Texas is the largest state by area in the US after Alaska,and one of the top states in the production and consumption of electricity with many coal-fired plants.Coal-fired power plants emit greater than 70% of polluta...Texas is the largest state by area in the US after Alaska,and one of the top states in the production and consumption of electricity with many coal-fired plants.Coal-fired power plants emit greater than 70% of pollutants in the energy sector.When coal is burned to produce electricity,nitrogen oxides(NO_(x))are released into the air,one of the main pollutants that threaten human health and lead to a large number of premature deaths.The key to effective air quality management is the strict compliance of all plants with emission standards.However,not all Texas coal plants have the environmental equipment to lower pollutant emissions.Nitrogen dioxide(NO2)observations from the TROPOspheric Monitoring Instrument(TROPOMI)were used to evaluate the emissions for Texas power plants.Data from both the Emissions and Generation Resource Integrated Database(EGRID)and the Emissions Database for Global Atmospheric Research(EDGAR)were used to examine emissions.It was found that NOx emissions for Texas power plants range from 1.53 kt/year to 10.99 kt/year,with the Martin Lake,Limestone and Fayette Power Project stations being the top emitters.WA Parish and Martin Lake stations have the strongest NOx fluxes,with both exhibiting significant seasonal variability.Comparisons of bottom-up inventories for EDGAR and EGRID show a high correlation(r=0.956)and a low root mean square error(0.766).A more reasonable control policy would lead to much reduced NOx emissions.展开更多
GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieve...GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.展开更多
The expansion of construction land on slopes in mountainous cities like Lanzhou has addressed the shortage of flat land but compromised slope stability,leading to uneven land subsidence and risks to infrastructure.Thi...The expansion of construction land on slopes in mountainous cities like Lanzhou has addressed the shortage of flat land but compromised slope stability,leading to uneven land subsidence and risks to infrastructure.This study assessed the land subsidence before and after urban expansion in five areas of Lanzhou by using slope spectrum construction method and gradient expansion intensity measurement that integrated with SBAS-InSAR technology.The results show that construction land on slopes over 20°increased significantly,accounting for 16%of new construction land.The average slope spectrum index was 4.02,with the upper slope limit rising by 8.2°.The land subsidence rate threshold increased by 10 mm/a,and the proportion of pixels experiencing subsidence greater than 5 mm/year rose from 3.63%to 5.24%.Increased construction intensity on slopes caused higher and faster subsidence,which diminished with greater distance from the expansion areas.Areas with slopes between 10°and 25°saw the greatest acceleration in subsidence.Geological composition,building density,groundwater exploitation,and cut-and-fill thickness collectively influence land subsidence rates.This study provides a scientific basis for mitigating geological disaster risks and promoting safe urban development in mountainous cities.展开更多
Due to the multiple impacts of global climate change and anthropogenic disturbances,regional ecological landscapes have been developing towards fragmentation.How to quantitatively measure regional ecological landscape...Due to the multiple impacts of global climate change and anthropogenic disturbances,regional ecological landscapes have been developing towards fragmentation.How to quantitatively measure regional ecological landscape fragmentation and identify its key drivers is an important foundation for regional biodiversity conservation and ecosystem restoration.Taking the Guanzhong Plain Urban Agglomeration(GPUA),China as the research object,this paper proposes a comprehensive framework that integrates landscape pattern index,principal component analysis,random forest(RF)and other methods to quantitatively analyze the spatial and temporal evolution of ecological landscape fragmentation and its driving factors.The results show that:1)cropland,forestland and grassland showed significant spatial differentiation in the landscape pattern index,and the change of their mean values indicated that cropland and forestland show a trend of‘little decrease-continuous increase’.Spatially,the northwestern and southeastern regions showed significant fragmentation and prominent spatial heterogeneity.2)From 2010 to 2020,the landscape fragmentation of cropland and forestland increased by 71%and 20%,respectively,while that of grassland decreased by 33%,indicating that the degree of landscape fragmentation of cropland changed more drastically than that of other ecological land.3)It was found that slope was the most important factor affecting landscape fragmentation of ecological land.In addition,road density had a significant effect on landscape fragmentation of cropland and forestland,but the min-distance between patches and the county center had an important effect on landscape fragmentation of grassland.This study can provide theoretical references for urban agglomeration planning and sustainable landscape management on a regional scale.展开更多
0 INTRODUCTION Permafrost refers to the ground that remains frozen year-round in polar and high-altitude regions,and its structure has traditionally been described by two distinct layers:the active layer and the perma...0 INTRODUCTION Permafrost refers to the ground that remains frozen year-round in polar and high-altitude regions,and its structure has traditionally been described by two distinct layers:the active layer and the permafrost layer(Dobiński,2011;French and Shur,2010;Muller,1943).The active layer undergoes seasonal cycles of thawing and freezing,which significantly influence hydrological cycles,biogeochemical processes,and ecosystem productivity(Dobiński,2020;Luo et al.,2023).展开更多
Precipitation types primarily include rainfall,snowfall,and sleet,and the transformation of precipitation types has significant impacts on regional climate,ecosystems,and the land-atmosphere system.This study employs ...Precipitation types primarily include rainfall,snowfall,and sleet,and the transformation of precipitation types has significant impacts on regional climate,ecosystems,and the land-atmosphere system.This study employs the Ding method to separate precipitation types from three datasets(CMFD,ERA5_Land,and CN05.1).Using data from 26meteorological observation stations in the Chinese Tianshan Mountains Region(CTMR)of China as the validation dataset,the precipitation type separation accuracy of three datasets was evaluated.Additionally,the impacts of relative humidity,precipitation amount,and air temperature on the accuracy of precipitation type separation were analyzed.The results indicate that the CMFD dataset provides the highest separation accuracy,followed by CN05.1,with ERA5_Land showing the poorest performance.Spatial correlation analysis reveals that CMFD outperforms the other two datasets at both annual and monthly scales.Root Mean Square Error(RMSE)and Mean Deviation(MD)values suggest that CMFD is more consistent with the station observational data.The analysis further demonstrates that relative humidity and precipitation amount significantly affect separation accuracy.After bias correction,the correlation coefficients between CMFD,ERA5_Land,and station observational data improved to 0.85-0.94,while the RMSE was controlled within 2 mm.The study also revealed that the overestimation of precipitation was positively correlated with the overestimation of rainfall days,negatively correlated with the overestimation of snowfall days,and that underestimated air temperatures led to an increase in the misclassification of snowfall days.This research provides a basis for selecting climate change datasets and managing water resources in alpine regions.展开更多
