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Characteristics and driving factors of population age structure in China:A study based on the scale nesting theory 认领 引用
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作者 YING Kui HA Lin +1 位作者 DUAN Liancheng DING Jinhong 《Journal of Geographical Sciences》 SCIE CSCD 2026年第5期1278-1298,共21页
China's population age structure(PAS)has already entered a modern phase,with the effects of aging and declining birth rates becoming increasingly severe.These trends pose significant challenges to demographic and ... China's population age structure(PAS)has already entered a modern phase,with the effects of aging and declining birth rates becoming increasingly severe.These trends pose significant challenges to demographic and socioeconomic stability.In this study,the scale nesting theory was used to analyze the population census data for 2000-2020 from prefecture-level cities.Using a multiscale geographically weighted regression model,this study explores the spatial characteristics of China's age structure and quantitatively examines the driving factors within this nested framework.The evolution of PAS in the prefecture-level cities in China exhibited distinct stages,while depicting a rapid transition toward an aging model.In the nested space,single-scale nesting was primarily synchronous,while double-scale nesting was characterized by simultaneous synchronization.The Northeast region exhibited the highest degree of synchronous development in the PAS within the nested space.The regression coefficients indicated that the population system and per capita gross domestic product(GDP)were the primary and secondary factors,respectively.Topographical variation exerted an influence on only the synchronous-advance type,while PM2.5exhibited a significant association with the advance-lag type.This study provides scientific support for high-quality development across regions in the context of heterogeneous population age structures. 展开更多
关键词 age structure spatio-temporal characteristics scale nesting driving factors
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Dynamic patterns and driving factors of productive cropland in Ukraine before and after Russia-Ukraine conflict 认领 引用
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作者 Yiliang Li Kaixuan Yao +5 位作者 Qingxiang Meng Yujie Wang Rui Xiao Yuhang Liu Sensen Wu Yansheng Li 《Geography and Sustainability》 CSCD 2026年第1期106-118,共13页
Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in... Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in Ukraine,particularly in the context of the 2022 Russia-Ukraine conflict.We provide the first comprehensive assessment of both conflict-and non-conflict-related factors that influenced the distribution and productivity of Ukraine’s cropland from 2013 to 2023.In addition,we propose a novel method using machine learning models to isolate the impact of conflict on cropland.Our findings reveal that,prior to the conflict,the spatial pattern of Ukraine’s mean cultivation rate was primarily shaped by natural factors—such as climate,soil properties,and elevation—whereas socio-economic factors(e.g.,GDP and population size)exerted a weaker influence.Interannual dynamics in productive cropland area were largely driven by climate variability.The onset of conflict in 2022 dramatically altered this landscape,with nearly half of the cropland grid cells experiencing a conflict-induced reduction.Notably,almost half of the interannual reduction in productive cropland in 2022 was attributed to climate change.Remarkably,in 2023,the return of displaced populations and favorable climatic conditions in many oblasts contributed to a positive trend in cropland reclamation.Despite this,the total area of productive cropland in 2023 remained below expected levels,due to ongoing conflict and localized droughts.Finally,we highlight the urgent need to adopt a two-pronged approach that addresses both the immediate impacts of conflict and the ongoing threats posed by climate change to ensure the resilience and sustainability of agricultural systems in post-conflict areas. 展开更多
关键词 Ukraine’s cropland dynamics Driving factors analysis Time-series remote sensing Russia-Ukraine conflict
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Spatio-temporal variation and driving factors of wind and water compound erosion in the black soil region of northeastern China 认领 引用
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作者 SUN Liying WANG Chunhui 《Journal of Geographical Sciences》 SCIE CSCD 2026年第4期849-875,共27页
