Study on the Spatial and Temporal Trends of Ecological Environment Quality and Influencing Factors in Xinjiang Oasis

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(11), P. 1980 - 1980

Published: May 31, 2024

Human activities and climate change have profound impacts on the ecological environment of oases in Xinjiang, it is great significance to explore spatial temporal evolution patterns quality this region for sustainable development Xinjiang. The remote sensing index (RSEI) was extracted from Google Earth Engine (GEE) platform 2000 2020, coefficient variation Hurst were used reveal characteristics stability artificial oasis natural key factors affecting are explored through correlation analysis geoprobes. results show that distribution Xinjiang high north low south, overall shows a fluctuating downward trend 0.210 0.189. Artificial higher RSEI values, stability, sustainability than oases. study area mainly influenced by humidity, followed greenness heat, dryness had least influence model. Based geodetector, top three highest contributors found be precipitation (PRE) (0.83) > relative humidity (RHU) (0.82) evapotranspiration (ET) (0.57). Climate main factor oases, can improved increasing proportion aims provide scientific basis arid zones.

Language: Английский

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Unraveling the Impacts of River Network Connectivity on Ecological Quality Dynamics at a Basin Scale

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(13), P. 2370 - 2370

Published: June 28, 2024

The ecological quality of river basins is significantly influenced by the complex network structures and their connectivity. This study measured temporal spatial variability quality, as reflected remote sensing indices (RSEI), examined responses to connectivity (RNC). In total, 8 RNC indices, including structure density (Dr), water surface ratio (Wr), edge-node (β), (γ), node importance betweenness centrality (BC), PageRank (PG_R), out_degree (Out_D), in_closeness (In_C), were generated at subbasin scale. Our results highlighted significance in influencing both values RSEI, extent this influence varied across different time periods. Specifically, three distinct clusters can be extracted from representing wet, near-normal, dry years. index γ patterns RSEIs, particularly wet years (R2 = 0.554), whereas β displayed a pronounced U-shape correlation with RSEIs 0.512). Although did not correlate directly RSEI levels, did, they positively affected (EI_SD_t). Higher PG_R, Out_D, In_C associated increased variability. Based on these correlations, we developed RNC-based EI_SD_t models high adjusted coefficients determination facilitate assessment ecosystem quality. provides essential insights into dynamics related within basin offers valuable guidance for effective watershed management conservation efforts aimed enhancing resilience sustainability.

Language: Английский

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Spatiotemporal simulation of sustainable development based on ecosystem services under climate change

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0316605 - e0316605

Published: Feb. 4, 2025

This study explores the spatiotemporal distribution characteristics of ecosystem services (ESs) in karst region southeastern Yunnan under backdrop climate change. The innovatively calculates sustainable development goals (SDG) index based on (ESs). It employs patch-generating land use simulation (PLUS) model to simulate future changes (LUCs) and uses integrated valuation tradeoffs (InVEST) assess ESs different scenarios. research systematically evaluates SDGs regions within context results indicate that: (1) Under all three scenarios 2035, trend LUCs area is highly consistent, though intensity spatial configuration vary significantly. least reduction arable occurs shared socioeconomic pathways (SSP) 126 scenario, while water bodies construction show varying degrees increase; (2) Regarding ESs, both yield soil retention exhibit an increasing across by with most notable rise SSP126. Conversely, habitat quality carbon storage a decline, smallest decrease also SSP126; (3) Analyzing SDG index, overall value low 2020. In scenarios, increases southern part decreasing eastern part, indicating significant differences regional potential. Hotspots SSP126 SSP245 are concentrated densely vegetated southwest edge areas, cold spots mainly found heavily human-impacted central urban agglomeration Wenshan City. for first time dynamics provides scientific evidence ecological protection planning.