The urban fringe areas,situated between the urban-rural interface and critical ecological conservation zones,represent highly sensitive and rapidly evolving transitional zones within urban ecosystems,which are signifi...The urban fringe areas,situated between the urban-rural interface and critical ecological conservation zones,represent highly sensitive and rapidly evolving transitional zones within urban ecosystems,which are significantly impacted by the pressures of urban ex-pansion.However,current academic research on their spatial identification and ecological risks remains notably limited.This study fo-cused on Xi’an of China,utilizing multi-source data and the K-means algorithm to identify urban fringe areas during 2014-2022.Addi-tionally,this study assessed the landscape ecological risks from three perspectives,human activities,landscape fragmentation and ecolo-gical restoration in 2022.The results demonstrate that:1)Xi’an’s urban core and urban fringe areas significantly expanded between 2014 and 2022,growing from 145 to 471 km^(2) and 1319 to 1884 km^(2),respectively.The near urban core and mid-zone areas increased,while the near rural area initially decreased and then slightly recovered.2)Over half of the urban fringe area is at medium to high ecolo-gical risk,with higher risk zones concentrated near the urban core,and slight risk areas primarily along the Weihe River and northern edges.3)Landscape fragmentation and road network effects have become primary drivers in urban fringe areas,prompting a shift in their role from‘future expansion area’to‘ecological reserve area’to better support sustainable urban development.This study high-lights the spatial complexity and ecological significance of urban fringe areas,emphasizing their critical role in urban ecological man-agement.展开更多
Under the context of global warming,the mechanism of glacier shrinkage has become a central focus in cryospheric research.The Ányêmaqên Mountain is the most densely distributed glacier area in the sourc...Under the context of global warming,the mechanism of glacier shrinkage has become a central focus in cryospheric research.The Ányêmaqên Mountain is the most densely distributed glacier area in the source region of the Yellow River on the Tibetan Plateau,and it is highly sensitive to climate change.This study utilized the distributed Coupled Snowpack and Ice Energy and Mass Balance Model(COSIMA),integrating High Asia Refinement Analysis(HAR)data and meteorological station observations,to simulate spatiotemporal patterns of energy and mass balance for Ányêmaqên Mountain glaciers.The results demonstrated an annual glacier mass balance of-0.50 m w.e.from 1 January 2021 to 31 December 2023,with substantial mass loss(peaking at-5.4 m w.e.)observed in zones below 5300 m a.s.l.,notably the Halong,Weigeledangxiong,and Yehelong glaciers.The main energy sources for glacier melt were net shortwave radiation(79.38%),sensible heat flux(12.31%)and ground heat flux(8.30%).The main expenditure items of energy included net longwave radiation(67.05%),available heat for melt(14.97%)and latent heat flux(17.98%).Solid precipitation accounted for 95%of the accumulation of glacier mass balance,and melt-water refreezing accounted for 5.0%.Sensitivity experiments revealed that rising air temperatures and declining precipitation were the principal drivers of mass loss,with a 1 K temperature increase requiring a 20%annual precipitation increase to offset equivalent mass loss.The mass loss of glaciers was mainly caused by superimposed ice surface ablation and subsurface ablation.This study is an important reference for a deeper understanding of the glacier’s response to climate change in the source region of Yellow River.展开更多
High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for re...High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for regional air quality control and management. In this study, PM_(2.5) data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM_(2.5) concentration in China were evaluated. The main results are as follows.(1) In general, the average concentration of PM_(2.5) in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3.(2) PM_(2.5) is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM_(2.5) concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM_(2.5).(3) The center of gravity of PM_(2.5) has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM_(2.5) concentrations have moved eastward, while low-value PM_(2.5) has moved westward.(4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The "High-High" PM_(2.5) agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The "Low-Low" PM_(2.5) agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands.(5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM_(2.5) concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM_(2.5) concentration in China.展开更多
To resolve conflicts between development and the preservation of the natural environment,enable economic transformation,and achieve the global sustainable development goals(SDGs),green development(GD)is gradually beco...To resolve conflicts between development and the preservation of the natural environment,enable economic transformation,and achieve the global sustainable development goals(SDGs),green development(GD)is gradually becoming a major strategy in the construction of an ecological civilization and the ideal of building a"beautiful China",alongside the transformation and reconstruction of the global economy.Based on a combination of the concept and implications of GD,we first used the Slacks Based Model with undesirable outputs(SBM-Undesirable),the Theil index,and the spatial Markov chain to measure the spatial patterns,regional differences,and spatio-temporal evolution of urban green development efficiency(UGDE)in China from 2005 to 2015.Second,by coupling natural and human factors,the mechanism influencing UGDE was quantitatively investigated under the framework of the human-environment interaction.The results showed that:(1)from 2005 to 2015,the UGDE increased from 0.475 to 0.523,i.e.,an overall increase of 10%.In terms of temporal variation,there was a staged increase,with its evolution having the characteristics of a"W-shaped"pattern.(2)The regional differences in UGDE followed a pattern of eastern>central>western.For different types of urban agglomeration,the UGDE had inverted pyramid cluster growth characteristics that followed a pattern of"national level>regional level>local level",forming a stable hierarchical scale structure of"super cities>mega cities>big cities>medium cities>small cities".(3)UGDE in China has developed with significant spatial agglomeration characteristics.High-efficiency type cities have positive spillover effects,while low-efficiency cities have negative effects.Different types of urban evolution processes have a path dependence,and a spatial club convergence phenomenon exists,in which areas with high UGDE are concentrated and drive low UGDE elsewhere.(4)Under the framework of regional human-environment interaction,the degree of human and social influence on UGDE is greater than that of the natural background.The economic strength,industrial structure,openness,and climate conditions of China have positively promoted UGDE.展开更多