Wind and water compound erosion(WWCE)has aggregated the hazards of soil erosion on cropland in the black soil region of northeastern China.The present study employed novel methodology to characterize the spatio-tempor... Wind and water compound erosion(WWCE)has aggregated the hazards of soil erosion on cropland in the black soil region of northeastern China.The present study employed novel methodology to characterize the spatio-temporal variations in WWCE at the regional scale,using a classification scheme consisting of four levels and three types based on the Revised Universal Soil Loss Equation(RUSLE)and the Revised Wind Erosion Equation(RWEQ).The results showed that between 2001 and 2020,wind-dominated compound erosion(WIDCE)was the dominant type of WWCE,with the relative area decreasing from 73.3%to 55.5%.The significant(p<0.05)driving factors of spatial variation in WWCE included wind speed,precipitation,air temperature,slope gradient,and elevation in 2001,while the anthropogenic factor of land use/land cover was included since 2010.The total area of WWCE and WIDCE decreased initially and then increased from 2001 to 2020,while water-dominated compound erosion(WDCE)and wind-water equivalent compound erosion(WWECE)showed increasing trends during this period.The Moderate and Intensive degree areas of WIDCE,WDCE,and WWECE showed dramatic increases from 2001 to 2020.The implications are discussed,and hotspots are identified for the improvement of future soil and water conservation measures in the black soil region of northeastern China. 展开更多
关键词 soil and water conservation wind and water compound erosion black soil region driving factors hotspots area
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Landslide susceptibility on the Qinghai-Tibet Plateau:Key driving factors identified through machine learning 认领 引用 被引量：1
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作者 YANG Wanqing GE Quansheng +3 位作者 TAO Zexing XU Duanyang WANG Yuan HAO Zhixin 《Journal of Geographical Sciences》 SCIE CSCD 2026年第1期199-218,共20页
Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility ar... Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning. 展开更多
关键词 landslide susceptibility machine learning SHAP driving factors nonlinear effects
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Assessing the spatiotemporal patterns and driving factors of water erosion in the Ganges-Brahmaputra-Meghna River Basin based on RUSLE-Geodetector 认领 引用
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作者 WANG Zijun LI Jiacong +5 位作者 GUAN Yinghui XU Ximeng YAO Haoyi MAI Xirong XIANG Jiayi XING Jiacheng 《Journal of Mountain Science》 SCIE CSCD 2026年第7期3139-3154,共16页
The Ganges-Brahmaputra-Meghna(GBM)river basin,a critical transboundary river basin in South Asia,is increasingly affected by soil erosion.However,its spatiotemporal dynamics and underlying drivers remain poorly quanti... The Ganges-Brahmaputra-Meghna(GBM)river basin,a critical transboundary river basin in South Asia,is increasingly affected by soil erosion.However,its spatiotemporal dynamics and underlying drivers remain poorly quantified.This study comprehensively evaluates soil erosion intensity and its driving factors during 2000-2022 by the Revised Universal Soil Loss Equation(RUSLE)with Geodetector.The main findings are as follows:(1)The mean soil erosion intensity across the GBM basin is1087.78 t·km-2·a-1,with 68.76% of the basin experiencing mild erosion(<500 t·km-2·a-1).Spatially,erosion intensity is highest in the Southern Foothills of the Tibetan Plateau Area(SFA)(3099.84 t·km-2·a-1)and is lowest in the Flood Plain Area(174.10 t·km-2·a-1).(2)At the basin scale,no significant trend is observed in the GBM basin.In contrast,the SFA subregion shows a significant increasing trend of 34.38 t·km-2·a-2(P=0.05).Projections indicate that 67.57% of the basin is likely to experience worsening erosion in the future.(3)Topography and NDVI dominates the soil erosion patterns in most of the region.However,in the eastern hilly area,the primary drivers are topography and precipitation,with a high Q value of 0.841.Notably,topography influence has weakened over time,while the influence of human activities has strengthened,highlighting the need for targeted management of land use and conservation practices to reduce soil and ecosystem degradation.These results can provide valuable insights for mitigating water erosion and optimizing conservation strategies within the GBM river basin. 展开更多
关键词 Water erosion GBM river basin Spatiotemporal variations Driving factors RUSLE
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Post-disaster recovery assessment and driving factors of the 2013 Lushan Earthquake affected area based on multi-temporal nighttime light data 认领 引用
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作者 ZHU Xiaolin WEI Benyong +5 位作者 SU Guiwu QI Wenhua GAO Yuan ZHANG Tengfei GUO Xinxin WANG Xu 《Journal of Mountain Science》 SCIE CSCD 2026年第4期1367-1383,共17页
Although severe earthquakes continue to challenge the resilience of local communities,finescale knowledge of post-earthquake recovery remains scarce.Nighttime light data facilitate the continuous monitoring and assess... Although severe earthquakes continue to challenge the resilience of local communities,finescale knowledge of post-earthquake recovery remains scarce.Nighttime light data facilitate the continuous monitoring and assessment of post-earthquake impacts and recovery through multi-temporal scales,thereby providing crucial scientific support for disaster management and the formulation of mitigation strategies.In this study,we applied spatiotemporal analysis to evaluate the post-disaster recovery process in the 2013 Lushan Earthquake affected area.We further explored the driving factors of the nighttime light changes after the earthquake and examined the natural