driving factor analysis of the Lijiang River Basin,based on Google Earth Engine

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.

Spatial-temporal heterogeneity of ecological quality changes across the Qinghai-Tibet Plateau under the influence of climate factors and human activities

Over the last few decades,the ecological quality of the Qinghai–Tibet Plateau(QTP)has significantly changed due to climate warming,humidification,and increasing human activities.Thus,evaluating this region's ecological quality and dominant factors is crucial for sustainable development.In this study,the changes in the ecological quality on the QTP from 2000 to 2020 were evaluated based on aggregated indices and Sen–MK trend analyses,and the dominant factors affecting the ecological quality of the QTP were quantitatively analyzed using decision tree classification.The results revealed that(1)the ecological quality of the QTP exhibited an overall high trend in the east and a low pattern in the west;(2)the ecological quality of the QTP significantly increased from 2000 to 2020,and human activities were the dominant factors causing this change;and(3)the changes in the ecological quality and dominant factors exhibited obvious spatiotemporal heterogeneity.The area with an improved ecological quality occurred mainly in the northern QTP region.It was governed by human activities and precipitation.In contrast,the area with a deteriorated ecological quality occurred largely in the southern QTP region and was dominated by human activities and temperature.The 2000–2010 period was the most significant period of heterogeneity regarding of ecological quality and its driving factors.(4)The change in the ecological quality was mainly affected by the synergistic relationship between human activities and climate change in this region,which encompassed multiple dominant factors.This study provides important information on the spatiotemporal heterogeneity of ecological quality change and its dominant factors on the QTP and offers systematic guidance for the planning and implementation of ecological protection projects.

Spatiotemporal Evolution of Ecological Quality in Alpine Freshwater Lake Nature Reserves in the Past 20 Years

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.

Spatio-temporal Evolution and Optimization of Landscape Ecological Risk in Karst Mountainous Areas

[Objective]The ecological vulnerability and landscape ecological risk of karst mountainous areas have increased as a result of enhanced disturbance of natural resources by human activities.This paper aimed to explore the characteristics of ecological risk evolution under different landscape patterns in the region,with a view to providing reference for land classification protection,sustainable use of resources and regional ecological risk optimization in karst mountainous areas.[Method]Taking Huangping County,a typical karst mountainous area,as an example,eight evaluation factors of natural and landscape patterns were selected to construct a landscape ecological risk evaluation model,to quantitatively explore the spatio-temporal evolution of landscape ecological risk and the trend of risk level transfer in the study area from^(2)010-2018,and to reveal the complex relationship between ecological risk and topography in karst mountainous areas.[Result]①From 2010 to 2018,land use types changed to different degrees,with the most amount of woodland transferred out(1627.37 hm^(2))and the most amount of construction land transferred in(1303.93 hm^(2));a total of 3552.31 hm^(2) of land was transferred,with a change ratio of 2.13%,and there was a significant conversion between construction land,arable land,and woodland.②From 2010 to 2018,the landscape ecological risk in the study area changed significantly,and the landscape ecological risk index decreased from 0.3441 to 0.1733,showing an upward and then downward trend;the landscape ecological risk of the whole region was dominated by low-risk and lower-risk zones,and the ecological risk level generally shifted from a high level to a low level,and the ecological environment was improved.③There was a negative correlation between ecological risk and topographic position,and high-risk zones were mainly distributed among low topographic zones;with the change of time,the advantage of risk level for the selection of topography was gradually weakened,and the influence of anthropogenic factors on the ecological risk of the landscape was becoming more and more prominent.[Conclusion]This paper can provide theoretical basis for land use optimization and ecological protection in karst mountainous areas.

Study on Ecological Change Remote Sensing Monitoring Method Based on Elman Dynamic Recurrent Neural Network

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.

Ecological risk assessment of heavy metals in sediments of Xiawan Port based on modified potential ecological risk index

Modified potential ecological risk index （MRI） was proposed based on the potential ecological risk index （RI） and risk assessment code （RAC） by modifying an index. The modified index was relevant to the chemical speciation of heavy metals. Xiawan Port, a typical region contaminated by industrial production, was selected as a case study area. The total concentrations and chemical speciation of heavy metals in sediments of Xiawan Port were analyzed. The experimental data indicate that Xiawan Port is seriously polluted by heavy metals, especially by Cd. The risks of heavy metals are evaluated by RI, RAC and MRI, respectively. The resluts of MRI show that the risks of heavy metals are in the decreasing order of Cd〉Pb〉Cu〉Zn. Comparison of results by different methods reveals that MRI integrates the characters of RI and RAC. MRI is recognized to be useful for risk managemnt of heavy metals in sediments.

The Basic Indexes and Practices of Regional Ecological Agricultural Construction in Dabie Mountains——A Case Study of Huanggang,Hubei

Taking Huanggang city as an example, the requirements of basic indexes for the regional ecological agricultural construction in Dabie Mountains were ana- lyzed and the measures that must be taken in implementing the in the Dabie Mountains were proposed.

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

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.

Development of a large-scale remote sensing ecological index in arid areas and its application in the Aral Sea Basin

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.