The Three-River Headwaters region in China is an ecological barrier providing en- vironmental protection and regional sustainable development for the mid-stream and down- stream areas, which also plays an important ro...The Three-River Headwaters region in China is an ecological barrier providing en- vironmental protection and regional sustainable development for the mid-stream and down- stream areas, which also plays an important role in animal husbandry in China. This study estimated the grassland yield in the Three-River Headwaters region based on MODIS NPP data, and calculated the proper livestock-carrying capacity of the grassland. We analyzed the overgrazing number and its spatial distribution characteristics through data comparison be- tween actual and proper livestock-carrying capacity. The results showed the following： （1） total grassland yield （hay） in the Three-River Headwaters region was 10.96 million tons in 2010 with an average grassland yield of 465.70 kg/hm2 （the spatial distribution presents a decreasing trend from the east and southeast to the west and northwest in turn）; （2） the proper livestock-carrying capacity in the Three-River Headwaters region is 12.19 million sheep units （hereafter described as ＂SU＂）, and the average stocking capacity is 51.27 SU [the proper carrying capacity is above 100 SU/km2 in the eastern counties, 60 SU/km2 in the cen- tral counties （except Madoi County）, and 30 SU/km2 in the western counties]; and （3） total overgrazing number was 6.52 million SU in the Three-River Headwaters region in 2010, with an average overgrazing ratio of 67.88% and an average overgrazing number of 27.43 SU/km2 A higher overgrazing ratio occurred in Tongde, Xinghai, Yushu, Henan and Z^kog. There was no overgrazing in Zhiduo, Tanggula Township and Darlag, Qumerleb and Madoi. The re- mainder of the counties had varying degrees of overgrazing.展开更多
Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by ...Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.展开更多
The assessment of the spatiotemporal evolution of habitat quality caused by land use changes can provide a scientifc basis for the ecological protection and green development of mining cities.Taking Yanshan County as ...The assessment of the spatiotemporal evolution of habitat quality caused by land use changes can provide a scientifc basis for the ecological protection and green development of mining cities.Taking Yanshan County as an example of a typical mining city,this article discussed the spatial pattern and evolution characteristics of habitat quality in 2000 and 2018 based on the ArcGIS platform and the InVEST model.The conclusions are as below:from 2000 to 2018,the area of farmland and construction land changed the most in the study area.Among them,the area of farmland decreased by 3.48%,and the area of industrial and mining land and construction land increased by 53.25%.Areas of low,relatively low and high habitat quality expanded,and areas of medium and relatively high habitat quality shrank,which is closely related to the distribution of land use.The areas with high habitat degradation degrees appear around cities,mining areas and watersheds,while the areas with low habitat degradation degrees are mainly distributed in the southern woodland.The distribution of cold and hot spots in the habitat quality distribution of Yanshan County presents a pattern of“hot in the south and cold in the north”.The results are of great signifcance to the precise implementation of ecosystem management decisions in mining cities and the creation of a landscape pattern of“beautiful countrysides,green cities,and green mines”.展开更多
The Yarlung Zangbo River Basin(YZRB)is a key ecological protection area on the Qinghai-Tibet Plateau(QTP).Determination of the ecosystem service values(ESVs)can help recognize the benefits of sustainable management.It...The Yarlung Zangbo River Basin(YZRB)is a key ecological protection area on the Qinghai-Tibet Plateau(QTP).Determination of the ecosystem service values(ESVs)can help recognize the benefits of sustainable management.It is gradually becoming the main path that constructs plateau spatial planning of integrating ecological protection,and achieves global sustainable development goals(SDGs)in China.In this paper,the spatio-temporal dynamic evolutions of the ESVs were estimated on the multiple scales of“basin,subbasin and watershed”from 1980 to 2015.The main factors influencing ESVs were explored in terms of physical geography,human activities,and climate change.It had been proposed that sustainable spatial planning including ecological protection,basin management,and regional development was urgent to set up.Our results show that the increase in wetland and forest and results in an increase of 9.4%in the ESVs.Attention should be paid to the reduction of water and grassland.Water conservation(WC),waste treatment(WT),and soil formation and conservation(SFC)are the most important ecosystem services in the YZRB.At present,the primary problem is to solve the ESVs decreasing caused by glacier melting,grassland degradation,and desertification in the upper reaches region.The middle reaches should raise the level of supply services.Regulation services should be increased in the lower reaches region on the premise of protecting vegetation.The ESVs in adjacent watersheds are interrelated and the phenomenon of“high agglomeration and low agglomeration”is obvious,existing hot-spots and cold-spots of ESVs.Additionally,when the altitude is 4500-5500 m,the temperature is 3-8°C,and the annual precipitation is 350-650 mm,ESVs could reach its maximum.A framework of sustainable plateau spatial planning could provide references to delimit the ecological protection red line,key ecological function zone,and natural resource asset accounting on the QTP.展开更多
The reasonable prior information between the parameters in the adjustment processing can significantly improve the precision of the parameter solution. Based on the principle of equality constraints, we establish the ...The reasonable prior information between the parameters in the adjustment processing can significantly improve the precision of the parameter solution. Based on the principle of equality constraints, we establish the mixed additive and multiplicative random error model with equality constraints and derive the weighted least squares iterative solution of the model. In addition, aiming at the ill-posed problem of the coefficient matrix, we also propose the ridge estimation iterative solution of ill-posed mixed additive and multiplicative random error model with equality constraints based on the principle of ridge estimation method and derive the U-curve method to determine the ridge parameter. The experimental results show that the weighted least squares iterative solution can obtain more reasonable parameter estimation and precision information than existing solutions, verifying the feasibility of applying the equality constraints to the mixed additive and multiplicative random error model. Furthermore, the ridge estimation iterative solution can obtain more accurate parameter estimation and precision information than the weighted least squares iterative solution.展开更多