and social characteristics underlying the postdisaster recovery process.The relationship between nighttime-light changes and the post-disaster recovery process varied across different temporal scales.Interday nighttime lighting provided a near-real-time reflection of earthquake disaster impacts.Intermonthly changes primarily reflected mid-term recovery progress,revealing two distinct recovery patterns:urban and rural.Interannual changes provided a macro-level overview of recovery across disaster zones,identifying three distinct recovery patterns:non-hit townships,hit townships,and main urban areas.The trend in light intensity over disasteraffected areas showed significant consistency with changes in the regional gross domestic product(GDP).Based on Pearson’s correlation analysis,the correlation coefficient between the two at the county level reached 0.857,indicating that nighttime light data can accurately reflect the spatial dynamics of economic activity.Natural factors including elevation and social factors,such as the distribution of construction land,had a significant impact on light variations.Furthermore,we established a multitimescale post-earthquake recovery analysis framework,which clarifies the correspondence between night-time lights and recovery processes across different scales.It also provides a quantitative representation of socioeconomic recovery and distinguishes the roles of key influencing factors.This study provides methodological foundations and empirical references for precise post-disaster assessments and optimized recovery strategies. 展开更多
关键词 Earthquake Post-disaster recovery Multi-temporal NPP-VIIRS night-time lights Driving factors
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Spatiotemporal variation and driving factors of vegetation coverage in Xigaze section of Yarlung Zangbo River 认领 引用
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作者 WANG Siqi ZHANG Zhengcai +5 位作者 SHEN Caisheng HAN Lanying JIANCAN Zhaxi LA Zhen ZHANG Lingguang ZHANG Zhenyu 《Journal of Mountain Science》 SCIE CSCD 2026年第4期1423-1438,共16页
Vegetation coverage regulates carbon cycling,conserves soil and water,and stabilizes ecosystems.The Xigaze section of the Yarlung Zangbo River(YZR)basin is a critical riparian zone affecting suspended sediment supply,... Vegetation coverage regulates carbon cycling,conserves soil and water,and stabilizes ecosystems.The Xigaze section of the Yarlung Zangbo River(YZR)basin is a critical riparian zone affecting suspended sediment supply,channel migration,and sandstorm intensity.However,studies on its spatiotemporal dynamics and driving factors remain limited,largely due to reliance on low-resolution data.In this study,fractional vegetation cover(FVC)within a 5 km riparian buffer was reconstructed using Landsat8 imagery(2015-2024)and Sentinel 2 imagery(2019-2024)based on the pixel dichotomy model.Trends were quantified with Theil-Sen slope statistics and the Mann-Kendall test.Land use and cover change(LUCC)was mapped by random forest classifier,and meteorological data from 14 stations were used to evaluate climatic drivers.The results reveal a general FVC decline,with a shift during 2019-2020.LUCC(q=0.704)was the dominant driver of vegetation variation,followed by temperature(q=0.061).Elevation and slopes influence vegetation mainly through interactions with other variables.In the Rizi section,sparse vegetation and intense aeolian activity suggest an urgent need for wind-erosion control.In Lhaze and Xigaze,mixed forest-grass systems are recommended to improve resilience.Additionally,ongoing monitoring of the risk of riverbank collapse under hydrological-aeolian processes is also warranted. 展开更多
关键词 Fractional vegetation cover Driving factors GeoDetector Yarlung Zangbo River Land use and cover change
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Spatiotemporal dynamics and driving factors of carbon sinks across ecosystems in Northwest China 认领 引用
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作者 CHEN Xueye SHI Ying +1 位作者 BIE Qiang Mujib ADEAGBO 《Journal of Arid Land》 SCIE CAS CSCD 2026年第5期735-751,共17页
Net ecosystem productivity(NEP)is a key indicator for estimating carbon sink dynamics in terrestrial ecosystems.Existing studies on carbon sink dynamics in Northwest China have uncertainties in quantifying spatiotempo... Net ecosystem productivity(NEP)is a key indicator for estimating carbon sink dynamics in terrestrial ecosystems.Existing studies on carbon sink dynamics in Northwest China have uncertainties in quantifying spatiotemporal variations of NEP and their driving factors.This study estimated NEP across ecosystems in Northwest China during 2000–2020 using multi-model integration,and analyzed its spatiotemporal patterns and drivers.Results showed that the annual average NEP was 97.98 g C/(m2·a),with higher values at eastern and western margins and lower values in central hinterland.Strong carbon sink areas included the Yili River Basin and northern slope of Tianshan Mountains,while low carbon sink areas concentrated in eastern Xinjiang Uygur Autonomous Region(Eastern Xinjiang)and Alxa-Ejin Plateau.NEP trended upward from 79.22 g C/(m2·a)in 2000 to 109.03 g C/(m2·a)in 2020 with low variability and strong persistence,suggesting continuous growth.NEP significantly and positively correlated with near-infrared reflectance of vegetation(NIRv),weakly with climate factors,and negatively with socio-economic density indicators.Topographically,NEP peaked at 2.0–2.4 km elevation,15°-25°slopes,and north-facing aspects.Changes in ecosystem type significantly influenced NEP,with bare land conversion into grassland/cropland enhancing carbon sinks.Results of this study highlight the need for ecological restoration and rational land use to boost carbon sequestration in this ecologically sensitive region. 展开更多