Language: Английский

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Eco-environmental quality assessment of transition region between Qinling Mountains and Huanghuai Plain using Remote Sensing Ecological Index

Geocarto International, Journal Year: 2025, Volume and Issue: 40(1)

Published: Feb. 13, 2025

Language: Английский

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Urban ecosystem quality assessment based on the improved remote sensing ecological index

PeerJ, Journal Year: 2025, Volume and Issue: 13, P. e19297 - e19297

Published: April 29, 2025

The remote sensing ecological index (RSEI) is an important tool for assessing ecosystem quality. However, its land surface temperature (LST) component poses challenges due to complex calculations and mismatched spatial resolution with other indicators. This study proposed improved (DRSEI). By replacing the LST in RSEI difference (DI) (representing PM 2.5 concentration), new better reflects air pollution’s impact on results demonstrated that DRSEI outperformed quality Chongqing’s urban area. It exhibited three advantages: stronger correlation (EI), standard deviation values closer EI’s baseline, lower root mean square error. applicability of varied across different regions: proved be more suitable highly urbanized areas, whereas performed suburban regions. Further analysis revealed variability indicators influenced their loadings principal analysis, thereby affecting assessment results. emphasizes importance considering distribution when constructing indices. findings suggest could effectively assess areas. approach provides insights monitoring environmental management.

Language: Английский

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Spatial-temporal variation and influencing factors of ecological environment quality in Jilin Province (China)

Frontiers in Environmental Science, Journal Year: 2024, Volume and Issue: 12

Published: Sept. 13, 2024

Jilin Province is a crucial region of interest for agricultural and forestry development in China. The deterioration its ecological environment could have severe impact on production conservation. A systematic assessment quality essential sustainable development. In this study, we utilized Landsat data from 1990 to 2020 (every 5 years) construct the Remote Sensing Ecological Index (RSEI) Province. We applied Sen’s slope estimator Mann-Kendall trend test examine spatiotemporal changes over 30-year period. Additionally, employed Geo-detector explore socioeconomic natural factors influencing quality. results revealed: 1) From 2020, average RSEI index ranged 0.586 0.699, indicating overall good Spatially, gradually declined east west. 2) exhibited an initial increase, followed by decrease, then another increase trend. This improvement can be attributed implementation government policies, which reversed expansion saline-alkali land. significantly improved western 3) Socioeconomic both influence Among these factors, vegetation coverage has most significant study area, with exerting more than factors. Our research provide relevant support policy-making

Language: Английский

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Spatiotemporal Variation in Ecological Environmental Quality and Its Response to Different Factors in the Xia-Zhang-Quan Urban Agglomeration over the Past 30 Years

Land, Journal Year: 2024, Volume and Issue: 13(7), P. 1078 - 1078

Published: July 17, 2024

The interactions between economic development, environmental sustainability, population growth, and urbanization are vital in assessing the ecological dynamics of urban agglomerations. This study explores relationship within Xia-Zhang-Quan agglomeration Fujian Province from 1989 to 2022. Utilizing Landsat remote sensing images, we calculated Remote Sensing Ecological Index (RSEI) evaluate changes quality. results show that average RSEI values for 1989, 2000, 2010, 2022 were 0.5829, 0.5607, 0.5827, 0.6195, respectively, indicating an initial decline followed by a significant increase, culminating overall upward trend. spatial distribution classification shows area has largest proportion mainly “good” areas with “excellent” quality increased (13.41% 25.12% 2022), while those “general” decreased (28.03% 21.21% 2022). Over past three decades, Xiamen experienced substantial degradation (RSEI change −0.0897), Zhangzhou showed marked improvement 0.0519), Quanzhou exhibited slight deterioration −0.0396). Central typically had poorer conditions but signs improvement, whereas non-central regions demonstrated enhancement. factor detector analysis identified land use as dominant influencing quality, precipitation having relatively minor impact. Interaction revealed all other factors bi-variable enhancement or nonlinear enhancement, suggesting interactive effects these greater than individual alone. Land consistently solid explanatory power. Temperature also influence when interacting factors. Due planning can plan use, findings suggest effective harmonize development protection agglomeration.