Sensitivity assessment is useful for monitoring land desertification. Research into how to prevent and control desertification is also important. In the arid region of northwest China, desertification is becoming wors...Sensitivity assessment is useful for monitoring land desertification. Research into how to prevent and control desertification is also important. In the arid region of northwest China, desertification is becoming worse and is a serious problem that affects local sustainable development. Based on remote-sensing and geographic information system technology, this study establishes a 'soil-terrain-hydrology-climate-vegetation' desertification sensitivity comprehensive evaluation system to reflect the spatiotemporal changes of land desertification, and proposes a spatial distance model to calculate a desertification sensitivity index. The spatiotemporal change characteristics of land desertification sensitivity in northwest China are quantitatively assessed from 2000 to 2017. Moreover, the main driving factors are analyzed using the geographical detector method. The results show the following.(1) Terrain, soil, climate, vegetation and hydrology affect and restrict each other, and constitute the background conditions of the distributions and changes of sensitivity to desertification in northwest China.(2) Desertification sensitivity generally displays a low distribution characteristic on the periphery of the area and a high one in the interior. The low-sensitivity regions are mainly in the five major mountain ranges(Altai Mountains, Tianshan Mountains, Kunlun Mountains, Altun Mountains and Qilian Mountains), while the high-sensitivity regions are mainly in regions such as the Junggar Basin, the Tarim Basin and the Inner Mongolia Plateau, as well as the Taklimakan Desert, Badain Jaran Desert and Tengger Desert. The spatial distribution of desertification sensitivity is obviously regional, and the high-and low-sensitivity regions have clear boundaries and a concentrated distribution.(3) With regard to spatiotemporal evolution, changes in desertification sensitivity since 2000 have been predominantly stable, and the overall sensitivity has displayed a slowly decreasing trend, indicating that potential desertification regions are decreasing annually and that some achievements have been made in the control of regional desertification.(4) Soil and climate play a direct role in the driving factors of desertification in northwest China, and these have been found to be the most important influential factors. Vegetation is the most active and basic factor in changing the sensitivity. In addition, topography and hydrology play a role in restricting desertification changes. Socio-economic factors are the most rapid factors affecting regional desertification sensitivity, and their impacts tend to be gradually increasing. In general, desertification has been effectively controlled in northwest China, and positive results have been achieved in such control. However, against the backdrop of intensified global climate change, increasingly prominent human activities and new normals of socio-economic development, the monitoring, assessment and control of desertification in China still have a long way to go.展开更多
When linearizing three-dimensional(3 D)coordinate similarity transformation model with large rotations,we usually encounter the ill-posed normal matrix which may aggravate the instability of solutions.To alleviate the...When linearizing three-dimensional(3 D)coordinate similarity transformation model with large rotations,we usually encounter the ill-posed normal matrix which may aggravate the instability of solutions.To alleviate the problem,a series of conversions are contributed to the 3 D coordinate similarity transformation model in this paper.We deduced a complete solution for the 3 D coordinate similarity transformation at any rotation with the nonlinear adjustment methodology,which involves the errors of the common and the non-common points.Furthermore,as the large condition number of the normal matrix resulted in an intractable form,we introduced the bary-centralization technique and a surrogate process for deterministic element of the normal matrix,and proved its benefit for alleviating the condition number.The experimental results show that our approach can obtain the smaller condition number to stabilize the convergence of the interested parameters.Especially,our approach can be implemented for considering the errors of the common and the non-common points,thus the accuracy of the transformed coordinates improves.展开更多
To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a deriv...To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.展开更多
Through theoretical derivation, some properties of the total least squares estimation are found. The total least squares estimation is the linear transformation of the least squares estimation, and the total least squ...Through theoretical derivation, some properties of the total least squares estimation are found. The total least squares estimation is the linear transformation of the least squares estimation, and the total least squares estimation is unbiased. The condition number of the total least squares estimation is greater than the least squares estimation, so the total least squares estimation is easier to be affected by the data error than the least squares estimation. Then through the further derivation, the relationships of solutions, residuals and unit weight variance estimations between the total least squares and the least squares are given.展开更多
Static models of accessibility are usually based on the fixed distance or Average Travel Time(ATT)models.Because of ignoring the traffic as a dynamic process affecting the accessibility through the change of Travel Ti...Static models of accessibility are usually based on the fixed distance or Average Travel Time(ATT)models.Because of ignoring the traffic as a dynamic process affecting the accessibility through the change of Travel Time(TT),these models lead to unperceived temporal inequities.In contrast to the consideration of the temporal Variation of TT(VTT)in the previous studies,the variation of traffic-related TT and its relations with network distance has not been considered.In this study,relations between VTT and network distance to access urban parks in Tehran megacity has been modeled.Traffic maps at five times of day are used to produce TT maps of Traffic Analysis Zones(TAZs)to their 3-closest parks.Comparison of the Gini coefficients of accessibility show significant inequities of accessibility at different times of day.Relations between the distance,ATT,and TT_(max) are modeled by statistical analysis.Results show both TT and TTmax have significant positive relations with distance and traffic and reach their maximum at 6 p.m.Observation of significant relations between distance,ATT,TT_(max),and VTT provides interesting knowledge for the conversion of temporal measures of equity(TT)to a physical measure of equity(distance).A simple application of these findings for effective management of the spatiotemporal inequities is the definition of critical distances from public services.As an example,to decrease the TT_(max) of TAZs to less than 12 min,their maximum distance to the closest parks should be less than 4 km.The developed approach can be adopted for the accessibility evaluation of the other public services,particularly the health and education centers.展开更多
基金This work was supported by the Basic Research Top Talent Plan of Lanzhou Jiaotong University(2022JC05).