关键词 near-infrared reflectance of vegetation net ecosystem productivity carbon sink driving factors Northwest China
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Spatiotemporal variation of fraction vegetation coverage and its driving factors in the Taihang mountainous area,China 认领 引用
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作者 QIAO Dingding ZHENG Peijin +3 位作者 SUN Piling LIU Kun LI Nan LIU Qingguo 《Journal of Mountain Science》 SCIE CSCD 2026年第7期3090-3103,共14页
This study investigates the spatiotemporal dynamics and driving factors of Fractional Vegetation Coverage(FVC)in the Taihang mountainous area from 2000 to 2022,using the Mann-Kendall test,Theil-Sen median analysis,coe... This study investigates the spatiotemporal dynamics and driving factors of Fractional Vegetation Coverage(FVC)in the Taihang mountainous area from 2000 to 2022,using the Mann-Kendall test,Theil-Sen median analysis,coefficient of variation(Cv),and the Optimal Parameter Geographic Detector(OPGD).FVC plays a critical role in mountain ecosystems by enhancing soil moisture retention,reducing erosion risk,stabilizing slopes,and indicating vegetation vitality and resilience in environmentally sensitive regions.As an essential ecological safety barrier for the North China Plain,understanding FVC variations in the Taihang Mountains is imperative for environmental protection and sustainable development in ecologically fragile mountainous areas.Results reveal a transition from low-grade to highgrade FVC,with an average annual increase of 0.004 and notable fluctuations.Improved areas accounted for 92.37%of the total,while degraded areas comprised only 6.26%.Spatially,FVC exhibits significant heterogeneity,with low coverage in the north and high coverage in the south.The coefficient of variation indicates generally low volatility,with lower Cv values in the south and east and higher values in the north and west.Mean annual temperature(Mat),mean annual precipitation(Map),and aspect(Asp)are identified as the primary driving factors.Interaction analyses demonstrate an enhancement effect,with combinations of natural environmental and socioeconomic factors exerting particularly significant impacts. 展开更多
关键词 Fraction vegetation coverage(FVC) Spatiotemporal variation Driving factors Optimal parameter geographic detector(OPGD) Taihang mountainous area
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Mechanism of Multi-Source Excitation for Whistling Sound of Gear Teeth in Automotive Electric Drive System 认领 引用
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作者 Shuai Yuan Zhen Lin Wenfu Sun 《Journal of Electronic Research and Application》 2025年第4期65-70,共6页
This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimiz... This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers. 展开更多
关键词 Automotive electric drive system Whistle of gear teeth Multi-source excitation mechanism
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Long-term spatiotemporal variations of ammonia in the Yangtze River Delta region of China and its driving factors 认领 引用 被引量：1
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作者 Jingkai Xue Chengzhi Xing +6 位作者 Qihua Li Shanshan Wang Qihou Hu Yizhi Zhu Ting Liu Chengxin Zhang Cheng Liu 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2025年第4期202-217,共16页
This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data fr... This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH3VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH3concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH3VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH3VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH3VCDs.The rise in NH3VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO2,as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH3VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD. 展开更多
关键词 Yangtze River Delta Ammonia Spatiotemporal distribution Driving factors
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Coupling Coordination Development and Driving Factors of New Energy Vehicles and Ecological Environment in China 认领 引用 被引量：5
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作者 XU Zonghuang 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2025年第1期79-90,共12页
Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoti... Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China. 展开更多
关键词 new energy vehicles(NEVs) ecological environment coupling coordination development machine learning driving factors
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Investigation into the Evolution Characteristics and Driving Factors of Seagrass Beds in Sanggou Bay(1985-2022) 认领 引用