Language: Английский

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Research on remote sensing ecological livability index based on Google Earth Engine: a case study from Urumqi-Changji-Shihezi urban cluster

PeerJ, Journal Year: 2024, Volume and Issue: 12, P. e17872 - e17872

Published: Aug. 30, 2024

The U-Chang-Shi (Urumqi-Changji-Shihezi) urban cluster, located at the heart of Xinjiang, boasts abundant natural resources. Over past two decades, rapid urbanization, industrialization, and climate change have significantly threatened region’s ecological livability. To comprehensively, scientifically, objectively assess livability this area, study leverages Google Earth Engine (GEE) platform multi-source remote sensing data to develop a comprehensive evaluation metric: Remote Sensing Ecological Livability Index (RSELI). This aims examine changes in cluster from 2000 2020. findings show that despite some annual improvements, overall trend is declining, indicating swift pace urbanization industrialization has placed considerable pressure on environment. Land use changes, driven by expansion growth agricultural industrial lands, progressively encroached upon existing green spaces water bodies, further deteriorating Additionally, topographical features influenced its livability; large terrain fluctuations made soil erosion geological disasters common. Despite central plains’ vast rivers providing ample resources, over exploitation ill-conceived hydrological constructions led escalating scarcity. area near Gurbantunggut Desert north, with extremely fragile environment, long been unsuitable for habitation. provides crucial scientific basis future development hopes offer theoretical support practical guidance sustainable improvement region.

Language: Английский

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Spatiotemporal changes and driving factors of ecological environmental quality in the Yongding-Luan River Basin based on RSEI

Frontiers in Environmental Science, Journal Year: 2024, Volume and Issue: 12

Published: Nov. 15, 2024

The ecological environmental quality (EEQ) of the Yongding-Luan River Basin (YLRB) is pivotal to security Beijing-Tianjin-Hebei (JJJ) region's core area. Evaluating EEQ and analyzing its changes are essential for regional management. However, long-term in YLRB remain uncovered. In this study, we constructed a seamless Remote Sensing Ecological Index (RSEI) from 1986 2022 using time-series Landsat imagery on Google Earth Engine (GEE) platform. Sen + Mann-Kendall method was employed analyze spatiotemporal trends EEQ, Geodetector used quantitatively assess driving factors their interactions. results show that: 1) mean RSEI increased 0.486 0.532 2022, marking 9.5% rise indicating fluctuating upward trend. 2) experienced three distinct phases: improvement, deterioration, re-improvement. Improvements were predominantly western YLRB, while deterioration mainly northern Xilinguole region southern urban expansion areas Beijing, Langfang, Tianjin, Tangshan. 3) factor detection indicates that land use type annual average precipitation primary change YLRB. Furthermore, interaction significant effect RSEI, with maximum 0.691. These findings align historical policies implemented by Chinese government. evolution identified study offer scientific basis decision-making

Language: Английский

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Spatio-Temporal Heterogeneity of Ecological Quality in a Typical Dryland of Northern China Driven by Climate Change and Human Activities

Plants, Journal Year: 2024, Volume and Issue: 13(23), P. 3341 - 3341

Published: Nov. 28, 2024

With the intensification of climate change and anthropogenic impacts, ecological environment in drylands faces serious challenges, underscoring necessity for regionally adapted quality evaluation. This study evaluates suitability original Remote Sensing Ecological Index (oRSEI), modified RSEI (mRSEI), (aRSEI) a typical dryland region northern China. Spatio-temporal changes from 2000 to 2022 were analyzed using Theil–Sen median trend analysis, Mann–Kendall test, Hurst exponent. Multiple regression residual analysis quantified relative contributions human activities changes. Results showed that (1) aRSEI was most suitable index area; (2) observed exhibited significant spatial heterogeneity, with improvements generally inner areas Yellow River declines outer areas; (3) primarily driven by activities, dominating 2011 influence increasing 2012 2022. compares efficacy RSEIs evaluating quality, identifies spatio-temporal patterns, elucidates driving mechanisms, offering scientific evidence policy recommendations targeted conservation restoration measures address future regions.

Language: Английский

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