文摘Texas is the largest state by area in the US after Alaska,and one of the top states in the production and consumption of electricity with many coal-fired plants.Coal-fired power plants emit greater than 70% of pollutants in the energy sector.When coal is burned to produce electricity,nitrogen oxides(NO_(x))are released into the air,one of the main pollutants that threaten human health and lead to a large number of premature deaths.The key to effective air quality management is the strict compliance of all plants with emission standards.However,not all Texas coal plants have the environmental equipment to lower pollutant emissions.Nitrogen dioxide(NO2)observations from the TROPOspheric Monitoring Instrument(TROPOMI)were used to evaluate the emissions for Texas power plants.Data from both the Emissions and Generation Resource Integrated Database(EGRID)and the Emissions Database for Global Atmospheric Research(EDGAR)were used to examine emissions.It was found that NOx emissions for Texas power plants range from 1.53 kt/year to 10.99 kt/year,with the Martin Lake,Limestone and Fayette Power Project stations being the top emitters.WA Parish and Martin Lake stations have the strongest NOx fluxes,with both exhibiting significant seasonal variability.Comparisons of bottom-up inventories for EDGAR and EGRID show a high correlation(r=0.956)and a low root mean square error(0.766).A more reasonable control policy would lead to much reduced NOx emissions.
基金supported by the National Natural Science Foundation of China(Grant Nos.42404017,42122025 and 42174030).
文摘GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.
基金National Natural Science Foundation of China(Grant No.42271214)National Key R&D Program of China(Grant No.2022YFC3800700)+1 种基金Key Research Program of Gansu Province(Grant No.23ZDKA0004)Natural Science Foundation of Gansu Province(Grant No.21JR7RA281).
文摘The expansion of construction land on slopes in mountainous cities like Lanzhou has addressed the shortage of flat land but compromised slope stability,leading to uneven land subsidence and risks to infrastructure.This study assessed the land subsidence before and after urban expansion in five areas of Lanzhou by using slope spectrum construction method and gradient expansion intensity measurement that integrated with SBAS-InSAR technology.The results show that construction land on slopes over 20°increased significantly,accounting for 16%of new construction land.The average slope spectrum index was 4.02,with the upper slope limit rising by 8.2°.The land subsidence rate threshold increased by 10 mm/a,and the proportion of pixels experiencing subsidence greater than 5 mm/year rose from 3.63%to 5.24%.Increased construction intensity on slopes caused higher and faster subsidence,which diminished with greater distance from the expansion areas.Areas with slopes between 10°and 25°saw the greatest acceleration in subsidence.Geological composition,building density,groundwater exploitation,and cut-and-fill thickness collectively influence land subsidence rates.This study provides a scientific basis for mitigating geological disaster risks and promoting safe urban development in mountainous cities.
基金Under the auspices of National Natural Science Foundation of China(No.42271214)Key Research Program of Gansu Province(No.23ZDKA0004)Natural Science Foundation of Gansu Province(No.25JRRA212,21JR7RA281,22JR11RA149,24JRR A250)。
文摘Due to the multiple impacts of global climate change and anthropogenic disturbances,regional ecological landscapes have been developing towards fragmentation.How to quantitatively measure regional ecological landscape fragmentation and identify its key drivers is an important foundation for regional biodiversity conservation and ecosystem restoration.Taking the Guanzhong Plain Urban Agglomeration(GPUA),China as the research object,this paper proposes a comprehensive framework that integrates landscape pattern index,principal component analysis,random forest(RF)and other methods to quantitatively analyze the spatial and temporal evolution of ecological landscape fragmentation and its driving factors.The results show that:1)cropland,forestland and grassland showed significant spatial differentiation in the landscape pattern index,and the change of their mean values indicated that cropland and forestland show a trend of‘little decrease-continuous increase’.Spatially,the northwestern and southeastern regions showed significant fragmentation and prominent spatial heterogeneity.2)From 2010 to 2020,the landscape fragmentation of cropland and forestland increased by 71%and 20%,respectively,while that of grassland decreased by 33%,indicating that the degree of landscape fragmentation of cropland changed more drastically than that of other ecological land.3)It was found that slope was the most important factor affecting landscape fragmentation of ecological land.In addition,road density had a significant effect on landscape fragmentation of cropland and forestland,but the min-distance between patches and the county center had an important effect on landscape fragmentation of grassland.This study can provide theoretical references for urban agglomeration planning and sustainable landscape management on a regional scale.
基金supported by the Science and Technology Program of Gansu Province(No.23ZDFA017)Western Young Scholars Project of the Chinese Academy of Sciences of China and Longyuan Youth Talents Project(Luo D L)+1 种基金the National Natural Science Foundation of China(No.U2243214)Youth Innovation Promotion Association of the Chinese Academy of Sciences(No.2023445)。
文摘0 INTRODUCTION Permafrost refers to the ground that remains frozen year-round in polar and high-altitude regions,and its structure has traditionally been described by two distinct layers:the active layer and the permafrost layer(Dobiński,2011;French and Shur,2010;Muller,1943).The active layer undergoes seasonal cycles of thawing and freezing,which significantly influence hydrological cycles,biogeochemical processes,and ecosystem productivity(Dobiński,2020;Luo et al.,2023).
基金financial support from the National Natural Sciences Foundation of China(42261026,and 42161025)the Open Foundation of Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone(XJYS0907-2023-01)。
文摘Precipitation types primarily include rainfall,snowfall,and sleet,and the transformation of precipitation types has significant impacts on regional climate,ecosystems,and the land-atmosphere system.This study employs the Ding method to separate precipitation types from three datasets(CMFD,ERA5_Land,and CN05.1).Using data from 26meteorological observation stations in the Chinese Tianshan Mountains Region(CTMR)of China as the validation dataset,the precipitation type separation accuracy of three datasets was evaluated.Additionally,the impacts of relative humidity,precipitation amount,and air temperature on the accuracy of precipitation type separation were analyzed.The results indicate that the CMFD dataset provides the highest separation accuracy,followed by CN05.1,with ERA5_Land showing the poorest performance.Spatial correlation analysis reveals that CMFD outperforms the other two datasets at both annual and monthly scales.Root Mean Square Error(RMSE)and Mean Deviation(MD)values suggest that CMFD is more consistent with the station observational data.The analysis further demonstrates that relative humidity and precipitation amount significantly affect separation accuracy.After bias correction,the correlation coefficients between CMFD,ERA5_Land,and station observational data improved to 0.85-0.94,while the RMSE was controlled within 2 mm.The study also revealed that the overestimation of precipitation was positively correlated with the overestimation of rainfall days,negatively correlated with the overestimation of snowfall days,and that underestimated air temperatures led to an increase in the misclassification of snowfall days.This research provides a basis for selecting climate change datasets and managing water resources in alpine regions.