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作者 LI Meina CHEN Bin +5 位作者 LI Haibo ZOU Liang CAO Ke YUE Baojing HU Rui LI Xue 《Journal of Ocean University of China》 SCIE CAS CSCD 2025年第5期1195-1205,共11页
Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and... Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and water eutrophication,making them some of the most endangered ecosystems worldwide.In the Yellow Sea and Bohai Sea regions,seagrass bed assessment and monitoring have been largely overlooked.Thus,strengthening research efforts is necessary to identify current distribution patterns and long-term changes in seagrass bed resources.This study focused on a seagrass bed in Sanggou Bay,Rongcheng,using remote sensing(RS)and geographic information system technologies to analyze multisource satellite data from the US Landsat and Chinese resource satellite series.By combining RS indexes with historical survey data,large-scale temporal and geographic distribution data for seagrass beds were obtained in the study area from 1985 to 2022.The spatial distribution and evolution trends of the seagrass bed were analyzed using a water depth inversion model,and the factors driving its degradation were identified.Results indicated that the seagrass bed area in Sanggou Bay fluctuated between 100 and 140 km2 from 1985 to 2010.During 2010–2013,dynamic changes in the seagrass bed area increased,with a considerable decrease in its overall size.After 2014,changes were minimal,indicating a notably stable state.Seagrass bed degradation in Sanggou Bay is influenced by high-intensity human activities,pollution from coastal land sources,raft cultures,underwater terrain conditions,and sedimentary environmental factors.The findings offer essential insights for developing seagrass restoration and protection strategies in Sanggou Bay and contribute to the broader scientific efforts for coastal ecosystem conservation and rehabilitation. 展开更多
关键词 seagrass bed spatiotemporal evolution remote sensing technology driving factors human activities environmental effect
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Quantitative assessment of driving factors behind the ecological effects of the Beijing-Tianjin sandstorm source region,China during past 20 years 认领 引用
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作者 Changlong Li Bin Sun +3 位作者 Shiqi Huang Yu Zang Sheng Liang Mouchun Han 《Ecological Frontiers》 CSCD 2025年第4期1005-1016,共12页
The Beijing–Tianjin sandstorm source region(BTSSR)is an important ecological barrier in North China,which can prevent land desertification from spreading.However,the challenge of separating the impacts of climate cha... The Beijing–Tianjin sandstorm source region(BTSSR)is an important ecological barrier in North China,which can prevent land desertification from spreading.However,the challenge of separating the impacts of climate change from those of human activities on ecological restoration remains a critical concern.This study addresses this issue by employing residual trend analysis to investigate long-term trends in net ecosystem productivity(NEP),water conservation(WC),soil erosion(SE),and habitat quality(HQ)in the BTSSR.The results showed that the ecological recovery of the study area was significantly improved.Notably,there is a significant increase in NEP,with affected areas constituting 68.88%of the total,alongside a 56.11%expansion in WC.Conversely,HQ showed a modest increase in 25.59%,while SE experienced a significant decline in half of the study area.The strong positive correlation noted between NEP and summer precipitation,leading to the selection of NEP as a key index for assessing ecological restoration drivers.The research identifies engineering measures as the primary force propelling restoration efforts,contributing 38.18%,followed by precipitation at 26.80%.Predominantly,these impactful areas are situated in the southern region,where beneficial water and thermal conditions foster higher vegetation coverage.The methodology employed here enhances the precision of evaluating ecological engineering across various regions and climatic contexts,offering vital insights for national ecological governance and restoration initiatives. 展开更多
关键词 Beijing-Tianjin sandstorm source region Residual trend analysis method Long time series Driving factors
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Assessment and Driving Factors of Desertification Vulnerability in the Mu Us Sandy Land,China:A MEDALUS-Based Approach 认领 引用
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作者 Yu Ren Xidong Chen 《Journal of Environmental & Earth Sciences》 CAS 2025年第6期213-226,共14页
As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification... As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km2,constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km2(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region. 展开更多
关键词 Desertification Risk MEDALUS Geographical Detector Method Driving Factors
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Uncovering the spatiotemporal evolution and driving mechanisms of soybean planting area in China from 2000 to 2022 认领 引用