Spatiotemporal changes of eco-environmental quality based on remote sensing-based ecological index in the Hotan Oasis,Xinjiang

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.

Environmental Monitoring in Northern Aksu, China Based on Remote Sensing Ecological Index Model

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.

On Index System and Quantitative Assessment of Eco-cities:A Case Study on Urban Agglomeration of the Yangtze Delta

Urban agglomeration of the Yangtze Delta （UAYD）, one of the most developed regions of China, has witnessed an increasing prevalence in building ecological cities when the ecological cities are pursued by many modem cities, and great achievements have been made in this regard. It is inevitable, however, that certain problems exist during the construction of ecological city, which include but not limited to non-harmonious development of urban complex ecosystem, and the difficulty in quantifying eco-city construction or incomplete quantification in assessing the construction of present and future eco-city. Based on the analysis on social-economic conditions and regional conditions of the UAYD, this paper attempts to set up an index system of eco-cities combining with local characteristics, and to adopt the indices of eco-city, urban harmony, and eco-city colligate to evaluate the ecological level, urban harmonious development and eco-city construction of cities within the UAYD. Results indicate that among 15 cities in UAYD, Suzhou City ranks the highest in terms of eco-city construction, whereas Nantong ranks relatively lower; sustainable eco-city construction is possible only when cities are developed in every respect of harmony.

Ecological evaluation of marine macroalgal communities on five islands of Korea in the Yellow Sea

Macroalgae have long been used as biological indicators of marine ecosystem health worldwide due to their ecological importance and sensitivity to environmental stress.A number of previous studies have utilized macroalgal communities in monitoring surveys of environmental conditions.This study examined the characteristics and patterns of marine macroalgal communities in the Yellow Sea off the western coast of Korea.Macroalgae were analyzed for the number of species,biomass,and coverage ratio by macroalgal type.During the study period,82 macroalgal species(10 green algae,17 brown algae,and 55 red algae)were identified at the five study sites,with the highest number of species found at Gwanrido and Uido(both containing 41 species)and the lowest at Daeijakdo(27 species).The average biomass(via dry weight)was 98.63 g/m^(2),consisting of green algae(8.39 g/m^(2)),brown algae(35.08 g/m^(2)),and red algae(55.16 g/m^(2)).The dominant macroalgae species in terms of biomass were Corallina pilulifera,Sargassum thunbergii,and Ulva australis in the intertidal zones,and Botryocladia wrightii and Gelidium elegans in the subtidal zones.Richness,evenness,and diversity indices based on the biomass of abundant species were 5.08,0.65,and 2.30,respectively,over the entire study area.Based on the evaluation of the environmental states by the community indices,overall,the Ecological Evaluation Index of macroalgae communities in the study area was marked as“Good-Moderate”,but was determined as“ModerateLow”at several sites during summer.The results can be a direct approach in the assessment of coastal habitats in which anthropogenic as well as climate change influences persist.

Environmental availability and ecological risk assessment of heavy metals in zinc leaching residue

Four different methods,namely mineralogical analysis,three-stage BCR sequential extraction procedure,dynamic leaching test and Hakanson Potential Ecological Risk Index Method were used to access the environmental activity and potential ecological risks of heavy metals in zinc leaching residue.The results demonstrate that the environmental activity of heavy metals declines in the following order：CdZnCuAsPb.Potential ecological risk indices for single heavy metal are CdZnCuAsPb.Cd has serious potential ecological risk to the ecological environment and contributes most to the potential toxicity response indices for various heavy metals in the residue.

A Modified Model of Ecological Footprint Accounting and Its Application to Cropland in Jiangsu,China

Based on the theory of emergy analysis,a modified model of ecological footprint accounting,termed emergetic ecological footprint(EMEF)in contrast to the conventional ecological footprint(EF)model,is formulated and applied to a case study of Jiangsu cropland,China.Comparisons between the EF and the EMEF with respect to grain,cotton,and food oil were outlined.Per capita EF and EMEF of cropland were also presented to depict the resources consumption level by comparing the biocapacity(BC)or emergetic biocapacity(EMBC,a new BC calculation by emergy analysis) of the same area.In the meanwhile,the ecological sustainability index(ESI),a new concept initiated by the authors, was established in the modified model to indicate and compare the sustainability of cropland use at different levels and between different regions.The results from conventional EF showed that per capita EF of the cropland has exceeded its per capita BC in Jiangsu since 1986.In contrast,based on the EMBC,the per capita EMEF exceeded the per capita EMBC 5 years earlier.The ESIs of Jiangsu cropland use were between 0.7 and 0.4 by the conventional method,while the numbers were between 0.7 and 0.3 by the modified one.The fact that the results of the two methods were similar showed that the modified model was reasonable and feasible,although some principles of the EF and EMEF were quite different. Also,according to the realities of Jiangsu cropland use,the results from the modified model were more acceptable.

Ecological Risk Assessment of World Heritage Sites Using RS and GIS:A Case Study of Huangshan Mountain, China

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.

Assessment of ecological quality in Northwest China(2000-2020)using the Google Earth Engine platform:Climate factors and land use/land cover contribute to ecological quality

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.