基金Under the auspices of National Natural Science Foundation of China(No.42271214)National Key R&D Program of China(No.2022YFC3800700)+1 种基金Key Research Program of Gansu Province(No.23ZDKA0004)Key Program of Natural Science Foundation of Gansu Province(No.21JR7RA281,24JRRA250)。
文摘The urban fringe areas,situated between the urban-rural interface and critical ecological conservation zones,represent highly sensitive and rapidly evolving transitional zones within urban ecosystems,which are significantly impacted by the pressures of urban ex-pansion.However,current academic research on their spatial identification and ecological risks remains notably limited.This study fo-cused on Xi’an of China,utilizing multi-source data and the K-means algorithm to identify urban fringe areas during 2014-2022.Addi-tionally,this study assessed the landscape ecological risks from three perspectives,human activities,landscape fragmentation and ecolo-gical restoration in 2022.The results demonstrate that:1)Xi’an’s urban core and urban fringe areas significantly expanded between 2014 and 2022,growing from 145 to 471 km^(2) and 1319 to 1884 km^(2),respectively.The near urban core and mid-zone areas increased,while the near rural area initially decreased and then slightly recovered.2)Over half of the urban fringe area is at medium to high ecolo-gical risk,with higher risk zones concentrated near the urban core,and slight risk areas primarily along the Weihe River and northern edges.3)Landscape fragmentation and road network effects have become primary drivers in urban fringe areas,prompting a shift in their role from‘future expansion area’to‘ecological reserve area’to better support sustainable urban development.This study high-lights the spatial complexity and ecological significance of urban fringe areas,emphasizing their critical role in urban ecological man-agement.
基金supported by the National Key Research and Development Program of China(2023YFC3206300)National Natural Science Foundation of China(42271156)the program of the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,CAS(No.CSFSE-ZZ-2402).
文摘Under the context of global warming,the mechanism of glacier shrinkage has become a central focus in cryospheric research.The Ányêmaqên Mountain is the most densely distributed glacier area in the source region of the Yellow River on the Tibetan Plateau,and it is highly sensitive to climate change.This study utilized the distributed Coupled Snowpack and Ice Energy and Mass Balance Model(COSIMA),integrating High Asia Refinement Analysis(HAR)data and meteorological station observations,to simulate spatiotemporal patterns of energy and mass balance for Ányêmaqên Mountain glaciers.The results demonstrated an annual glacier mass balance of-0.50 m w.e.from 1 January 2021 to 31 December 2023,with substantial mass loss(peaking at-5.4 m w.e.)observed in zones below 5300 m a.s.l.,notably the Halong,Weigeledangxiong,and Yehelong glaciers.The main energy sources for glacier melt were net shortwave radiation(79.38%),sensible heat flux(12.31%)and ground heat flux(8.30%).The main expenditure items of energy included net longwave radiation(67.05%),available heat for melt(14.97%)and latent heat flux(17.98%).Solid precipitation accounted for 95%of the accumulation of glacier mass balance,and melt-water refreezing accounted for 5.0%.Sensitivity experiments revealed that rising air temperatures and declining precipitation were the principal drivers of mass loss,with a 1 K temperature increase requiring a 20%annual precipitation increase to offset equivalent mass loss.The mass loss of glaciers was mainly caused by superimposed ice surface ablation and subsurface ablation.This study is an important reference for a deeper understanding of the glacier’s response to climate change in the source region of Yellow River.
基金The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA19040401China Postdoctoral Science Foundation,No.2016M600121+1 种基金National Natural Science Foundation of China,No.41701173,No.41501137The State Key Laboratory of Resources and Environmental Information System
文摘High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for regional air quality control and management. In this study, PM_(2.5) data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM_(2.5) concentration in China were evaluated. The main results are as follows.(1) In general, the average concentration of PM_(2.5) in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3.(2) PM_(2.5) is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM_(2.5) concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM_(2.5).(3) The center of gravity of PM_(2.5) has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM_(2.5) concentrations have moved eastward, while low-value PM_(2.5) has moved westward.(4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The "High-High" PM_(2.5) agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The "Low-Low" PM_(2.5) agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands.(5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM_(2.5) concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM_(2.5) concentration in China.
基金National Natural Science Foundation of China,No.41701173,No.41961027Foundation for the Excellent Youth Scholars of Ministry of Education of China,No.17YJCZH268。
文摘To resolve conflicts between development and the preservation of the natural environment,enable economic transformation,and achieve the global sustainable development goals(SDGs),green development(GD)is gradually becoming a major strategy in the construction of an ecological civilization and the ideal of building a"beautiful China",alongside the transformation and reconstruction of the global economy.Based on a combination of the concept and implications of GD,we first used the Slacks Based Model with undesirable outputs(SBM-Undesirable),the Theil index,and the spatial Markov chain to measure the spatial patterns,regional differences,and spatio-temporal evolution of urban green development efficiency(UGDE)in China from 2005 to 2015.Second,by coupling natural and human factors,the mechanism influencing UGDE was quantitatively investigated under the framework of the human-environment interaction.The results showed that:(1)from 2005 to 2015,the UGDE increased from 0.475 to 0.523,i.e.,an overall increase of 10%.In terms of temporal variation,there was a staged increase,with its evolution having the characteristics of a"W-shaped"pattern.(2)The regional differences in UGDE followed a pattern of eastern>central>western.For different types of urban agglomeration,the UGDE had inverted pyramid cluster growth characteristics that followed a pattern of"national level>regional level>local level",forming a stable hierarchical scale structure of"super cities>mega cities>big cities>medium cities>small cities".(3)UGDE in China has developed with significant spatial agglomeration characteristics.High-efficiency type cities have positive spillover effects,while low-efficiency cities have negative effects.Different types of urban evolution processes have a path dependence,and a spatial club convergence phenomenon exists,in which areas with high UGDE are concentrated and drive low UGDE elsewhere.(4)Under the framework of regional human-environment interaction,the degree of human and social influence on UGDE is greater than that of the natural background.The economic strength,industrial structure,openness,and climate conditions of China have positively promoted UGDE.