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作者 Wenbin Liu Shu Li +8 位作者 Juan Cao Jun Xie Jinwei Dong Jichong Han Qinghang Mei Lichang Yin Hongyan Zhang Hong Zhou Fulu Tao 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2026年第5期2121-2138,共18页
Understanding the spatial distribution,temporal dynamics,and driving factors of soybean cultivation is critical for yield estimation,agricultural planning,and national food security.However,high-resolution,long-term,a... Understanding the spatial distribution,temporal dynamics,and driving factors of soybean cultivation is critical for yield estimation,agricultural planning,and national food security.However,high-resolution,long-term,and nationwide datasets of soybean cultivation in China remain scarce.This study developed a 30-m resolution dataset of soybean in China from2000-2022 using multi-source data(ChinaSoyA30m),and analyzed the spatiotemporal dynamics and driving forces of soybean cultivation.The phenological characteristics of major crops across China were evaluated to generate training samples for supervised classification.Gap statistics,K-means clustering,and spectral angle mapping were employed to enhance classification reliability.A supervised classification approach was implemented on Google Earth Engine(GEE)using dense Landsat data to produce annual soybean maps.ChinaSoyA30m demonstrates competitive performance compared to six existed soybean datasets,with strong correlations with provincial,prefectural,and county statistics(R2=0.95,0.89,and 0.80),and the F1 scores validated against ground truth data were 70.16,80.40,and 78.38%.Since 2000,the soybean planting area has exhibited a fluctuating upward trend with distinct regional characteristics.Northern China emerged as the primary production area,characterized by a stable planting centroid and small spatial variation.The primary driver of soybean area dynamics was the "value added of primary industry",while gross power of agricultural machinery was a significant factor in North China,highlighting regional differences in driving mechanisms.This study provides the first long-term,high-resolution soybean planting dataset for China and offers valuable insights into the sustainable development of soybean cultivation. 展开更多
关键词 soybean remote sensing classification spatiotemporal dynamics driving factors
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Unveiling the drivers of PM2.5 and O3 pollution rebound in Shandong,China during three periods of 2023 by an integrated machine learning method 认领 引用
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作者 Gang WANG Sai LIU +3 位作者 Kai WANG Huijuan MENG Na ZHAO Hanyu ZHANG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第7期746-761,I0050-I0056,共16页
Following the relaxation of coronavirus disease 2019 restrictions and the subsequent full economic recovery,Shandong Province,China experienced a 4.3%rebound in the air quality index in 2023,with both fine particulate... Following the relaxation of coronavirus disease 2019 restrictions and the subsequent full economic recovery,Shandong Province,China experienced a 4.3%rebound in the air quality index in 2023,with both fine particulate matter(PM2.5)and ozone(O3)concentrations exhibiting noticeable upward trends.Quantifying the drivers of this rebound is essential for developing targeted air quality management strategies.To this end,the analysis focused on the early spring period(ESP,February to April)and autumn harvest period(AHP,September to October)for PM2.5 pollution and the photochemical season period(PSP,July to October)for O3 pollution.We developed an interpretable random forest-Shapley additive explanation(RF-SHAP)framework optimized with a tree-structured Parzen estimator(TPE)to assess the impacts of anthropogenic emissions and meteorological factors.The introduction of the TPE optimization technique enhanced RF model performance across these pollution periods.Anthropogenic emissions played the dominant role in PM2.5 pollution rebounds,contributing 14.1%during the ESP and 19.0%during the AHP,for example,industrial recovery(9.2%increase in energy consumption)and agricultural waste burning(70.0%increase in crop residue burning incident).In contrast,O3 pollution was more strongly influenced by meteorological conditions,which contributed a 5.8%increase during the PSP.Critical meteorological drivers included strengthened atmospheric oxidation capacity,reduced total cloud cover,and changes in boundary layer height,although precursor emissions from the transportation and petrochemical industries remained indispensable for O3 formation.This study provides an important scientific basis for precise air quality management in Shandong Province in the postpandemic period. 展开更多
关键词 Air pollution rebound Driving factors Random forest-Shapley additive explanation(RF-SHAP) Anthropogenic emissions Meteorological conditions
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Farmers'participation in soil conservation programs and its influencing factors:Evidence from the Three Gorges Reservoir area 认领 引用
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作者 WEI Jie XIA Chengcheng +3 位作者 WANG Min TANG Qiang SONG Minxin HE Xiubin 《Journal of Mountain Science》 SCIE CSCD 2026年第7期3317-3333,共17页
Sustained farmer participation is fundamental to the success of soil conservation initiatives in erosion-prone mountainous agricultural regions.The Three Gorges Reservoir area of China,characterized by steep terrain,e... Sustained farmer participation is fundamental to the success of soil conservation initiatives in erosion-prone mountainous agricultural regions.The Three Gorges Reservoir area of China,characterized by steep terrain,ecological fragility,and a sensitive human-land interface,offers an instructive context for examining the drivers of farmer engagement in such programs.This study draws on two waves of repeated cross-sectional questionnaire surveys conducted in 2015 and 2022 to compare aggregate-level changes in farmers’attitudes,involvement,and conservation practices.A random forest model was employed to identify key determinants of participation.Over the study period,farmers’awareness of soil conservation,supportive attitudes,and perceived importance of the issue increased by 32.69%,8.03%,and 2.19%,respectively.The proportions of farmers exhibiting moderate and high participation levels rose by 21.16% and 23.12% in the 2022 sample relative to 2015.The most pronounced increase in participation(49.9%)occurred during the planning and design stages of conservation programs.Farmers demonstrated a growing willingness to adopt soil conservation measures,with behavioral uptake following a distinct sequence:reverse-slope tillage,crop rotation or intercropping,slope-to-terrace conversion,hedgerow planting,and contour tillage.The random forest model achieved strong predictive performance,with a test-set accuracy of 0.825,weighted precision of 0.838,weighted recall of 0.825,and weighted F1-score of 0.82.Results indicate that having benefited from conservation programs,awareness of soil conservation,support for program implementation,and perceived importance of soil conservation were the most influential factors associated with participation.Despite gains in perceived importance,substantial scope remains for enhancing engagement.Accordingly,strengthening extension and training efforts,while tailoring program design to local natural,social,and economic conditions,is essential for further progress. 展开更多
关键词 Farmers’participation Soil conservation measures Soil conservation behavior Random forest Driving factors Three Gorges Reservoir area
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Indirect drivers of urban impervious surface:Spatial interaction and policy in Beijing-Tianjin-Hebei region,China 认领 引用
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作者 YANG Junhui SHI Wenjiao XU Xinliang 《Journal of Geographical Sciences》 SCIE CSCD 2026年第5期1257-1277,共21页
Disentangling the driving mechanisms of urban impervious surface(UIS)spatial changes is critical for developing effective urban growth planning.However,previous studies often overlooked the indirect effects of multipl... Disentangling the driving mechanisms of urban impervious surface(UIS)spatial changes is critical for developing effective urban growth planning.However,previous studies often overlooked the indirect effects of multiple factors especially inter-urban spatial interaction and policy factors on urban expansion in urban clusters.Here,we used structural equation modeling and geographically weighted regression to quantify the spatiotemporal patterns of direct and indirect effects of socioeconomic factors,geographical environment,inter-urban spatial interaction,and policy factors on urban expansion in the Beijing-Tianjin-Hebei(BTH)region from 1990 to 2020.The findings showed that urban population,inter-urban spatial interaction,tertiary industry,road density,and policies were the main drivers of UIS changes.Among them,inter-urban spatial interaction primarily had an indirect positive effect on urban spatial patterns by increasing urban population and optimizing industrial structures,with the strongest impact in southern BTH.Regional planning policies such as development zones promoted urban expansion by stimulating industrial development and attracting urban population,with their influence escalating from 0.41 in 1990 to 0.57 in 2010.These findings highlight the importance of strategically guiding inter-urban spatial interactions and optimizing industrial layouts to foster compact urban development and sustainable land use in the BTH region. 展开更多
关键词 urban impervious surface urban cluster urban spatial pattern driving factors structural equation model geographically weighted regression
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Dynamic changes and driving factors of ecosystem service value(ESV)in the Northeast Forest Belt of China 认领 引用 被引量：2
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作者 Jiao Shi Yujuan Gao Yuyou Zou 《Journal of Forestry Research》 SCIE EI CAS CSCD 2025年第2期167-186,共20页
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec... The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth. 展开更多
关键词 Ecosystem service value(ESV) Northeast Forest Belt of China Equivalent factor method Geographic detectors Driving factors
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