基金The Chinese National Non-profit Program for Environment Protection,No.201109030
文摘The Three-River Headwaters region in China is an ecological barrier providing en- vironmental protection and regional sustainable development for the mid-stream and down- stream areas, which also plays an important role in animal husbandry in China. This study estimated the grassland yield in the Three-River Headwaters region based on MODIS NPP data, and calculated the proper livestock-carrying capacity of the grassland. We analyzed the overgrazing number and its spatial distribution characteristics through data comparison be- tween actual and proper livestock-carrying capacity. The results showed the following： （1） total grassland yield （hay） in the Three-River Headwaters region was 10.96 million tons in 2010 with an average grassland yield of 465.70 kg/hm2 （the spatial distribution presents a decreasing trend from the east and southeast to the west and northwest in turn）; （2） the proper livestock-carrying capacity in the Three-River Headwaters region is 12.19 million sheep units （hereafter described as ＂SU＂）, and the average stocking capacity is 51.27 SU [the proper carrying capacity is above 100 SU/km2 in the eastern counties, 60 SU/km2 in the cen- tral counties （except Madoi County）, and 30 SU/km2 in the western counties]; and （3） total overgrazing number was 6.52 million SU in the Three-River Headwaters region in 2010, with an average overgrazing ratio of 67.88% and an average overgrazing number of 27.43 SU/km2 A higher overgrazing ratio occurred in Tongde, Xinghai, Yushu, Henan and Z^kog. There was no overgrazing in Zhiduo, Tanggula Township and Darlag, Qumerleb and Madoi. The re- mainder of the counties had varying degrees of overgrazing.
基金financially supported by the Project of State Key Basic R & D Program of China (973 Program, Grant No. 2010CB951002)the key deployment project of Chinese Academy of Sciences (Grant No. KZZD-EW-12-2)Chinese Academy of Sciences Visiting Professorship for Senior International Scientists (Grant No. 2011T2Z40)
文摘Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.
基金was funded by the Jiangxi Provincial Social Science Foundation“the 14th Five-Year Plan”(2021)regional project(21DQ44)Science and Technology Research Project of Jiangxi Provincial Department of Education(GJJ210723)+1 种基金the Doctoral Research Initiation fund of East China University of Technology(DHBK2019184)the Graduate Innovation Fund of East China University of Technology(DHYC-202123).
文摘The assessment of the spatiotemporal evolution of habitat quality caused by land use changes can provide a scientifc basis for the ecological protection and green development of mining cities.Taking Yanshan County as an example of a typical mining city,this article discussed the spatial pattern and evolution characteristics of habitat quality in 2000 and 2018 based on the ArcGIS platform and the InVEST model.The conclusions are as below:from 2000 to 2018,the area of farmland and construction land changed the most in the study area.Among them,the area of farmland decreased by 3.48%,and the area of industrial and mining land and construction land increased by 53.25%.Areas of low,relatively low and high habitat quality expanded,and areas of medium and relatively high habitat quality shrank,which is closely related to the distribution of land use.The areas with high habitat degradation degrees appear around cities,mining areas and watersheds,while the areas with low habitat degradation degrees are mainly distributed in the southern woodland.The distribution of cold and hot spots in the habitat quality distribution of Yanshan County presents a pattern of“hot in the south and cold in the north”.The results are of great signifcance to the precise implementation of ecosystem management decisions in mining cities and the creation of a landscape pattern of“beautiful countrysides,green cities,and green mines”.
基金Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401)National Natural Science Foundation of China(41961027)+1 种基金National Natural Science Foundation of China(41701173)China Postdoctoral Science Foundation(2016M600121)。
文摘The Yarlung Zangbo River Basin(YZRB)is a key ecological protection area on the Qinghai-Tibet Plateau(QTP).Determination of the ecosystem service values(ESVs)can help recognize the benefits of sustainable management.It is gradually becoming the main path that constructs plateau spatial planning of integrating ecological protection,and achieves global sustainable development goals(SDGs)in China.In this paper,the spatio-temporal dynamic evolutions of the ESVs were estimated on the multiple scales of“basin,subbasin and watershed”from 1980 to 2015.The main factors influencing ESVs were explored in terms of physical geography,human activities,and climate change.It had been proposed that sustainable spatial planning including ecological protection,basin management,and regional development was urgent to set up.Our results show that the increase in wetland and forest and results in an increase of 9.4%in the ESVs.Attention should be paid to the reduction of water and grassland.Water conservation(WC),waste treatment(WT),and soil formation and conservation(SFC)are the most important ecosystem services in the YZRB.At present,the primary problem is to solve the ESVs decreasing caused by glacier melting,grassland degradation,and desertification in the upper reaches region.The middle reaches should raise the level of supply services.Regulation services should be increased in the lower reaches region on the premise of protecting vegetation.The ESVs in adjacent watersheds are interrelated and the phenomenon of“high agglomeration and low agglomeration”is obvious,existing hot-spots and cold-spots of ESVs.Additionally,when the altitude is 4500-5500 m,the temperature is 3-8°C,and the annual precipitation is 350-650 mm,ESVs could reach its maximum.A framework of sustainable plateau spatial planning could provide references to delimit the ecological protection red line,key ecological function zone,and natural resource asset accounting on the QTP.
基金supported by the National Natural Science Foundation of China,Grant Nos.42174011,41874001 and 41664001Innovation Found Designated for Graduate Students of ECUT,Grant No.DHYC-202020。
文摘The reasonable prior information between the parameters in the adjustment processing can significantly improve the precision of the parameter solution. Based on the principle of equality constraints, we establish the mixed additive and multiplicative random error model with equality constraints and derive the weighted least squares iterative solution of the model. In addition, aiming at the ill-posed problem of the coefficient matrix, we also propose the ridge estimation iterative solution of ill-posed mixed additive and multiplicative random error model with equality constraints based on the principle of ridge estimation method and derive the U-curve method to determine the ridge parameter. The experimental results show that the weighted least squares iterative solution can obtain more reasonable parameter estimation and precision information than existing solutions, verifying the feasibility of applying the equality constraints to the mixed additive and multiplicative random error model. Furthermore, the ridge estimation iterative solution can obtain more accurate parameter estimation and precision information than the weighted least squares iterative solution.
基金National Natural Science Foundation of China,No.41861040, No.41761047, No.41961027。
文摘Sensitivity assessment is useful for monitoring land desertification. Research into how to prevent and control desertification is also important. In the arid region of northwest China, desertification is becoming worse and is a serious problem that affects local sustainable development. Based on remote-sensing and geographic information system technology, this study establishes a 'soil-terrain-hydrology-climate-vegetation' desertification sensitivity comprehensive evaluation system to reflect the spatiotemporal changes of land desertification, and proposes a spatial distance model to calculate a desertification sensitivity index. The spatiotemporal change characteristics of land desertification sensitivity in northwest China are quantitatively assessed from 2000 to 2017. Moreover, the main driving factors are analyzed using the geographical detector method. The results show the following.(1) Terrain, soil, climate, vegetation and hydrology affect and restrict each other, and constitute the background conditions of the distributions and changes of sensitivity to desertification in northwest China.(2) Desertification sensitivity generally displays a low distribution characteristic on the periphery of the area and a high one in the interior. The low-sensitivity regions are mainly in the five major mountain ranges(Altai Mountains, Tianshan Mountains, Kunlun Mountains, Altun Mountains and Qilian Mountains), while the high-sensitivity regions are mainly in regions such as the Junggar Basin, the Tarim Basin and the Inner Mongolia Plateau, as well as the Taklimakan Desert, Badain Jaran Desert and Tengger Desert. The spatial distribution of desertification sensitivity is obviously regional, and the high-and low-sensitivity regions have clear boundaries and a concentrated distribution.(3) With regard to spatiotemporal evolution, changes in desertification sensitivity since 2000 have been predominantly stable, and the overall sensitivity has displayed a slowly decreasing trend, indicating that potential desertification regions are decreasing annually and that some achievements have been made in the control of regional desertification.(4) Soil and climate play a direct role in the driving factors of desertification in northwest China, and these have been found to be the most important influential factors. Vegetation is the most active and basic factor in changing the sensitivity. In addition, topography and hydrology play a role in restricting desertification changes. Socio-economic factors are the most rapid factors affecting regional desertification sensitivity, and their impacts tend to be gradually increasing. In general, desertification has been effectively controlled in northwest China, and positive results have been achieved in such control. However, against the backdrop of intensified global climate change, increasingly prominent human activities and new normals of socio-economic development, the monitoring, assessment and control of desertification in China still have a long way to go.
基金supported by the National Natural Science Foundation of China,Nos.41874001 and 41664001Support Program for Outstanding Youth Talents in Jiangxi Province,No.20162BCB23050National Key Research and Development Program,No.2016YFB0501405。
文摘When linearizing three-dimensional(3 D)coordinate similarity transformation model with large rotations,we usually encounter the ill-posed normal matrix which may aggravate the instability of solutions.To alleviate the problem,a series of conversions are contributed to the 3 D coordinate similarity transformation model in this paper.We deduced a complete solution for the 3 D coordinate similarity transformation at any rotation with the nonlinear adjustment methodology,which involves the errors of the common and the non-common points.Furthermore,as the large condition number of the normal matrix resulted in an intractable form,we introduced the bary-centralization technique and a surrogate process for deterministic element of the normal matrix,and proved its benefit for alleviating the condition number.The experimental results show that our approach can obtain the smaller condition number to stabilize the convergence of the interested parameters.Especially,our approach can be implemented for considering the errors of the common and the non-common points,thus the accuracy of the transformed coordinates improves.
基金supported by the National Natural Science Foundation of China(No.42174011 and No.41874001).
文摘To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.
基金The research was supported by the National Natural Science Foundation of China(41204003)Scientific Research Foundation of ECIT(DHBK201113)Scientific Research Foundation of Jiangxi Province Key Laboratory for Digital Land(DLLJ201207)
文摘Through theoretical derivation, some properties of the total least squares estimation are found. The total least squares estimation is the linear transformation of the least squares estimation, and the total least squares estimation is unbiased. The condition number of the total least squares estimation is greater than the least squares estimation, so the total least squares estimation is easier to be affected by the data error than the least squares estimation. Then through the further derivation, the relationships of solutions, residuals and unit weight variance estimations between the total least squares and the least squares are given.
文摘Static models of accessibility are usually based on the fixed distance or Average Travel Time(ATT)models.Because of ignoring the traffic as a dynamic process affecting the accessibility through the change of Travel Time(TT),these models lead to unperceived temporal inequities.In contrast to the consideration of the temporal Variation of TT(VTT)in the previous studies,the variation of traffic-related TT and its relations with network distance has not been considered.In this study,relations between VTT and network distance to access urban parks in Tehran megacity has been modeled.Traffic maps at five times of day are used to produce TT maps of Traffic Analysis Zones(TAZs)to their 3-closest parks.Comparison of the Gini coefficients of accessibility show significant inequities of accessibility at different times of day.Relations between the distance,ATT,and TT_(max) are modeled by statistical analysis.Results show both TT and TTmax have significant positive relations with distance and traffic and reach their maximum at 6 p.m.Observation of significant relations between distance,ATT,TT_(max),and VTT provides interesting knowledge for the conversion of temporal measures of equity(TT)to a physical measure of equity(distance).A simple application of these findings for effective management of the spatiotemporal inequities is the definition of critical distances from public services.As an example,to decrease the TT_(max) of TAZs to less than 12 min,their maximum distance to the closest parks should be less than 4 km.The developed approach can be adopted for the accessibility evaluation of the other public services,particularly the health and education centers.
